Increased spontaneous neuronal activity in structurally damaged cortex is correlated with early motor recovery in patients with subcortical infarction.
Liu G,Dang C,Peng K,Xie C,Chen H,Xing S,Chen X,Zeng J
European journal of neurology
BACKGROUND AND PURPOSE:Secondary cortical thinning and volumetric atrophy in the motor-related cortex can inhibit early functional recovery after subcortical infarction. However, the relationship between the spontaneous neuronal activity in these cortices and motor recovery in patients with focal cerebral infarct remains unknown. METHODS:Structural magnetic resonance imaging (MRI) and resting-state functional MRI were conducted 1, 4 and 12 weeks after onset in 22 patients with an acute subcortical infarct and in 22 normal subjects. Group differences in cortical thickness and in the amplitude of low-frequency fluctuation (ALFF) in motor-related areas were evaluated, and the relationships between ALFF, cortical thickness changes and changes in the Fugl-Meyer scores of physical performance were further analyzed. RESULTS:In patients with subcortical infarction, progressively decreasing cortical thickness was found over the observation period ipsilesionally in the primary motor cortex (PMC), supplementary motor cortex (SMC) and precuneus (all P < 0.05). Contralesionally, progressive increases in cortical thickness were detected in SMC and insula (all P < 0.05). Increases in ALFF were observed only in PMC (bilaterally) and only at 12 weeks after stroke (all P < 0.05). The cortical thickness changes in the contralesional SMC (rs = 0.483, P = 0.023) and the ALFF changes in bilateral PMC (ipsilesional, rs = 0.51, P = 0.015; contralesional, rs = 0.463, P = 0.03) were positively correlated with changes in the Fugl-Meyer scores. CONCLUSIONS:These results suggest that increased spontaneous neuronal activity of the PMC, a region structurally damaged secondarily to ischaemic lesion, may contribute to early motor recovery in patients with subcortical infarction.
10.1111/ene.12780
Relationship between temporal dynamics of intrinsic brain activity and motor function remodeling in patients with acute BGIS.
Frontiers in neuroscience
Background:patients with acute basal ganglia ischemic stroke (BGIS) show changes in local brain activity represented by the amplitude of low-frequency fluctuation (ALFF), but the time-varying characteristics of this local nerve activity are still unclear. This study aimed to investigate the abnormal time-varying local brain activity of patients with acute BGIS by using the ALFF method combined with the sliding-window approach. Methods:In this study, 34 patients with acute BGIS with motor dysfunction and 44 healthy controls (HCs) were recruited. The dynamic amplitude of low-frequency fluctuation (dALFF) was employed to detect the alterations in brain activity induced by acute BGIS patients. A two-sample -test comparison was performed to compare the dALFF value between the two groups and a Spearman correlation analysis was conducted to assess the relationship between the local brain activity abnormalities and clinical characteristics. Results:Compared with HCs, the activity of neurons in the left temporal pole (TP), parahippocampal gyrus (paraHIP), middle occipital gyrus (MOG), dorsolateral superior frontal gyrus (SFGdl), medial cingulate cortex (MCC), right rectus, precuneus (PCu) and right cerebellum crus1 were significantly increased in patients with BGIS. In addition, we found that there was a negative correlation ( = -0.458, = 0.007) between the dALFF value of the right rectus and the scores of the National Institutes of Health Stroke Scale (NIHSS), and a positive correlation ( = 0.488, 0.499, < 0.05) with the scores of the Barthel Index scale (BI) and the Fugl Meyer motor function assessment (FMA). ROC analysis results demonstrated that the area under the curves (AUC) of the right rectus was 0.880, <0.001. Conclusion:The pattern of intrinsic brain activity variability was altered in patients with acute BGIS compared with HCs. The abnormal dALFF variability might be a potential tool to assess motor function in patients with acute BGIS and potentially inform the diagnosis of this disease.
10.3389/fnins.2023.1154018
The Local Brain Abnormalities in Patients With Transient Ischemic Attack: A Resting-State fMRI Study.
Lv Yating,Li Lingyu,Song Yulin,Han Yu,Zhou Chengshu,Zhou Dan,Zhang Fuding,Xue Qiming,Liu Jinling,Zhao Lijuan,Zhang Cairong,Han Xiujie
Frontiers in neuroscience
Transient ischemic attack (TIA) is an important risk factor for stroke. Despite the transient episodes of clinical symptoms, brain alterations are still observed in patients with TIA. However, the functional mechanism of transient ischemia is still unclear. Here, we employed resting-state functional magnetic resonance imaging (rs-fMRI) to explore the functional abnormalities in patients with TIA. 48 TIA patients and 41 age- and sex-matched healthy controls (HCs) were enrolled in the study. For each participant, we collected rs-fMRI data and clinical/physiological/biochemical data. Amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) were then calculated. Two sample -tests were performed to compare the ALFF, ReHo, and DC maps between the two groups. Furthermore, a correlation analysis was performed to explore the relationship between local brain abnormalities and clinical/physiological/biochemical characteristics tests in TIA patients. Compared with the HCs, the TIA patients exhibited decreased ALFF in the left middle temporal gyrus, decreased DC in the triangular part of right inferior frontal gyrus, and no significant statistical difference in ReHo. No correlation was found between local abnormalities and clinical/physiological/biochemical scores in the patients with TIA. Collectively, we found decreased ALFF and DC in patients with TIA which provide evidence for local brain dysfunctions and may help to understand the pathological mechanism for the disease.
10.3389/fnins.2019.00024
Functional and structural brain reorganization in patients with ischemic stroke: a multimodality MRI fusion study.
Cerebral cortex (New York, N.Y. : 1991)
Understanding how structural and functional reorganization occurs is crucial for stroke diagnosis and prognosis. Previous magnetic resonance imaging (MRI) studies focused on the analyses of a single modality and demonstrated abnormalities in both lesion regions and their associated distal regions. However, the relationships of multimodality alterations and their associations with poststroke motor deficits are still unclear. In this study, 71 hemiplegia patients and 41 matched healthy controls (HCs) were recruited and underwent MRI examination at baseline and at 2-week follow-up sessions. A multimodal fusion approach (multimodal canonical correlation analysis + joint independent component analysis), with amplitude of low-frequency fluctuation (ALFF) and gray matter volume (GMV) as features, was used to extract the co-altered patterns of brain structure and function. Then compared the changes in patients' brain structure and function between baseline and follow-up sessions. Compared with HCs, the brain structure and function of stroke patients decreased synchronously in the local lesions and their associated distal regions. Damage to structure and function in the local lesion regions was associated with motor function. After 2 weeks, ALFF in the local lesion regions was increased, while GMV did not improve. Taken together, the brain structure and function in the local lesions and their associated distal regions were damaged synchronously after ischemic stroke, while during motor recovery, the 2 modalities were changed separately.
10.1093/cercor/bhad295
Frequency-Specific Changes of Amplitude of Low-Frequency Fluctuations in Patients with Acute Basal Ganglia Ischemic Stroke.
Quan Xuemei,Hu Su,Meng Chaoguo,Cheng Lulu,Lu Yujie,Xia Yumei,Li Wenmei,Liang Huo,Li Mengting,Liang Zhijian
Neural plasticity
Objective:The purpose of this study was to investigate the characteristics of different frequency bands in the spontaneous brain activity among patients with acute basal ganglia ischemic stroke (BGIS). Methods:In the present study, thirty-four patients with acute BGIS and forty-four healthy controls were examined by resting-state functional magnetic resonance imaging (rs-fMRI) from May 2019 to December 2020. Two amplitude methods including amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) calculated in three frequency bands (conventional frequency band: 0.01-0.08 Hz; slow-5 frequency band: 0.01-0.027 Hz; and slow-4 frequency band: 0.027-0.073 Hz) were conducted to evaluate the spontaneous brain activity in patients with acute BGIS and healthy controls (HCs). Gaussian Random Field Theory (GRF, voxel < 0.01 and cluster < 0.05) correction was applied. The correlation analyses were performed between clinical scores and altered metrics values. Results:Compared to HCs, patients with acute BGIS showed decreased ALFF in the right supramarginal gyrus (SMG) in the conventional and slow-4 bands, increased fALFF in the right middle frontal gyrus (MFG) in the conventional and slow-4 bands, and increased fALFF in the bilateral caudate in the slow-5 frequency band. The fALFF value of the right caudate in the slow-5 frequency band was negatively correlated with the clinical scores. Conclusion:In conclusion, this study showed the alterations in ALFF and fALFF in three frequency bands between patients with acute BGIS and HCs. The results reflected that the abnormal LFO amplitude might be related with different frequency bands and promoted our understanding of pathophysiological mechanism in acute BGIS.
10.1155/2022/4106131
Dynamic changes of resting state functional network following acute ischemic stroke.
Journal of chemical neuroanatomy
Stroke, the second common cause of death in the world, is commonly considered to the well-known phenomenon of diaschisis. After stroke, regions far from the lesion can show altered neural activity. However, the comprehensive treatment recovery mechanism of acute ischemic stroke remains unclear. This study aims to investigate the impact of comprehensive treatment on resting state brain functional connectivity to reveal the therapeutic mechanism through a three time points study design. Twenty-one acute ischemic stroke patients and twenty matched healthy controls (HC) were included. Resting state functional magnetic resonance imaging (fMRI) and clinical evaluations were assessed in three stages: baseline (less than 72 h after stroke onset), post-first month and post-third month. Amplitude of low-frequency fluctuations (ALFF) and Independent component analysis (ICA) were conducted. We found: 1) stroke patients had decreased ALFF in the right cuneus (one of the important parts of the visual network). After three months, ALFF increased to the normal level; 2) the decreased functional connectivity in the right cuneus within the visual network and restored three months after onset. However, the decreased functional connectivity in the right precuneus within the default mode network restored one month after onset; 3) a significant association was found between the clinical scale score change over time and improvement in the cuneus and precuneus functional connectivity. Our results demonstrate the importance of the cuneus and precuneus within the visual network and default mode network in stroke recovery. These findings suggest that the different restored patterns of neural functional networks may contribute to the neurological function recovery. It has potential applications from stroke onset through rehabilitation because different rehabilitation phase corresponds to specific strategies.
10.1016/j.jchemneu.2023.102272
Reduced Complexity in Stroke with Motor Deficits: A Resting-State fMRI Study.
Liang Liuke,Hu Rongliang,Luo Xuemao,Feng Bao,Long Wansheng,Song Rong
Neuroscience
Recently, alterations of complexity due to brain disorders have been demonstrated using brain entropy (BEN), while the changes of brain complexity in stroke, a common cerebrovascular disease, remain unclear. In this research, resting-state functional magnetic resonance imaging (fMRI) was performed to explore the alterations of brain complexity using BEN in twenty stroke patients with motor deficits and nineteen matched healthy controls. The sample entropy (SampEn) was applied to build the BEN mapping for each participant. Compared with healthy controls, stroke patients exhibited lower BEN values in the contralesional precentral gyrus (preCG), bilateral dorsolateral frontal gyrus (SFGdor) and bilateral supplementary motor area (SMA). Moreover, significantly positive correlations between BEN values and Fugl-Meyer Assessment scores were detected in the ipsilesional SFGdor and ipsilesional SMA. Mutual information independence was observed between BEN and regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), respectively, in the stroke patients. Our findings implied that brain complexity had been impacted after stroke, and also suggested that BEN could be a complementary tool for evaluating the motor impairment after stroke.
10.1016/j.neuroscience.2020.03.020
Altered resting-state FMRI signals in acute stroke patients with ischemic penumbra.
Tsai Yuan-Hsiung,Yuan Rui,Huang Yen-Chu,Weng Hsu-Huei,Yeh Mei-Yu,Lin Ching-Po,Biswal Bharat B
PloS one
BACKGROUND:Identifying the ischemic penumbra in acute stroke subjects is important for the clinical decision making process. The aim of this study was to use resting-state functional magnetic resonance singal (fMRI) to investigate the change in the amplitude of low-frequency fluctuations (ALFF) of these subjects in three different subsections of acute stroke regions: the infarct core tissue, the penumbra tissue, and the normal brain tissue. Another aim of this study was to test the feasilbility of consistently detecting the penumbra region of the brain through ALFF analysis. METHODS:Sixteen subjects with first-ever acute ischemic stroke were scanned within 27 hours of the onset of stroke using magnetic resonance imaging. The core of infarct regions and penumbra regions were determined by diffusion and perfusion-weighted imaging respectively. The ALFF were measured from resting-state blood oxygen level dependent (BOLD) fMRI scans. The averaged relative ALFF value of each regions were correlated with the time after the onset of stroke. RESULTS:Relative ALFF values were significantly different in the infarct core tissue, penumbra tissue and normal brain tissue. The locations of lesions in the ALFF maps did not match perfectly with diffusion and perfusion-weighted imagings; however, these maps provide a contrast that can be used to differentiate between penumbra brain tissue and normal brain tissue. Significant correlations between time after stroke onset and the relative ALFF values were present in the penumbra tissue but not in the infarct core and normal brain tissue. CONCLUSION:Preliminary results from this study suggest that the ALFF reflects the underlying neurovascular activity and has a great potential to estimate the brain tissue viability after ischemia. Results also show that the ALFF may contribute to acute stroke imaging for thrombolytic or neuroprotective therapies.
10.1371/journal.pone.0105117
The Predictive Value of Dynamic Intrinsic Local Metrics in Transient Ischemic Attack.
Frontiers in aging neuroscience
BACKGROUND:Transient ischemic attack (TIA) is known as "small stroke." However, the diagnosis of TIA is currently difficult due to the transient symptoms. Therefore, objective and reliable biomarkers are urgently needed in clinical practice. OBJECTIVE:The purpose of this study was to investigate whether dynamic alterations in resting-state local metrics could differentiate patients with TIA from healthy controls (HCs) using the support-vector machine (SVM) classification method. METHODS:By analyzing resting-state functional MRI (rs-fMRI) data from 48 patients with and 41 demographically matched HCs, we compared the group differences in three dynamic local metrics: dynamic amplitude of low-frequency fluctuation (d-ALFF), dynamic fractional amplitude of low-frequency fluctuation (d-fALFF), and dynamic regional homogeneity (d-ReHo). Furthermore, we selected the observed alterations in three dynamic local metrics as classification features to distinguish patients with TIA from HCs through SVM classifier. RESULTS:We found that TIA was associated with disruptions in dynamic local intrinsic brain activities. Compared with HCs, the patients with TIA exhibited increased d-fALFF, d-fALFF, and d-ReHo in vermis, right calcarine, right middle temporal gyrus, opercular part of right inferior frontal gyrus, left calcarine, left occipital, and left temporal and cerebellum. These alternations in the dynamic local metrics exhibited an accuracy of 80.90%, sensitivity of 77.08%, specificity of 85.37%, precision of 86.05%, and area under curve of 0.8501 for distinguishing the patients from HCs. CONCLUSION:Our findings may provide important evidence for understanding the neuropathology underlying TIA and strong support for the hypothesis that these local metrics have potential value in clinical diagnosis.
10.3389/fnagi.2021.808094
One-step analysis of brain perfusion and function for acute stroke patients after reperfusion: A resting-state fMRI study.
Chen Qian,Zhou Junshan,Zhang Hong,Chen Yuchen,Mao Cunnan,Chen Xiangliang,Ni Ling,Zhuo Zhizheng,Zhang Yingdong,Geng Wen,Yin Xindao,Lv Yating
Journal of magnetic resonance imaging : JMRI
BACKGROUND:Resting-state functional magnetic resonance imaging (rs-fMRI) can noninvasively estimate the perfusion and function of the brain. PURPOSE:To investigate the perfusion and functional status using rs-fMRI in acute ischemic stroke (AIS) patients after reperfusion therapy. STUDY TYPE:Prospective. SUBJECTS:Twenty-five AIS patients who underwent dynamic susceptibility contrast (DSC) upon hospital admission and both rs-fMRI and DSC scans at 24 hours after reperfusion therapy. FIELD STRENGTH/SEQUENCE:3T; DSC, rs-fMRI. ASSESSMENT:The time delay of the blood oxygenation level-dependent (BOLD) signal was calculated using time-shift-analysis (TSA) and compared with the time to peak (TTP) derived from the DSC. For patients who exhibited partial or complete reperfusion in the supratentorial hemisphere, we quantified the function of different regions (healthy tissue, reperfused tissue, not reperfused tissue) by using three rs-fMRI measurements (functional connectivity, the amplitude of low-frequency fluctuation [ALFF] and regional homogeneity [ReHo]). Correlations between the functional measurements and modified Rankin Scale (mRS) scores were calculated. STATISTICAL TESTS:Dice coefficient (DC) analysis, two-sample t-tests, Pearson correlation coefficient. RESULTS:Twelve patients who exhibited complete reperfusion on their TTP maps showed no time-delayed areas on the TSA maps. For the remaining 13 patients with partial reperfusion (5/13) or no reperfusion (8/13) on the TTP maps, the TSA detected comparable time-delayed areas. Eleven out of 13 patients showed moderate to good overlap (mean DC, 0.58 ± 0.1) between the TTP and TSA results. Fourteen patients were chosen for functional analyses and most patients (12/14) showed abnormal functional connectivity in the reperfused regions. The reperfused and not reperfused tissues had lower mean ReHo values than those of the healthy tissue (both P < 0.001). The mRS scores showed negative correlation with mean ReHo values of reperfused region (R = -0.523, P = 0.027). DATA CONCLUSION: rs-fMRI might be a useful way to estimate both the perfusion and functional status for AIS patients after reperfusion therapy. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:221-229.
10.1002/jmri.26571
Effect of acupuncture plus conventional treatment on brain activity in ischemic stroke patients: a regional homogeneity analysis.
Wu Ping,Zeng Fang,Yin Canxin,Xiong Yan,Bai Yu,Wang Dan,Zhou Yume,Liang Fanrong,Li Yongxin,Li Ji,Qiu Lihua,Qin Wei,Luo Lu
Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
OBJECTIVE:To determine differences in cerebral activity evoked by acupuncture and conventional stroke treatment, and identify the treatment targets. METHODS:In total, 21 patients were randomly divided into two groups. Group A (11 patients) received both acupuncture and conventional treatment, while group B (10 patients) received conventional treatment only. Resting-state functional magnetic resonance imaging (fMRI) was performed on each participant before and after treatment. Regional homogeneity analysis was performed to investigate the potential mechanism of acupuncture treatment by comparing differences in cerebral activity between treatments. RESULTS:Group A showed higher ReHo in the frontal lobe (BA6, BA46), supra-marginal gyrus (BA40), middle temporal gyrus (BA21), cerebellum, and insula. Group B showed higher ReHo in the frontal lobe (BA6) and parietal lobe (BA3, BA7). CONCLUSION:Acupuncture and conventional treatment triggered relatively different clinical efficacy and brain responses. Acupuncture treatment more significantly improved the symptoms of stroke patients. More marked changes in sensory, emotional, and motor areas (including the frontal lobe, middle temporal gyrus, cerebellum, and insula) might reflect the specific acupuncture mechanism.
Hemispheric Difference of Regional Brain Function Exists in Patients With Acute Stroke in Different Cerebral Hemispheres: A Resting-State fMRI Study.
Frontiers in aging neuroscience
OBJECTIVE:To explore the different compensatory mechanisms of brain function between the patients with brain dysfunction after acute ischemic stroke (AIS) in the dominant hemisphere and the non-dominant hemisphere based on Resting-state Functional Magnetic Resonance Imaging (Rs-fMRI). METHODS:In this trial, 15 healthy subjects (HS) were used as blank controls. In total, 30 hemiplegic patients with middle cerebral artery acute infarction of different dominant hemispheres were divided into the dominant hemisphere group (DH) and the non-dominant hemisphere group (NDH), scanned by a 3.0 T MRI scanner, to obtain the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) and compare the differences. RESULTS:Compared with the HS, increased ALFF values in the brain areas, such as the bilateral midbrain, were observed in DH. Meanwhile decreased ReHo values in the brain areas, such as the right postcentral gyrus (BA3), were also observed. Enhanced ALFF values in the brain areas, such as the left BA6, and enhanced ReHo values in the brain areas, such as the left precuneus, were observed in the NDH. The ALFF and ReHo values of the right BA9 and precentral gyrus were both increased. Compared with DH, the NDH group showed lower ALFF values in the left supplementary motor area and lower ReHo values in the right BA10. CONCLUSION:After acute infarction in the middle cerebral artery of the dominant hemisphere, a compensation mechanism is triggered in brain areas of the ipsilateral cortex regulating motor-related pathways, while some brain areas related to cognition, sensation, and motor in the contralateral cortex are suppressed, and the connection with the peripheral brain regions is weakened. After acute infarction in the middle cerebral artery of the non-dominant hemisphere, compensatory activation appears in motor control-related brain areas of the dominant hemisphere. After acute middle cerebral artery infarction in the dominant hemisphere, compared with the non-dominant hemisphere, functional specificity in the bilateral supplementary motor area weakens. After acute middle cerebral artery infarction in different hemispheres, there are hemispheric differences in the compensatory mechanism of brain function.
10.3389/fnagi.2021.691518
Altered static and dynamic spontaneous neural activity in patients with ischemic pontine stroke.
Frontiers in neuroscience
Objective:The purpose of the study was to investigate the abnormality both of static spontaneous brain activity and dynamic temporal variances following a pontine infarction. Methods:Forty-six patients with chronic left pontine infarction (LPI), thirty-two patients with chronic right pontine infarction (RPI), and fifty healthy controls (HCs) were recruited for the study. The static amplitude of low-frequency fluctuations (sALFF), static regional homogeneity (sReHo), dynamic ALFF (dALFF), and dynamic ReHo (dReHo) were employed to detect the alterations in brain activity induced by an infarction. The Rey Auditory Verbal Learning Test and Flanker task were used to evaluate the verbal memory and visual attention function, respectively. Receiver operating characteristic curve analysis was used to reveal the potential capacity of these metrics to distinguish the patients from HCs. Results:There were significant variations of these static and dynamic metrics in patients with chronic pontine infarction. The altered regions involved the supratentorial regions, including cortex and subcortical. Moreover, the altered metrics were significantly correlated with verbal memory and visual attention. In addition, these static and dynamic metrics also showed potential in distinguishing stroke patients with behavior deficits from HCs. Conclusion:The pontine infarction-induced cerebral activation changes are observed in both motor and cognitive systems, indicating the functional damage and reorganization across the global cerebral level in these patients with subtentorial infarction, and there is a reciprocal effect between motor and cognitive impairment and repair.
10.3389/fnins.2023.1131062
Frequency-specific alterations of regional homogeneity in subcortical stroke patients with different outcomes in hand function.
Zhao Zhiyong,Tang Chaozheng,Yin Dazhi,Wu Jie,Gong Jiayu,Sun Limin,Jia Jie,Xu Dongrong,Fan Mingxia
Human brain mapping
Emerging evidence has suggested that abnormalities in regional spontaneous brain activity following stroke may be detected by intrinsic low-frequency oscillations (LFO) in resting-state functional MRI (R-fMRI). However, the relationship between hand function outcomes following stroke and local LFO synchronization in different frequency bands is poorly understood. In this study, we performed R-fMRI to examine the regional homogeneity (ReHo) at three different frequency bands (slow-5: .01-.027 Hz; slow-4: .027-.08 Hz; and typical band: .01-.1 Hz) in 26 stroke patients with completely paralyzed hands (CPH) and 26 matched patients with partially paralyzed hands (PPH). Compared to the PPH group, decreased ReHo in the bilateral cerebellum posterior lobes and the contralesional cerebellum anterior lobe was observed in the slow-5 band and the slow-4 band in the CPH group, respectively. The mean ReHo values in these regions were positively correlated with the Fugl-Meyer assessment (FMA) scores. In contrast, increased ReHo in the contralesional supplementary motor area and the contralesional superior temporal gyrus was observed in the slow-4 band and the slow-5 band, respectively. The mean ReHo values in these regions were negatively correlated with the FMA scores. Importantly, significant interactions were identified between the frequency bands and the subgroups of patients in the contralesional precentral gyrus and middle frontal gyrus. These findings indicate that frequency-dependent R-fMRI patterns may serve as potential biomarkers of the neural substrates associated with hand function outcomes following stroke.
10.1002/hbm.24277
Brain Functional Changes in Stroke Following Rehabilitation Using Brain-Computer Interface-Assisted Motor Imagery With and Without tDCS: A Pilot Study.
Hu Mengjiao,Cheng Hsiao-Ju,Ji Fang,Chong Joanna Su Xian,Lu Zhongkang,Huang Weimin,Ang Kai Keng,Phua Kok Soon,Chuang Kai-Hsiang,Jiang Xudong,Chew Effie,Guan Cuntai,Zhou Juan Helen
Frontiers in human neuroscience
Brain-computer interface-assisted motor imagery (MI-BCI) or transcranial direct current stimulation (tDCS) has been proven effective in post-stroke motor function enhancement, yet whether the combination of MI-BCI and tDCS may further benefit the rehabilitation of motor functions remains unknown. This study investigated brain functional activity and connectivity changes after a 2 week MI-BCI and tDCS combined intervention in 19 chronic subcortical stroke patients. Patients were randomized into MI-BCI with tDCS group and MI-BCI only group who underwent 10 sessions of 20 min real or sham tDCS followed by 1 h MI-BCI training with robotic feedback. We derived amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) from resting-state functional magnetic resonance imaging (fMRI) data pre- and post-intervention. At baseline, stroke patients had lower ALFF in the ipsilesional somatomotor network (SMN), lower ReHo in the contralesional insula, and higher ALFF/Reho in the bilateral posterior default mode network (DMN) compared to age-matched healthy controls. After the intervention, the MI-BCI only group showed increased ALFF in contralesional SMN and decreased ALFF/Reho in the posterior DMN. In contrast, no post-intervention changes were detected in the MI-BCI + tDCS group. Furthermore, higher increases in ALFF/ReHo/FC measures were related to better motor function recovery (measured by the Fugl-Meyer Assessment scores) in the MI-BCI group while the opposite association was detected in the MI-BCI + tDCS group. Taken together, our findings suggest that brain functional re-normalization and network-specific compensation were found in the MI-BCI only group but not in the MI-BCI + tDCS group although both groups gained significant motor function improvement post-intervention with no group difference. MI-BCI and tDCS may exert differential or even opposing impact on brain functional reorganization during post-stroke motor rehabilitation; therefore, the integration of the two strategies requires further refinement to improve efficacy and effectiveness.
10.3389/fnhum.2021.692304
Frequency-dependent changes in the regional amplitude and synchronization of resting-state functional MRI in stroke.
Zhu Jianfang,Jin Yuanyuan,Wang Kai,Zhou Yumiao,Feng Yue,Yu Maihong,Jin Xiaoqing
PloS one
Resting-state functional magnetic resonance imaging (R-fMRI) has been intensively used to assess alterations of inter-regional functional connectivity in patients with stroke, but the regional properties of brain activity in stroke have not yet been fully investigated. Additionally, no study has examined a frequency effect on such regional properties in stroke patients, although this effect has been shown to play important roles in both normal brain functioning and functional abnormalities. Here we utilized R-fMRI to measure the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo), two major methods for characterizing the regional properties of R-fMRI, in three different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.73 Hz; and typical band: 0.01-0.1 Hz) in 19 stroke patients and 15 healthy controls. Both the ALFF and ReHo analyses revealed changes in brain activity in a number of brain regions, particularly the parietal cortex, in stroke patients compared with healthy controls. Remarkably, the regions with changed activity as detected by the slow-5 band data were more extensive, and this finding was true for both the ALFF and ReHo analyses. These results not only confirm previous studies showing abnormality in the parietal cortex in patients with stroke, but also suggest that R-fMRI studies of stroke should take frequency effects into account when measuring intrinsic brain activity.
10.1371/journal.pone.0123850
Dynamic Alterations in Spontaneous Neural Activity in Multiple Brain Networks in Subacute Stroke Patients: A Resting-State fMRI Study.
Frontiers in neuroscience
To examine whether subacute stroke patients would exhibit abnormal dynamic characteristics of brain activity relative to healthy controls (HC) and to investigate whether the altered dynamic regional indexes were associated with clinical behavior in stroke patients. The dynamic amplitude of low-frequency fluctuations (dALFF) and dynamic regional homogeneity (dReHo) in 42 subacute stroke patients and 55 healthy controls were compared. Correlation analyses between dALFF and dReHo in regions showing significant intergroup differences and clinical scores (i.e., the National Institutes of Health Stroke Scale, Fugl-Meyer assessment and lesion volume size) were conducted in stroke patients. Receiver operating characteristic (ROC) curve analysis was used to determine the potential value of altered dynamic regional indexes to identify stroke patients. Significantly dALFF in the bilateral cerebellum posterior lobe (CPL), ipsilesional superior parietal lobe, ipsilesional inferior temporal gyrus (ITG), the midline supplementary motor area (SMA), ipsilesional putamen and lentiform nucleus were detected in stroke patients compared to HC. Relative to the HC group, the stroke patients showed significant differences in dReHo in the contralesional rectal gyrus, contralesional ITG, contralesional pons, ipsilesional middle frontal gyrus (MFG). Significant correlations between dALFF variability in midline SMA and Fugl-Meyer assessment (FMA) scores or between dReHo variability in the ipsilesional MFG and FMA scores were detected in stroke patients. Furthermore, the ROC curve revealed that dynamic ALFF at SMA and ReHo at ipsilesional MFG might have the potential to distinguish stroke patients. The pattern of intrinsic brain activity variability is altered in stroke patients compared with HC, and dynamic ALFF/ReHo might be potential tools to assess stroke patients' motor function.
10.3389/fnins.2018.00994
Regional homogeneity alterations in multifrequency bands in patients with basal ganglia stroke: A resting-state functional magnetic resonance imaging study.
Frontiers in aging neuroscience
Objective:The aim of this study was to investigate the spontaneous regional neural activity abnormalities in patients with acute basal ganglia ischemic stroke (BGIS) using a multifrequency bands regional homogeneity (ReHo) method and to explore whether the alteration of ReHo values was associated with clinical characteristics. Methods:In this study, 34 patients with acute BGIS and 44 healthy controls (HCs) were recruited. All participants were examined by resting-state functional magnetic resonance imaging (rs-fMRI). The ReHo method was used to detect the alterations of spontaneous neural activities in patients with acute BGIS. A two-sample -test comparison was performed to compare the ReHo value between the two groups, and a Pearson correlation analysis was conducted to assess the relationship between the regional neural activity abnormalities and clinical characteristics. Results:Compared with the HCs, the patients with acute BGIS showed increased ReHo in the left caudate and subregions such as the right caudate and left putamen in conventional frequency bands. In the slow-5 frequency band, patients with BGIS showed decreased ReHo in the left medial cingulum of BGIS compared to the HCs and other subregions such as bilateral caudate and left putamen. No brain regions with ReHo alterations were found in the slow-4 frequency band. Moreover, we found that the ReHo value of left caudate was positively correlated with the NIHSS score. Conclusion:Our findings revealed the alterations of ReHo in patients with acute BGIS in a specific frequency band and provided a new insight into the pathogenesis mechanism of BGIS. This study demonstrated the frequency-specific characteristics of ReHo in patients with acute BGIS, which may have a positive effect on the future neuroimaging studies.
10.3389/fnagi.2022.938646
Biomarkers for prognostic functional recovery poststroke: A narrative review.
Frontiers in cell and developmental biology
Prediction of poststroke recovery can be expressed by prognostic biomarkers that are related to the pathophysiology of stroke at the cellular and molecular level as well as to the brain structural and functional reserve after stroke at the systems neuroscience level. This study aimed to review potential biomarkers that can predict poststroke functional recovery. A narrative review was conducted to qualitatively summarize the current evidence on biomarkers used to predict poststroke functional recovery. Neurophysiological measurements and neuroimaging of the brain and a wide diversity of molecules had been used as prognostic biomarkers to predict stroke recovery. Neurophysiological studies using resting-state electroencephalography (EEG) revealed an interhemispheric asymmetry, driven by an increase in low-frequency oscillation and a decrease in high-frequency oscillation in the ipsilesional hemisphere relative to the contralesional side, which was indicative of individual recovery potential. The magnitude of somatosensory evoked potentials and event-related desynchronization elicited by movement in task-related EEG was positively associated with the quantity of recovery. Besides, transcranial magnetic stimulation (TMS) studies revealed the potential values of using motor-evoked potentials (MEP) and TMS-evoked EEG potentials from the ipsilesional motor cortex as prognostic biomarkers. Brain structures measured using magnetic resonance imaging (MRI) have been implicated in stroke outcome prediction. Specifically, the damage to the corticospinal tract (CST) and anatomical motor connections disrupted by stroke lesion predicted motor recovery. In addition, a wide variety of molecular, genetic, and epigenetic biomarkers, including hemostasis, inflammation, tissue remodeling, apoptosis, oxidative stress, infection, metabolism, brain-derived, neuroendocrine, and cardiac biomarkers, etc., were associated with poor functional outcomes after stroke. However, challenges such as mixed evidence and analytical concerns such as specificity and sensitivity have to be addressed before including molecular biomarkers in routine clinical practice. Potential biomarkers with prognostic values for the prediction of functional recovery after stroke have been identified; however, a multimodal approach of biomarkers for prognostic prediction has rarely been studied in the literature. Future studies may incorporate a combination of multiple biomarkers from big data and develop algorithms using data mining methods to predict the recovery potential of patients after stroke in a more precise way.
10.3389/fcell.2022.1062807
Connectomics underlying motor functional outcomes in the acute period following stroke.
Frontiers in aging neuroscience
Objective:Stroke remains the number one cause of morbidity in many developing countries, and while effective neurorehabilitation strategies exist, it remains difficult to predict the individual trajectories of patients in the acute period, making personalized therapies difficult. Sophisticated and data-driven methods are necessary to identify markers of functional outcomes. Methods:Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI (rsfMRI), and diffusion weighted scans were obtained from 79 patients following stroke. Sixteen models were constructed to predict performance across six tests of motor impairment, spasticity, and activities of daily living, using either whole-brain structural or functional connectivity. Feature importance analysis was also performed to identify brain regions and networks associated with performance in each test. Results:The area under the receiver operating characteristic curve ranged from 0.650 to 0.868. Models utilizing functional connectivity tended to have better performance than those utilizing structural connectivity. The Dorsal and Ventral Attention Networks were among the top three features in several structural and functional models, while the Language and Accessory Language Networks were most commonly implicated in structural models. Conclusions:Our study highlights the potential of machine learning methods combined with connectivity analysis in predicting outcomes in neurorehabilitation and disentangling the neural correlates of functional impairments, though further longitudinal studies are necessary.
10.3389/fnagi.2023.1131415
Infarct growth velocity predicts early neurological outcomes in single subcortical infarction.
Scientific reports
In single subcortical infarction (SSI), changes in lesion size are a major determinant of early neurological deterioration. We evaluated the association between END and infarct growth velocity (IGV) in patients with SSI. We included consecutive patients with SSI who underwent MRI within 24 h of symptom onset between 2010 and 2020. END was defined as an increase of ≥ 2 in the total National Institutes of Health Stroke Scale (NIHSS) score or ≥ 1 in the motor NIHSS score. IGV was calculated using the following formula: IGV (mL/h) = diffusion-weighted imaging volume (mL)/time to MRI (h). A total of 604 patients with SSI were evaluated. Multivariable logistic regression analysis showed that IGV remained significant after adjusting for confounders (aOR = 1.34, 95% CI 1.12-1.61). In a subgroup analysis based on the type of SSI, only patients with distal SSI showed an association between IGV and END (aOR = 1.64, 95% CI 1.24-2.16). In patients with proximal SSI, IGV did not show any statistical association with END. In conclusion, IGV was positively associated with END in patients with SSI. IGV should be interpreted differently in clinical settings depending on the location of the SSI lesion.
10.1038/s41598-023-31727-0
Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages.
Brain communications
Following a stroke in regions of the brain responsible for motor activity, patients can lose their ability to control parts of their body. Over time, some patients recover almost completely, while others barely recover at all. It is known that lesion volume, initial motor impairment and cortico-spinal tract asymmetry significantly impact motor changes over time. Recent work suggested that disabilities arise not only from focal structural changes but also from widespread alterations in inter-regional connectivity. Models that consider damage to the entire network instead of only local structural alterations lead to a more accurate prediction of patients' recovery. However, assessing white matter connections in stroke patients is challenging and time-consuming. Here, we evaluated in a data set of 37 patients whether we could predict upper extremity motor recovery from brain connectivity measures obtained by using the patient's lesion mask to introduce virtual lesions in 60 healthy streamline tractography connectomes. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging. We added these measures to benchmark structural features, and we used a ridge regression regularization to predict motor recovery at 3 months post-injury. As hypothesized, accuracy in prediction significantly increased ( = 0.68) as compared to benchmark features ( = 0.38). This improved prediction of recovery could be beneficial to clinical care and might allow for a better choice of intervention.
10.1093/braincomms/fcad055
Post-reperfusion acute MR diffusion in stroke is a potential predictor for clinical outcome in rats.
Scientific reports
Middle cerebral artery occlusion (MCAO) models show substantial variability in outcome, introducing uncertainties in the evaluation of treatment effects. Early outcome predictors would be essential for prognostic purposes and variability control. We aimed to compare apparent diffusion coefficient (ADC) MRI data obtained during MCAO and shortly after reperfusion for their potentials in acute-phase outcome prediction. Fifty-nine male rats underwent a 45-min MCAO. Outcome was defined in three ways: 21-day survival; 24 h midline-shift and neurological scores. Animals were divided into two groups: rats surviving 21 days after MCAO (survival group, n = 46) and rats dying prematurely (non-survival/NS group, n = 13). At reperfusion, NS group showed considerably larger lesion volume and lower mean ADC of the initial lesion site (p < 0.0001), while during occlusion there were no significant group differences. At reperfusion, each survival animal showed decreased lesion volume and increased mean ADC of the initial lesion site compared to those during occlusion (p < 10), while NS group showed a mixed pattern. At reperfusion, lesion volume and mean ADC of the initial lesion site were significantly associated with 24 h midline-shift and neurological scores. Diffusion MRI performed soon after reperfusion has a great impact in early-phase outcome prediction, and it works better than the measurement during occlusion.
10.1038/s41598-023-32679-1
Deep learning prediction of motor performance in stroke individuals using neuroimaging data.
Journal of biomedical informatics
The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have been used as potential biomarkers of motor recovery, with limited accuracy up to date. To address this, the present study aimed to develop a deep learning model based on structural brain images obtained from stroke participants and healthy volunteers. The following inputs were used in a multi-channel 3D convolutional neural network (CNN) model: fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps obtained from Diffusion Tensor Imaging (DTI) images, white and gray matter intensity values obtained from Magnetic Resonance Imaging, as well as demographic data (e.g., age, gender). Upper limb motor function was classified into "Poor" and "Good" categories. To assess the performance of the DL model, we compared it to more standard machine learning (ML) classifiers including k-nearest neighbor, support vector machines (SVM), Decision Trees, Random Forests, Ada Boosting, and Naïve Bayes, whereby the inputs of these classifiers were the features taken from the fully connected layer of the CNN model. The highest accuracy and area under the curve values were 0.92 and 0.92 for the 3D-CNN and 0.91 and 0.91 for the SVM, respectively. The multi-channel 3D-CNN with residual blocks and SVM supported by DL was more accurate than traditional ML methods to classify upper limb motor impairment in the stroke population. These results suggest that combining volumetric DTI maps and measures of white and gray matter integrity can improve the prediction of the degree of motor impairment after stroke. Identifying the potential of recovery early on after a stroke could promote the allocation of resources to optimize the functional independence of these individuals and their quality of life.
10.1016/j.jbi.2023.104357
A prospective reappraisal of motor outcome prediction in patients with acute stroke by using atlas-based diffusion tensor imaging biomarkers.
Topics in stroke rehabilitation
BACKGROUND:Diffusion tensor imaging (DTI) biomarkers can be used to quantify microstructural changes in the cerebral white matter (WM) following injury. OBJECTIVES:This prospective single-center study aimed to evaluate whether atlas-based DTI-derived metrics obtained within 1 week after stroke can predict the motor outcome at 3 months. METHODS:Forty patients with small acute stroke (2-7 days after onset) involving the corticospinal tract were included. Each patient underwent magnetic resonance imaging (MRI) within 1 week and at 3 months after stroke, and the changes based on DTI-derived metrics were compared by performing WM tract atlas-based quantitative analysis. RESULTS:A total of 40 patients were included, with median age 63.5 years and a majority of males (72.5%). Patients were classified into good-prognosis group (mRS 0-2, = 27) and poor-prognosis group (mRS 3-5, = 13) by outcome. The median (25-75 percentile) of MD (0.7 (0.6-0.7) vs. 0.7 (0.7-0.8); = 0.049) and AD (0.6 (0.5, 0.7) vs. 0.7 (0.6, 0.8); = 0.023) ratios within 1 week were significantly lower in the poor-prognosis group compared to the good-prognosis group. The ROC curve of the combined DTI-derived metrics model showed comparable Youden index (65.5% vs. 58.4%-65.4%) and higher specificity (96.3% vs. 69.2%-88.5%) compared to clinical indexes. The area under the ROC curve of the combined DTI-derived metrics model is comparable to those of the clinical indexes (all > 0.1) and higher than those of the individual DTI-derived metrics parameters. CONCLUSIONS:Atlas-based DTI-derived metrics at acute stage provide objective information for prognosis prediction of patients with ischemic or lacunar stroke.
10.1080/10749357.2023.2214977
Neuroimaging markers of early neurological deterioration in acute isolated pontine infarction.
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND:Imaging indicators of early neurological deterioration (END) in patients with acute isolated pontine infarctions (AIPI) remained ambiguous. We aimed to find more specific neuroimaging markers for the development of END in patients with AIPI. METHODS:Patients with AIPI within 72 h of stroke onset were screened from a stroke database from January 2018 to July 2021 in the First Affiliated Hospital of Zhengzhou University. Clinical characteristics, laboratory tests, and imaging parameters were collected. The layers having the largest infarct area on diffusion-weighted imaging (DWI) and T sequences were chosen. On the transverse plane of DWI and sagittal plane of T-Flair images, the maximum length (a, m) and maximum width (b, n) vertical to the length of the infarcted lesions were measured respectively. On the sagittal plane of T-Flair image, the maximum ventrodorsal length (f) and rostrocaudal thickness (h) were measured. On the sagittal plane, lesions were evenly split into upper, middle, and lower types based on the lesion's location in the pons. The ventral and dorsal types of location were separated based on whether the ventral borders of the pons were involved on transvers plane. END was defined as a ≥2 point increase in the National Institutes of Health Stroke Scale (NIHSS) total score or a ≥1 point increase in the motor items within 72 h after admission. Multivariate logistic regression analyses were used to explore risk factors associated with END. The receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) was performed to estimate the discriminative power and determine the optimal cut-off points of imaging parameters on the prediction of END. RESULTS:A total of 218 patients with AIPI were included in the final analysis. END occurred in 61 cases (28.0%). Multivariate logistic regression analysis showed that the ventral type of lesion location was associated with END in all models adjusted. In addition, in Model 1, b (odds ratio (OR) 1.145, 95% confidence interval (95% CI), 1.007-1.301) and n (OR 1.163, 95% CI 1.012-1.336); in Model 2, bn (OR 1.010, 95% CI 1.002-1.018); in Model 3, n (OR 1.179, 95% CI, 1.028-1.353); and in Model 4, b (OR 1.143, 95% CI 1.006-1.298) and n (OR 1.167, 95% CI 1.016-1.341) were found to be associated with END respectively after different adjustments. ROC curve analysis with END showed that the AUC, the optimal cut-off value, and its sensitivity and specificity were 0.743 (0.671-0.815), 9.850 mm, and 68.9% and 79.0% for b; 0.724 (0.648-0.801), 10.800 mm, and 57.4% and 80.9% for n; and 0.772 (0.701-0.842), 108.274 mm, and 62.3% and 85.4% for b*n, respectively (b*n vs b: P =0.213; b*n vs n: P =0.037; b vs n: P =0.645). CONCLUSIONS:Our study revealed that besides the ventral type of lesion location, the maximum width of lesion on the transverse plane of DWI and sagittal plane of T image (b, n) may be imaging markers for the development of END in AIPI patients, and the product of the two (b*n) showed a better prediction value on the risks of END.
10.1007/s10072-023-06837-2
Neuroimaging mechanisms of acupuncture on functional reorganization for post-stroke motor improvement: a machine learning-based functional magnetic resonance imaging study.
Frontiers in neuroscience
Objective:Motor recovery is crucial in stroke rehabilitation, and acupuncture can influence recovery. Neuroimaging and machine learning approaches provide new research directions to explore the brain functional reorganization and acupuncture mechanisms after stroke. We applied machine learning to predict the classification of the minimal clinically important differences (MCID) for motor improvement and identify the neuroimaging features, in order to explore brain functional reorganization and acupuncture mechanisms for motor recovery after stroke. Methods:In this study, 49 patients with unilateral motor pathway injury (basal ganglia and/or corona radiata) after ischemic stroke were included and evaluated the motor function by Fugl-Meyer Assessment scores (FMA) at baseline and at 2-week follow-up sessions. Patients were divided by the difference between the twice FMA scores into one group showing minimal clinically important difference (MCID group, = 28) and the other group with no minimal clinically important difference (N-MCID, = 21). Machine learning was performed by PRoNTo software to predict the classification of the patients and identify the feature brain regions of interest (ROIs). In addition, a matched group of healthy controls (HC, = 26) was enrolled. Patients and HC underwent magnetic resonance imaging examination in the resting state and in the acupuncture state (acupuncture at the Yanglingquan point on one side) to compare the differences in brain functional connectivity (FC) and acupuncture effects. Results:Through machine learning, we obtained a balance accuracy rate of 75.51% and eight feature ROIs. Compared to HC, we found that the stroke patients with lower FC between these feature ROIs with other brain regions, while patients in the MCID group exhibited a wider range of lower FC. When acupuncture was applied to Yanglingquan (GB 34), the abnormal FC of patients was decreased, with different targets of effects in different groups. Conclusion:Feature ROIs identified by machine learning can predict the classification of stroke patients with different motor improvements, and the FC between these ROIs with other brain regions is decreased. Acupuncture can modulate the bilateral cerebral hemispheres to restore abnormal FC different targets, thereby promoting motor recovery after stroke. Clinical trial registration:https://www.chictr.org.cn/showproj.html?proj=37359, ChiCTR1900022220.
10.3389/fnins.2023.1143239
Novel personalized treatment strategy for patients with chronic stroke with severe upper-extremity impairment: The first patient of the AVANCER trial.
Med (New York, N.Y.)
BACKGROUND:Around 25% of patients who have had a stroke suffer from severe upper-limb impairment and lack effective rehabilitation strategies. The AVANCER proof-of-concept clinical trial (NCT04448483) tackles this issue through an intensive and personalized-dosage cumulative intervention that combines multiple non-invasive neurotechnologies. METHODS:The therapy consists of two sequential interventions, lasting until the patient shows no further motor improvement, for a minimum of 11 sessions each. The first phase involves a brain-computer interface governing an exoskeleton and multi-channel functional electrical stimulation enabling full upper-limb movements. The second phase adds anodal transcranial direct current stimulation of the motor cortex of the lesioned hemisphere. Clinical, electrophysiological, and neuroimaging examinations are performed before, between, and after the two interventions (T0, T1, and T2). This case report presents the results from the first patient of the study. FINDINGS:The primary outcome (i.e., 4-point improvement in the Fugl-Meyer assessment of the upper extremity) was met in the first patient, with an increase from 6 to 11 points between T0 and T2. This improvement was paralleled by changes in motor-network structure and function. Resting-state and transcranial magnetic stimulation-evoked electroencephalography revealed brain functional changes, and magnetic resonance imaging (MRI) measures detected structural and task-related functional changes. CONCLUSIONS:These first results are promising, pointing to feasibility, safety, and potential efficacy of this personalized approach acting synergistically on the nervous and musculoskeletal systems. Integrating multi-modal data may provide valuable insights into underlying mechanisms driving the improvements and providing predictive information regarding treatment response and outcomes. FUNDING:This work was funded by the Wyss-Center for Bio and Neuro Engineering (WCP-030), the Defitech Foundation, PHRT-#2017-205, ERA-NET-NEURON (Discover), and SNSF (320030L_197899, NiBS-iCog).
10.1016/j.medj.2023.06.006
Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach.
Frontiers in aging neuroscience
Background:Stroke is a debilitating disease affecting millions of people worldwide. Despite the survival rate has significantly increased over the years, many stroke survivors are left with severe impairments impacting their quality of life. Rehabilitation programs have proved to be successful in improving the recovery process. However, a reliable model of sensorimotor recovery and a clear identification of predictive markers of rehabilitation-induced recovery are still needed. This article introduces the cross-modality protocols designed to investigate the rehabilitation treatment's effect in a group of stroke survivors. Methods/design:A total of 75 stroke patients, admitted at the IRCCS San Camillo rehabilitation Hospital in Venice (Italy), will be included in this study. Here, we describe the rehabilitation programs, clinical, neuropsychological, and physiological/imaging [including electroencephalography (EEG), transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI) techniques] protocols set up for this study. Blood collection for the characterization of predictive biological biomarkers will also be taken. Measures derived from data acquired will be used as candidate predictors of motor recovery. Discussion/summary:The integration of cutting-edge physiological and imaging techniques, with clinical and cognitive assessment, dose of rehabilitation and biological variables will provide a unique opportunity to define a predictive model of recovery in stroke patients. Taken together, the data acquired in this project will help to define a model of rehabilitation induced sensorimotor recovery, with the final aim of developing personalized treatments promoting the greatest chance of recovery of the compromised functions.
10.3389/fnagi.2023.1205063
Disordered network structure and function in dystonia: pathological connectivity vs. adaptive responses.
Cerebral cortex (New York, N.Y. : 1991)
Primary dystonia is thought to emerge through abnormal functional relationships between basal ganglia and cerebellar motor circuits. These interactions may differ across disease subtypes and provide a novel biomarker for diagnosis and treatment. Using a network mapping algorithm based on resting-state functional MRI (rs-fMRI), a method that is readily implemented on conventional MRI scanners, we identified similar disease topographies in hereditary dystonia associated with the DYT1 or DYT6 mutations and in sporadic patients lacking these mutations. Both networks were characterized by contributions from the basal ganglia, cerebellum, thalamus, sensorimotor areas, as well as cortical association regions. Expression levels for the two networks were elevated in hereditary and sporadic dystonia, and in non-manifesting carriers of dystonia mutations. Nonetheless, the distribution of abnormal functional connections differed across groups, as did metrics of network organization and efficiency in key modules. Despite these differences, network expression correlated with dystonia motor ratings, significantly improving the accuracy of predictions based on thalamocortical tract integrity obtained with diffusion tensor MRI (DTI). Thus, in addition to providing unique information regarding the anatomy of abnormal brain circuits, rs-fMRI functional networks may provide a widely accessible method to help in the objective evaluation of new treatments for this disorder.
10.1093/cercor/bhad012
Predicting Training Gain for a 3 Week Period of Arm Ability Training in the Subacute Stage After Stroke.
Lotze Martin,Roschka Sybille,Domin Martin,Platz Thomas
Frontiers in neurology
Biomarkers for gains of evidence based interventions for upper limb motor training in the subacute stage following stroke have rarely been described. Information about these parameters might help to identify patients who benefit from specific interventions and to determine individually expected behavioral gains for a certain period of therapy. To evaluate predictors for hand motor outcome after arm ability training in the subacute stage after stroke selected from known potentially relevant parameters (initial motor strength, structural integrity of the pyramidal tract and functional motor cortex integrity). We applied the arm ability training (AAT) over 3 weeks to a subpopulation of stroke patients with mild arm paresis, i.e., in 14 patients on average 4 weeks after stroke. The following biomarkers were measured before therapy onset: grip strength on the affected hand, transcranial magnetic stimulation recruitment curve steepness over the primary motor hand area [slope ratio between the ipsilesional hemisphere (IH) and contralesional hemisphere (CH)], and diffusion weighted MRI fractional anisotropy (FA) in the posterior limb of the internal capsule (PLIC; determined as a lateralization index between IH and CH). Outcome was assessed as the AATgain (percentage improvement over training). The "Test d'Evaluation des Membres Supérieurs de Personnes Âgées" (TEMPA) was assessed before and after training to test for possible associations of AAT with activity of daily living. A stepwise linear regression identified the lateralization index of PLIC FA as the only significant predictor for AAT-gain ( = 0.519; = 0.029). AAT-gain was positively associated ( = 0.59; = 0.028) with improvement in arm function during daily activities (TEMPA). While all mildly affected patients achieved a clinically relevant therapeutic effect, pyramidal tract integrity nevertheless had a modifying role for clinical benefit.
10.3389/fneur.2018.00854
On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke.
Frontiers in neuroscience
Recent tract-based analyses provided evidence for the exploitability of 3D-SHORE microstructural descriptors derived from diffusion MRI (dMRI) in revealing white matter (WM) plasticity. In this work, we focused on the main open issues left: (1) the comparative analysis with respect to classical tensor-derived indices, i.e., Fractional Anisotropy (FA) and Mean Diffusivity (MD); and (2) the ability to detect plasticity processes in gray matter (GM). Although signal modeling in GM is still largely unexplored, we investigated their sensibility to stroke-induced microstructural modifications occurring in the contralateral hemisphere. A more complete picture could provide hints for investigating the interplay of GM and WM modulations. Ten stroke patients and ten age/gender-matched healthy controls were enrolled in the study and underwent diffusion spectrum imaging (DSI). Acquisitions at three and two time points () were performed on patients and controls, respectively. For all subjects and acquisitions, FA and MD were computed along with 3D-SHORE-based indices [Generalized Fractional Anisotropy (GFA), Propagator Anisotropy (PA), Return To the Axis Probability (RTAP), Return To the Plane Probability (RTPP), and Mean Square Displacement (MSD)]. Tract-based analysis involving the cortical, subcortical and transcallosal motor networks and region-based analysis in GM were successively performed, focusing on the contralateral hemisphere to the stroke. Reproducibility of all the indices on both WM and GM was quantitatively proved on controls. For tract-based, longitudinal group analyses revealed the highest significant differences across the subcortical and transcallosal networks for all the indices. The optimal regression model for predicting the clinical motor outcome at included GFA, PA, RTPP, and MSD in the subcortical network in combination with the main clinical information at baseline. Region-based analysis in the contralateral GM highlighted the ability of anisotropy indices in discriminating between groups mainly at , while diffusivity indices appeared to be altered at . 3D-SHORE indices proved to be suitable in probing plasticity in both WM and GM, further confirming their viability as a novel family of biomarkers in ischemic stroke in WM and revealing their potential exploitability in GM. Their combination with tensor-derived indices can provide more detailed insights of the different tissue modulations related to stroke pathology.
10.3389/fnins.2018.00092
Non-invasive brain stimulation and neuroenhancement.
Clinical neurophysiology practice
Attempts to enhance human memory and learning ability have a long tradition in science. This topic has recently gained substantial attention because of the increasing percentage of older individuals worldwide and the predicted rise of age-associated cognitive decline in brain functions. Transcranial brain stimulation methods, such as transcranial magnetic (TMS) and transcranial electric (tES) stimulation, have been extensively used in an effort to improve cognitive functions in humans. Here we summarize the available data on low-intensity tES for this purpose, in comparison to repetitive TMS and some pharmacological agents, such as caffeine and nicotine. There is no single area in the brain stimulation field in which only positive outcomes have been reported. For self-directed tES devices, how to restrict variability with regard to efficacy is an essential aspect of device design and function. As with any technique, reproducible outcomes depend on the equipment and how well this is matched to the experience and skill of the operator. For self-administered non-invasive brain stimulation, this requires device designs that rigorously incorporate human operator factors. The wide parameter space of non-invasive brain stimulation, including dose (e.g., duration, intensity (current density), number of repetitions), inclusion/exclusion (e.g., subject's age), and homeostatic effects, administration of tasks before and during stimulation, and, most importantly, placebo or nocebo effects, have to be taken into account. The outcomes of stimulation are expected to depend on these parameters and should be strictly controlled. The consensus among experts is that low-intensity tES is safe as long as tested and accepted protocols (including, for example, dose, inclusion/exclusion) are followed and devices are used which follow established engineering risk-management procedures. Devices and protocols that allow stimulation outside these parameters cannot claim to be "safe" where they are applying stimulation beyond that examined in published studies that also investigated potential side effects. Brain stimulation devices marketed for consumer use are distinct from medical devices because they do not make medical claims and are therefore not necessarily subject to the same level of regulation as medical devices (i.e., by government agencies tasked with regulating medical devices). Manufacturers must follow ethical and best practices in marketing tES stimulators, including not misleading users by referencing effects from human trials using devices and protocols not similar to theirs.
10.1016/j.cnp.2022.05.002
Brain Temperature Measured by Magnetic Resonance Spectroscopy to Predict Clinical Outcome in Patients with Infarction.
Ishida Tomohisa,Inoue Takashi,Inoue Tomoo,Endo Toshiki,Fujimura Miki,Niizuma Kuniyasu,Endo Hidenori,Tominaga Teiji
Sensors (Basel, Switzerland)
Acute ischemic stroke is characterized by dynamic changes in metabolism and hemodynamics, which can affect brain temperature. We used proton magnetic resonance (MR) spectroscopy under everyday clinical settings to measure brain temperature in seven patients with internal carotid artery occlusion to explore the relationship between lesion temperature and clinical course. Regions of interest were selected in the infarct area and the corresponding contralateral region. Single-voxel MR spectroscopy was performed using the following parameters: 2000-ms repetition time, 144-ms echo time, and 128 excitations. Brain temperature was calculated from the chemical shift between water and -acetyl aspartate, choline-containing compounds, or creatine phosphate. Within 48 h of onset, compared with the contralateral region temperature, brain temperature in the ischemic lesion was lower in five patients and higher in two patients. Severe brain swelling occurred subsequently in three of the five patients with lower lesion temperatures, but in neither of the two patients with higher lesion temperatures. The use of proton MR spectroscopy to measure brain temperature in patients with internal carotid artery occlusion may predict brain swelling and subsequent motor deficits, allowing for more effective early surgical intervention. Moreover, our methodology allows for MR spectroscopy to be used in everyday clinical settings.
10.3390/s21020490
Resting state interhemispheric motor connectivity and white matter integrity correlate with motor impairment in chronic stroke.
Chen Joyce L,Schlaug Gottfried
Frontiers in neurology
Functional and structural reorganization in the brain occurs after stroke. The ability to predict motor outcomes may depend on patterns of brain functional and structural connectivity. We tested the hypothesis that alterations in motor transcallosal and corticospinal connections correlate with motor impairment in patients with chronic stroke. Eleven ischemic stroke patients underwent the Upper Extremity Fugl-Meyer (UE-FM) assessment, resting state functional magnetic resonance imaging, and diffusion tensor imaging (DTI). Twelve healthy control subjects underwent DTI. We assessed the temporal coupling in neural activity between interhemispheric motor cortex, and white matter integrity by means of fractional anisotropy (FA), in the transcallosal motor fibers and corticospinal tract. Partial correlation analyses were performed to determine whether these connectivity measures correlate with Upper UE-FM scores. Patients compared to controls had reduced FA in common voxels of transcallosal motor and ipsilesional corticospinal fibers. Within the patient group those with higher interhemispheric motor cortex connectivity and higher FA in the transcallosal motor fibers were less impaired. The results show that markers of functional and structural motor cortex connectivity correlate with motor impairment in the chronic stage of stroke.
10.3389/fneur.2013.00178
Neuronal injury in the motor cortex after chronic stroke and lower limb motor impairment: a voxel-based lesion symptom mapping study.
Reynolds Alexandria M,Peters Denise M,Vendemia Jennifer M C,Smith Lenwood P,Sweet Raymond C,Baylis Gordon C,Krotish Debra,Fritz Stacy L
Neural regeneration research
Many studies have examined motor impairments using voxel-based lesion symptom mapping, but few are reported regarding the corresponding relationship between cerebral cortex injury and lower limb motor impairment analyzed using this technique. This study correlated neuronal injury in the cerebral cortex of 16 patients with chronic stroke based on a voxel-based lesion symptom mapping analysis. Neuronal injury in the corona radiata, caudate nucleus and putamen of patients with chronic stroke could predict walking speed. The behavioral measure scores were consistent with motor deficits expected after damage to the cortical motor system due to stroke. These findings suggest that voxel-based lesion symptom mapping may provide a more accurate prognosis of motor recovery from chronic stroke according to neuronal injury in cerebral motor cortex.
10.4103/1673-5374.131589
Predictors and brain connectivity changes associated with arm motor function improvement from intensive practice in chronic stroke.
Wittenberg George F,Richards Lorie G,Jones-Lush Lauren M,Roys Steven R,Gullapalli Rao P,Yang Suzy,Guarino Peter D,Lo Albert C
F1000Research
The brain changes that underlie therapy-induced improvement in motor function after stroke remain obscure. This study sought to demonstrate the feasibility and utility of measuring motor system physiology in a clinical trial of intensive upper extremity rehabilitation in chronic stroke-related hemiparesis. This was a substudy of two multi-center clinical trials of intensive robotic and intensive conventional therapy arm therapy in chronic, significantly hemiparetic, stroke patients. Transcranial magnetic stimulation was used to measure motor cortical output to the biceps and extensor digitorum communus muscles. Magnetic resonance imaging (MRI) was used to determine the cortical anatomy, as well as to measure fractional anisotropy, and blood oxygenation (BOLD) during an eyes-closed rest state. Region-of-interest time-series correlation analysis was performed on the BOLD signal to determine interregional connectivity. Functional status was measured with the upper extremity Fugl-Meyer and Wolf Motor Function Test. Motor evoked potential (MEP) presence was associated with better functional outcomes, but the effect was not significant when considering baseline impairment. Affected side internal capsule fractional anisotropy was associated with better function at baseline. Affected side primary motor cortex (M1) activity became more correlated with other frontal motor regions after treatment. Resting state connectivity between affected hemisphere M1 and dorsal premotor area (PMAd) predicted recovery. Presence of motor evoked potentials in the affected motor cortex and its functional connectivity with PMAd may be useful in predicting recovery. Functional connectivity in the motor network shows a trends towards increasing after intensive robotic or non-robotic arm therapy. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00372411 \& NCT00333983.
10.12688/f1000research.8603.2
Relation between rich-club organization versus brain functions and functional recovery after acute ischemic stroke.
Wang Lu,Xu Xiaopei,Kai Lau Kui,Li Leonard S W,Kwun Wong Yuen,Yau Christina,Mak Henry K F,Hui Edward S
Brain research
Studies have shown the brain's rich-club organization may underpin brain function and be associated with various brain disorders. In this study, we aimed to investigate the relation between poststroke brain functions and functional recovery versus the rich-club organization of the structural brain network of patients after first-time acute ischemic stroke. A cohort of 16 acute ischemic stroke patients (11 males) was recruited. Structural brain networks were measured using diffusion tensor imaging within 1 week and at 1, 3 and 6 months after stroke. Motor impairment was assessed using the Upper-Extremity Fugl-Meyer motor scale and activities of daily living using the Barthel Index at the same time points as MRI. The rich-club regions that were stable over the course of stroke recovery included the bilateral dorsolateral superior frontal gyri, right supplementary motor area, and left median cingulate and paracingulate gyri. The network properties that correlated with poststroke brain functions were mainly the ratio between communication cost ratio and density ratio of rich-club, feeder and local connections. The recovery of both motor functions and activities of daily living were correlated with higher normalized rich club coefficients and a shorter length of local connections within a week after stroke. The communication cost ratio of feeder connections, the length of rich-club and local connections, and normalized rich club coefficients were found to be potential prognostic indicators of stroke recovery. Our results provide additional support to the notion that different types of network connections play different roles in brain functions as well as functional recovery.
10.1016/j.brainres.2021.147441
Corticospinal excitability as a predictor of functional gains at the affected upper limb following robotic training in chronic stroke survivors.
Milot Marie-Hélène,Spencer Steven J,Chan Vicky,Allington James P,Klein Julius,Chou Cathy,Pearson-Fuhrhop Kristin,Bobrow James E,Reinkensmeyer David J,Cramer Steven C
Neurorehabilitation and neural repair
BACKGROUND:Robotic training can help improve function of a paretic limb following a stroke, but individuals respond differently to the training. A predictor of functional gains might improve the ability to select those individuals more likely to benefit from robot-based therapy. Studies evaluating predictors of functional improvement after a robotic training are scarce. One study has found that white matter tract integrity predicts functional gains following a robotic training of the hand and wrist. Objective. To determine the predictive ability of behavioral and brain measures in order to improve selection of individuals for robotic training. METHODS:Twenty subjects with chronic stroke participated in an 8-week course of robotic exoskeletal training for the arm. Before training, a clinical evaluation, functional magnetic resonance imaging (fMRI), diffusion tensor imaging, and transcranial magnetic stimulation (TMS) were each measured as predictors. Final functional gain was defined as change in the Box and Block Test (BBT). Measures significant in bivariate analysis were fed into a multivariate linear regression model. RESULTS:Training was associated with an average gain of 6 ± 5 blocks on the BBT (P < .0001). Bivariate analysis revealed that lower baseline motor-evoked potential (MEP) amplitude on TMS, and lower laterality M1 index on fMRI each significantly correlated with greater BBT change. In the multivariate linear regression analysis, baseline MEP magnitude was the only measure that remained significant. CONCLUSION:Subjects with lower baseline MEP magnitude benefited the most from robotic training of the affected arm. These subjects might have reserve remaining for the training to boost corticospinal excitability, translating into functional gains.
10.1177/1545968314527351
Disrupted functional connectivity and activity in the white matter of the sensorimotor system in patients with pontine strokes.
Wang Jingjuan,Yang Zhipeng,Zhang Miao,Shan Yi,Rong Dongdong,Ma Qingfeng,Liu Hesheng,Wu Xi,Li Kuncheng,Ding Zhaohua,Lu Jie
Journal of magnetic resonance imaging : JMRI
BACKGROUND:White matter (WM) blood oxygenation level-dependent (BOLD) signals are reported to be related to neural activity. However, sensitivity of WM BOLD signals to disease remains unclear. PURPOSE:To investigate WM BOLD signal changes, directional variations of resting-state correlations in sensorimotor system in patients with pontine strokes, and to determine the relationship between WM BOLD signals and motor deficits. STUDY TYPE:Prospective. SUBJECTS:Ethical approval was obtained from the local Ethics Committee and each participant gave written informed consent. Sixteen patients with focal pontine lesions and 16 age-matched control subjects were included. FIELD STRENGTH/SEQUENCE:3.0T T -weighted anatomic images using a 3D magnetization-prepared rapid gradient-echo sequence. Resting-state fMRI images using gradient-echo echo-planar imaging sequence. Diffusion-weighted images using single-shot spin-echo diffusion echo-planar imaging. ASSESSMENT:Relevant WM tracts in the sensorimotor system by region of interest-wise analysis were identified. Power spectra of BOLD signals and anisotropy of resting-state correlations were measured in sensorimotor system and compared between two groups. Their relationships with clinical scores were analyzed. STATISTICAL TESTS:Two-sample t-test; partial correlation analysis. RESULTS:Power spectra of BOLD signals in nerve tracts on the ipsilesional side were significantly decreased (P < 0.05). Compared with that in healthy subjects, the anisotropy of resting-state correlations along identified WM tracts was decreased in the thalamus-dorsolateral prefrontal cortex bundle on the contralesional side, and all nerve tracts on the ipsilesional side. Partial least squares regression analysis showed the predicted outcome scores correlated significantly with actual Fugl-Meyer scores (R = 0.944, P = 0.013). DATA CONCLUSION:Our findings suggest that disrupted activity and functional connectivity in WM areas of the sensorimotor system can be detected in pontine strokes, and may serve as a biomarker for motor function prediction. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:478-486.
10.1002/jmri.26214
Exploring the brain's structural connectome: A quantitative stroke lesion-dysfunction mapping study.
Kuceyeski Amy,Navi Babak B,Kamel Hooman,Relkin Norman,Villanueva Mark,Raj Ashish,Toglia Joan,O'Dell Michael,Iadecola Costantino
Human brain mapping
The aim of this work was to quantitatively model cross-sectional relationships between structural connectome disruptions caused by cerebral infarction and measures of clinical performance. Imaging biomarkers of 41 ischemic stroke patients (72.0 ± 12.0 years, 20 female) were related to their baseline performance in 18 cognitive, physical and daily life activity assessments. Individual estimates of structural connectivity disruption in gray matter regions were computed using the Change in Connectivity (ChaCo) score. ChaCo scores were utilized because they can be calculated using routinely collected clinical magnetic resonance imagings. Partial Least Squares Regression (PLSR) was used to predict various acute impairment and activity measures from ChaCo scores and patient demographics. Statistical methods of cross-validation, bootstrapping and multiple comparisons correction were implemented to minimize over-fitting and Type I errors. Multiple linear regression models based on lesion volume and lateralization information were constructed for comparison. All models based on connectivity disruption had lower Akaike Information Criterion and almost all had better goodness-of-fit values (R(2) : 0.26-0.92) than models based on lesion characteristics (R(2) : 0.06-0.50). Confidence intervals of PLSR coefficients identified brain regions important in predicting each clinical assessment. Appropriate mapping of eloquent functions, that is, language and motor, and replication of results across pathologies provided validation of this method. Models of complex functions provided new insights into brain-behavior relationships. In addition to the potential applications in prognostication and rehabilitation development, this quantitative approach provides insight into the structural networks underlying complex functions like activities of daily living and cognition. Quantitative analysis of big data will be invaluable in understanding complex brain-behavior relationships.
10.1002/hbm.22761
Classification of Functional Movement Disorders with Resting-State Functional Magnetic Resonance Imaging.
Brain connectivity
Functional movement disorder (FMD) is a type of functional neurological disorder characterized by abnormal movements that patients do not perceive as self-generated. Prior imaging studies show a complex pattern of altered activity, linking regions of the brain involved in emotional responses, motor control, and agency. This study aimed to better characterize these relationships by building a classifier using a support vector machine to accurately distinguish between 61 FMD patients and 59 healthy controls using features derived from resting-state functional magnetic resonance imaging. First, we selected 66 seed regions based on prior related studies, then we calculated the full correlation matrix between them before performing recursive feature elimination to winnow the feature set to the most predictive features and building the classifier. We identified 29 features of interest that were highly predictive of the FMD condition, classifying patients and controls with 80% accuracy. Several key features included regions in the right sensorimotor cortex, left dorsolateral prefrontal cortex, left cerebellum, and left posterior insula. The features selected by the model highlight the importance of the interconnected relationship between areas associated with emotion, reward, and sensorimotor integration, potentially mediating communication between regions associated with motor function, attention, and executive function. Exploratory machine learning was able to identify this distinctive abnormal pattern, suggesting that alterations in functional linkages between these regions may be a consistent feature of the condition in many FMD patients. Clinical-Trials.gov ID: NCT00500994 Impact statement Our research presents novel results that further elucidate the pathophysiology of functional movement disorder (FMD) with a machine learning model that classifies FMD and healthy controls correctly 80% of the time. Herein, we demonstrate how known differences in resting-state functional magnetic resonance imaging connectivity in FMD patients can be leveraged to better understand the complex pattern of neural changes in these patients. Knowing that there are measurable predictable differences in brain activity in patients with FMD may help both clinicians and patients conceptualize and better understand the illness at the point of diagnosis and during treatment. Our methods demonstrate how an effective combination of machine learning and qualitative approaches to analyzing functional brain connectivity can enhance our understanding of abnormal patterns of brain activity in FMD patients.
10.1089/brain.2022.0001
Severe White Matter Hyperintensity Is Associated with Early Neurological Deterioration in Patients with Isolated Pontine Infarction.
Nam Ki-Woong,Lim Jae-Sung,Kang Dong-Wan,Lee Yong-Seok,Han Moon-Ku,Kwon Hyung-Min
European neurology
OBJECTIVE:Pontine infarction is a common type of brain stem infarction and early neurological deterioration (END). We evaluated the possibility of severe white matter hyperintensity (WMH) as a predictor of END in isolated pontine infarction. METHODS:We recruited 2 types of patients with isolated pontine infarction within 24 h from symptom onset. END was defined as an increase of ≥1 point on the motor National Institutes of Health Stroke Scale (NIHSS) or ≥2 points on the total NIHSS score within 72 h from admission. We graded WMH using Fazekas scale, which is dichotomized into mild (grades 0-1) and moderate to severe (grades 2-3) on fluid-attenuated inversion recovery images. RESULTS:A total of 82 patients with an isolated pontine infarction were selected. END was detected in 23 patients (28%). Severe periventricular and subcortical WMH (PVWMH and SCWMH, respectively) were more frequent in deteriorating patients (p = 0.001 and p = 0.019, respectively). A logistic regression analysis revealed that both severe PVWMH (OR 6.17; 95% CI 1.93-19.75, p = 0.002) and SCWMH (OR 3.19; 95% CI 1.10-9.23, p = 0.032) remained independent predictors of END. CONCLUSIONS:Both severe PVWMH and SCWMH were useful to predict END in patients with isolated pontine infarction.
10.1159/000448888
Outcome assessment of hemiparesis due to intracerebral hemorrhage using diffusion tensor fractional anisotropy.
Koyama Tetsuo,Marumoto Kohei,Uchiyama Yuki,Miyake Hiroji,Domen Kazuhisa
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND:This study aimed to evaluate the prognostic efficacy of magnetic resonance diffusion tensor fractional anisotropy (FA) for patients with hemiparesis due to intracerebral hemorrhage. METHODS:Diffusion tensor FA brain images were acquired 14-21 days after putaminal and/or thalamic hemorrhage. The ratio of FA values within the cerebral peduncles of the affected and unaffected hemispheres (rFA) was calculated for each patient (n = 40) and assessed for correlation with Brunnstrom stage (BRS, 1-6), motor component of the functional independence measure (FIM-motor, 13-91), and the total length of stay (LOS) until discharge from rehabilitation (P < .05). Ordinal logistic regression analyses were conducted to determine the relationships between rFA and specific outcomes as measured by BRS range (poor, BRS 1 or 2; moderate, BRS 3 or 4; and good, BRS 5 or 6; P < .05). RESULTS:The rFA values were .571-1.043 (median, .856) and BRS scores were 1-6 (median, 4) for shoulder/elbow/forearm, 1-6 (median, 4) for hand, and 2-6 (median, 4) for lower extremities. FIM-motor scores were 58-86 (median, 78) and LOS ranged from 42 to 225 days (median, 175.5 days). Correlation coefficients were statistically significant between rFA and shoulder/elbow/forearm BRS (.696), hand BRS (.779), lower extremity BRS (.631), FIM-motor (.442), and LOS (-.598). Logistic model fit was moderate for shoulder/elbow/forearm BRS (R(2) = .221) and lower extremity BRS (R(2) = .277), but was much higher for hand BRS (R(2) = .441). CONCLUSIONS:Diffusion tensor FA values are predictive of clinical outcome from hemiparesis due to putaminal and/or thalamic hemorrhage, particularly hand function recovery.
10.1016/j.jstrokecerebrovasdis.2014.12.011
Detection and Predictive Value of Fractional Anisotropy Changes of the Corticospinal Tract in the Acute Phase of a Stroke.
Doughty Christopher,Wang Jasmine,Feng Wuwei,Hackney David,Pani Ethan,Schlaug Gottfried
Stroke
BACKGROUND AND PURPOSE:A decrease in fractional anisotropy (FA) of the ipsilesional corticospinal tract (CST) distal to stroke lesions in the subacute (eg, 30 days) and chronic phase has been correlated with poor motor outcomes, but it is unclear whether FA values obtained within the acute stroke phase (here defined as 80 hours after onset) can predict later outcome. METHODS:Fifty-eight patients underwent an assessment of motor impairment in the acute phase and at 3 months using the upper extremity Fugl-Meyer assessment. FA values, obtained within 80 hours after stroke onset, were determined in 2 regions of interest: cerebral peduncle and a stretch of the CST caudal to each stroke lesion (nearest-5-slices). RESULTS:The FA laterality index for the cerebral peduncle-regions of interest was a poor predictor of 3-month outcome (R(2)=0.044; P=0.137), whereas the slope over the FA laterality index of the nearest-5-slices showed a relatively weak but significant prediction (R(2)=0.11; P=0.022) with the affected side having lower FA values. Initial upper extremity Fugl-Meyer (R(2)=0.69; P<0.001) and the weighted CST lesion load (R(2)=0.71; P<0.001) were strong predictors of 3-month outcome. In multivariate analyses, controlling for initial upper extremity Fugl-Meyer, weighted CST lesion load, and days-of-therapy, neither the FA laterality index of the cerebral peduncle nor the slope over the FA laterality index of the nearest-5-slices significantly contributed to the prediction of 86% of the variance in the upper extremity Fugl-Meyer at 3 months. CONCLUSIONS:FA reductions of the CST can be detected near the ischemic lesion in the acute stroke phase, but offer minimal predictive value to motor outcomes at 3 months.
10.1161/STROKEAHA.115.012088
Predicting arm recovery following stroke: value of site of lesion.
Feys H,Hetebrij J,Wilms G,Dom R,De Weerdt W
Acta neurologica Scandinavica
OBJECTIVES:The aims of this study were to assess whether the site of lesion is predictive of upper limb recovery after stroke and to determine whether this information adds to the predictive ability of the clinical examination. MATERIAL AND METHODS:Forty-five patients were examined at entry to the study and at 2 and 12 months after stroke. The Brunnström-Fugl-Meyer test was used as outcome measurement. Predictor variables included clinical parameters and classifications of lesion site (obtained by CT/MRI). RESULTS:Correlation analysis revealed small to moderate relationships between lesions of subcortical structures and arm outcome at 2 months. In multiple regression analysis, the best model for predicting recovery at 2 months was found to be a combination of the clinical parameters with a purely subcortical lesion. Motor recovery at 12 months was best predicted by the clinical tests alone. The results further indicated that patients with subcortical damage tended to take longer to recover. CONCLUSIONS:Clinical assessment is most useful for determination of the prognosis of upper limb recovery after stroke. Neuroanatomical parameters measured by CT or MRI can only act as an adjunct.
Different Predictive Factors for Early Neurological Deterioration Based on the Location of Single Subcortical Infarction: Early Prognosis in Single Subcortical Infarction.
Nam Ki-Woong,Kwon Hyung-Min,Lee Yong-Seok
Stroke
Background and Purpose:Patients with single subcortical infarctions (SSIs) have relatively a favorable prognosis, but they often experience early neurological deterioration (END). In this study, we compared the predictors for END in patients with SSI according to the location of the lesion. Methods:We included consecutive patients with SSIs within 72 hours of symptom onset presenting between 2010 and 2016. END was defined as an increase of ≥2 in the total National Institutes of Health Stroke Scale (NIHSS) score or ≥1 in the motor NIHSS score within the first 72 hours of admission. Along with the analysis of all patients with SSI, we also analyzed the predictors for END in proximal/distal SSI patients and anterior/posterior circulation SSI patients. Results:A total of 438 patients with SSI were evaluated. In multivariable analysis, initial NIHSS score (adjusted odds ratio, 1.36 [95% CI, 1.15–1.60]), pulsatility index (adjusted odds ratio, 1.25 [95% CI, 1.03–1.52]), parent artery disease (adjusted odds ratio, 2.14 [95% CI, 1.06–4.33]), and neutrophil-to-lymphocyte ratio (adjusted odds ratio, 1.24 [95% CI, 1.04–1.49]) were positively associated with END. In patients with proximal SSI, initial NIHSS score, pulsatility index, parent artery disease, and neutrophil-to-lymphocyte ratio showed positive associations with END. Meanwhile, no variable related to END was found in the distal SSI group. When we compared the predictors for END based on the involved vascular territory, higher initial NIHSS score and neutrophil-to-lymphocyte ratio were significantly associated with END in patients with anterior circulation SSIs. On the contrary, higher pulsatility index values and the presence of parent artery disease were independent predictors for END in patients with SSIs in the posterior circulation. Conclusions:Initial NIHSS score, pulsatility index, parent artery disease, and neutrophil-to-lymphocyte ratio are associated with END in patients with SSIs. The frequency and predictors for END differ depending on the location of the SSI.
10.1161/STROKEAHA.120.032966
Functional Connectivity Changes in Multiple-Frequency Bands in Acute Basal Ganglia Ischemic Stroke Patients: A Machine Learning Approach.
Neural plasticity
Purpose:Several functional magnetic resonance imaging (fMRI) studies have investigated the resting-state functional connectivity (rs-FC) changes in the primary motor cortex (M1) in patients with acute basal ganglia ischemic stroke (BGIS). However, the frequency-specific FC changes of M1 in acute BGIS patients are still unclear. Our study was aimed at exploring the altered FC of M1 in three frequency bands and the potential features as biomarkers for the identification by using a support vector machine (SVM). Methods:We included 28 acute BGIS patients and 42 healthy controls (HCs). Seed-based FC of two regions of interest (ROI, bilateral M1s) were calculated in conventional, slow-5, and slow-4 frequency bands. The abnormal voxel-wise FC values were defined as the features for SVM in different frequency bands. Results:In the ipsilesional M1, the acute BGIS patients exhibited decreased FC with the right lingual gyrus in the conventional and slow-4 frequency band. Besides, the acute BGIS patients showed increased FC with the right medial superior frontal gyrus (SFGmed) in the conventional and slow-5 frequency band and decreased FC with the left lingual gyrus in the slow-5 frequency band. In the contralesional M1, the BGIS patients showed lower FC with the right SFGmed in the conventional frequency band. The higher FC values with the right lingual gyrus and left SFGmed were detected in the slow-4 frequency band. In the slow-5 frequency band, the BGIS patients showed decreased FC with the left calcarine sulcus. SVM results showed that the combined features (slow-4+slow-5) had the highest accuracy in classification prediction of acute BGIS patients, with an area under curve (AUC) of 0.86. Conclusion:Acute BGIS patients had frequency-specific alterations in FC; SVM is a promising method for exploring these frequency-dependent FC alterations. The abnormal brain regions might be potential targets for future researchers in the rehabilitation and treatment of stroke patients.
10.1155/2022/1560748
Utility of Fractional Anisotropy in Cerebral Peduncle for Stroke Outcome Prediction: Comparison of Hemorrhagic and Ischemic Strokes.
Koyama Tetsuo,Koumo Masatoshi,Uchiyama Yuki,Domen Kazuhisa
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND:Diffusion-tensor fractional anisotropy (FA) has been used for predicting stroke outcome. However, most previous studies focused on patients with either hemorrhagic or ischemic stroke. The aim of this study was to assess the correlation between FA and outcome for patients with hemorrhagic stroke and those with ischemic stroke, and then compare their correlation patterns. METHODS:This study sampled 40 hemorrhagic and 40 ischemic stroke patients from our previously published reports. Diffusion-tensor images were obtained on days 14-21, and FA images were generated, after which the ratio of FA within the cerebral peduncles of the affected and unaffected hemispheres (rFA) was calculated. Outcome was assessed using Brunnstrom stage (BRS), motor component of the functional independence measure (FIM-motor), and total length of hospital stay (LOS) at discharge from our affiliated rehabilitation hospital. The data were then compared between the hemorrhage and the infarct groups. Correlation analyses between rFA and outcome assessments were performed separately for both groups and then were compared between the groups. RESULTS:The hemorrhage group exhibited significantly more severe BRS, longer LOS, and lower rFA than the infarct group. The correlations between rFA and outcome measures were all statistically significant for both the hemorrhage and the infarct groups. The correlation patterns for BRS and LOS were very similar between the hemorrhage and the infarct groups. However, such similarity was not evident for FIM-motor. CONCLUSIONS:FA in the cerebral peduncles may be used to predict extremity functions and LOS for both types of stroke.
10.1016/j.jstrokecerebrovasdis.2017.10.022
Integrity of The Hand Fibers of The Corticospinal Tract Shown by Diffusion Tensor Imaging Predicts Hand Function Recovery After Hemorrhagic Stroke.
Gong Zhigang,Zhang Rongjun,Jiang Wenbin,Fu Zhihui
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND:Hand motor function is often severely affected in patients with hemorrhagic stroke. The present study aimed to investigate the feasibility of predicting hand function recovery after hypertensive intracerebral hemorrhage using diffusion tensor imaging (DTI). METHODS:A total of 75 patients with hypertensive intracerebral hemorrhage were prospectively included. DTI of the corticospinal tract (CST) connecting the hand knob area of the precentral gyrus and the cerebral peduncle was performed at around 3 weeks after stroke. Integrity of the CST was evaluated as no disruption, partial disruption, and complete disruption. Hand function was compared by the Brunnstrom recovery stage of hand (BRS-H) at post-stroke 3 weeks and 3 months. RESULTS:Degrees of integrity of the corticospinal cord was negatively correlated with the BRS-H at both post-stroke 3 weeks (r = -0.77, p < 0.01) and 3 months (r = -0.75, p < 0.01). Patients with intact CST or completely disrupted CST shown by DTI did not show significant improvement in the BRS-H at post-stroke 3 months. However, those with partially disrupted CST showed significant improvement in the BRS-H at post-stroke 3 months compared to 3 weeks (3.79 ± 1.36 vs 2.53 ± 1.58, p = 0.012). CONCLUSIONS:DTI can be used to visualize the damage to the hand fibers of the CST. Patients with partially disrupted CST may benefit most from rehabilitation therapy for hand function recovery after hypertensive intracerebral hemorrhage.
10.1016/j.jstrokecerebrovasdis.2020.105447
Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study.
Hu Jianping,Du Juan,Xu Qiang,Yang Fang,Zeng Fanyong,Weng Yifei,Dai Xi-Jian,Qi Rongfeng,Liu Xiaoxue,Lu Guangming,Zhang Zhiqiang
Neural plasticity
Recent fMRI studies have demonstrated that resting-state functional connectivity (FC) is of nonstationarity. Temporal variability of FC reflects the dynamic nature of brain activity. Exploring temporal variability of FC offers a new approach to investigate reorganization and integration of brain networks after stroke. Here, we examined longitudinal alterations of FC temporal variability in brain networks after stroke. Nineteen stroke patients underwent resting fMRI scans across the acute stage (within-one-week after stroke), subacute stage (within-two-weeks after stroke), and early chronic stage (3-4 months after stroke). Nineteen age- and sex-matched healthy individuals were enrolled. Compared with the controls, stroke patients exhibited reduced regional temporal variability during the acute stages, which was recovered at the following two stages. Compared with the acute stage, the subacute stage exhibited increased temporal variability in the primary motor, auditory, and visual cortices. Across the three stages, the temporal variability in the ipsilesional precentral gyrus (PreCG) was increased first and then reduced. Increased temporal variability in the ipsilesional PreCG from the acute stage to the subacute stage was correlated with motor recovery from the acute stage to the early chronic stage. Our results demonstrated that temporal variability of brain network might be a potential tool for evaluating and predicting motor recovery after stroke.
10.1155/2018/9394156
Impact of infarct location on functional outcome following endovascular therapy for stroke.
Rosso Charlotte,Blanc Raphael,Ly Julien,Samson Yves,Lehéricy Stéphane,Gory Benjamin,Marnat Gautier,Mazighi Mikael,Consoli Arturo,Labreuche Julien,Saleme Suzana,Costalat Vincent,Bracard Serge,Desal Hubert,Piotin Michel,Lapergue Bertrand,
Journal of neurology, neurosurgery, and psychiatry
OBJECTIVES:The relationship between stroke topography (ie, the regions damaged by the infarct) and functional outcome can aid clinicians in their decision-making at the acute and later stages. However, the side (left or right) of the stroke may also influence the identification of clinically relevant regions. We sought to determine which brain regions are associated with good functional outcome at 3 months in patients with left-sided and right-sided stroke treated by endovascular treatment using the diffusion-weighted imaging-Alberta Stroke Program Early CT Score (DWI-ASPECTS). METHODS:Patients with ischaemic stroke (n = 405) were included from the ASTER trial and Pitié-Salpêtrière registry. Blinded readers rated ASPECTS on day 1 DWI. Stepwise logistic regression analyses were performed to identify the regions related to 3-month outcome in left (n = 190) and right (n = 215) sided strokes with the modified Rankin scale (0-2) as a binary independent variable and with the 10 regions-of-interest of the DWI-ASPECTS as independent variables. RESULTS:Median National Institute of Health Stroke Scale (NIHSS) at baseline was 17 (IQR: 12-20), median age was 70 years (IQR: 58-80) and median day-one NIHSS 9 (IQR: 4-18). Not all brain regions have the same weight in predicting good outcome at 3 months; moreover, these regions depend on the affected hemisphere. In left-sided strokes, the multivariate analysis revealed that preservation of the caudate nucleus, the internal capsule and the cortical M5 region were independent predictors of good outcome. In right-sided strokes, the cortical M3 and M6 regions were found to be clinically relevant. CONCLUSION:Cortical non-motors areas related to outcome differed between left-sided and right-sided strokes. This difference might reflect the specialisation of the dominant and non-dominant hemispheres for language and attention, respectively. These results may influence decision-making at the acute and later stages. TRIAL REGISTRATION NUMBER:NCT02523261.
10.1136/jnnp-2018-318869
Neuroimaging Identifies Patients Most Likely to Respond to a Restorative Stroke Therapy.
Cassidy Jessica M,Tran George,Quinlan Erin B,Cramer Steven C
Stroke
BACKGROUND AND PURPOSE:Patient heterogeneity reduces statistical power in clinical trials of restorative therapies. Valid predictors of treatment responsiveness are needed, and several have been studied with a focus on corticospinal tract (CST) injury. We studied performance of 4 such measures for predicting behavioral gains in response to motor training therapy. METHODS:Patients with subacute-chronic hemiparetic stroke (n=47) received standardized arm motor therapy, and change in arm Fugl-Meyer score was calculated from baseline to 1 month post-therapy. Injury measures calculated from baseline magnetic resonance imaging included (1) percent CST overlap with stroke, (2) CST-related atrophy (cerebral peduncle area), (3) CST integrity (fractional anisotropy) in the cerebral peduncle, and (4) CST integrity in the posterior limb of internal capsule. RESULTS:Percent CST overlap with stroke, CST-related atrophy, and CST integrity did not correlate with one another, indicating that these 3 measures captured independent features of CST injury. Percent injury to CST significantly predicted treatment-related behavioral gains (=-0.41; =0.004). The other CST injury measures did not, neither did total infarct volume nor baseline behavioral deficits. When directly comparing patients with mild versus severe injury using the percent CST injury measure, the odds ratio was 15.0 (95% confidence interval, 1.54-147; <0.005) for deriving clinically important treatment-related gains. CONCLUSIONS:Percent CST injury is useful for predicting motor gains in response to therapy in the setting of subacute-chronic stroke. This measure can be used as an entry criterion or a stratifying variable in restorative stroke trials to increase statistical power, reduce sample size, and reduce the cost of such trials.
10.1161/STROKEAHA.117.018844
The PREP algorithm predicts potential for upper limb recovery after stroke.
Stinear Cathy M,Barber P Alan,Petoe Matthew,Anwar Samir,Byblow Winston D
Brain : a journal of neurology
Stroke is a leading cause of adult disability and the recovery of motor function is important for independence in activities of daily living. Predicting motor recovery after stroke in individual patients is difficult. Accurate prognosis would enable realistic rehabilitation goal-setting and more efficient allocation of resources. The aim of this study was to test and refine an algorithm for predicting the potential for recovery of upper limb function after stroke. Forty participants were prospectively enrolled within 3 days of ischaemic stroke. First, shoulder abduction and finger extension strength were graded 72 h after stroke onset to compute a shoulder abduction and finger extension score. Secondly, transcranial magnetic stimulation was used to assess the functional integrity of descending motor pathways to the affected upper limb. Third, diffusion-weighted magnetic resonance imaging was used to assess the structural integrity of the posterior limbs of the internal capsules. Finally, these measures were combined in the PREP algorithm for predicting an individual's potential for upper limb recovery at 12 weeks, measured with the Action Research Arm Test. A cluster analysis was used to independently group patients according to Action Research Arm Test score at 12 weeks, for comparison with predictions from the PREP algorithm. There was excellent correspondence between the cluster analysis of Action Research Arm Test score at 12 weeks and predictions made with the PREP algorithm. The algorithm had positive predictive power of 88%, negative predictive power of 83%, specificity of 88% and sensitivity of 73%. This study provides preliminary data in support of the PREP algorithm for the prognosis of upper limb recovery in individual patients. PREP may enable tailored planning of rehabilitation and more accurate stratification of patients in clinical trials.
10.1093/brain/aws146
Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients.
Scientific reports
Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.
10.1038/s41598-022-26945-x
Structural connectome disruption at baseline predicts 6-months post-stroke outcome.
Kuceyeski Amy,Navi Babak B,Kamel Hooman,Raj Ashish,Relkin Norman,Toglia Joan,Iadecola Costantino,O'Dell Michael
Human brain mapping
In this study, models based on quantitative imaging biomarkers of post-stroke structural connectome disruption were used to predict six-month outcomes in various domains. Demographic information and clinical MRIs were collected from 40 ischemic stroke subjects (age: 68.1 ± 13.2 years, 17 female, NIHSS: 6.8 ± 5.6). Diffusion-weighted images were used to create lesion masks, which were uploaded to the Network Modification (NeMo) Tool. The NeMo Tool, using only clinical MRIs, allows estimation of connectome disruption at three levels: whole brain, individual gray matter regions and between pairs of gray matter regions. Partial Least Squares Regression models were constructed for each level of connectome disruption and for each of the three six-month outcomes: applied cognitive, basic mobility and daily activity. Models based on lesion volume were created for comparison. Cross-validation, bootstrapping and multiple comparisons corrections were implemented to minimize over-fitting and Type I errors. The regional disconnection model best predicted applied cognitive (R(2) = 0.56) and basic mobility outcomes (R(2) = 0.70), while the pairwise disconnection model best predicted the daily activity measure (R(2) = 0.72). These results demonstrate that models based on connectome disruption metrics were more accurate than ones based on lesion volume and that increasing anatomical specificity of disconnection metrics does not always increase model accuracy, likely due to statistical adjustments for concomitant increases in data dimensionality. This work establishes that the NeMo Tool's measures of baseline connectome disruption, acquired using only routinely collected MRI scans, can predict 6-month post-stroke outcomes in various functional domains including cognition, motor function and daily activities. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.
10.1002/hbm.23198
Changes of resting cerebral activities in subacute ischemic stroke patients.
Wu Ping,Zeng Fang,Li Yong-Xin,Yu Bai-Li,Qiu Li-Hua,Qin Wei,Li Ji,Zhou Yu-Mei,Liang Fan-Rong
Neural regeneration research
This study aimed to detect the difference in resting cerebral activities between ischemic stroke patients and healthy participants, define the abnormal site, and provide new evidence for pathological mechanisms, clinical diagnosis, prognosis prediction and efficacy evaluation of ischemic stroke. At present, the majority of functional magnetic resonance imaging studies focus on the motor dysfunction and the acute stage of ischemic stroke. This study recruited 15 right-handed ischemic stroke patients at subacute stage (15 days to 11.5 weeks) and 15 age-matched healthy participants. A resting-state functional magnetic resonance imaging scan was performed on each subject to detect cerebral activity. Regional homogeneity analysis was used to investigate the difference in cerebral activities between ischemic stroke patients and healthy participants. The results showed that the ischemic stroke patients had lower regional homogeneity in anterior cingulate and left cerebrum and higher regional homogeneity in cerebellum, left precuneus and left frontal lobe, compared with healthy participants. The experimental findings demonstrate that the areas in which regional homogeneity was different between ischemic stroke patients and healthy participants are in the cerebellum, left precuneus, left triangle inferior frontal gyrus, left inferior temporal gyrus and anterior cingulate. These locations, related to the motor, sensory and emotion areas, are likely potential targets for the neural regeneration of subacute ischemic stroke patients.
10.4103/1673-5374.156977
Prediction of Motor Recovery in Patients with Basal Ganglia Hemorrhage Using Diffusion Tensor Imaging.
Journal of clinical medicine
Predicting prognosis in patients with basal ganglia hemorrhage is difficult. This study aimed to investigate the usefulness of diffusion tensor imaging in predicting motor outcome after basal ganglia hemorrhage. A total of 12 patients with putaminal hemorrhage were included in the study (aged 50 ± 12 years), 8 patients were male (aged 46 ± 11 years) and 4 were female (aged 59 ± 9 years). We performed diffusion tensor imaging and measured clinical outcome at baseline (pre) and 3 weeks (post1), 3 months (post2), and 6 months (post3) after the initial treatment. In the affected side of the brain, the mean fractional anisotropy (FA) value on pons was significantly higher in the good outcome group than that in the poor outcome group at pre ( = 0.004) and post3 ( = 0.025). Pearson correlation analysis showed that mean FA value at pre significantly correlated with the sum of the Brunnstrom motor recovery stage scores at post3 ( = 0.8, = 0.002). Change in the FA ratio on diffusion tractography can predict motor recovery after hemorrhagic stroke.
10.3390/jcm9051304
Brain regions important for recovery after severe post-stroke upper limb paresis.
Rondina Jane M,Park Chang-Hyun,Ward Nick S
Journal of neurology, neurosurgery, and psychiatry
The ability to predict outcome after stroke is clinically important for planning treatment and for stratification in restorative clinical trials. In relation to the upper limbs, the main predictor of outcome is initial severity, with patients who present with mild to moderate impairment regaining about 70% of their initial impairment by 3 months post-stroke. However, in those with severe presentations, this proportional recovery applies in only about half, with the other half experiencing poor recovery. The reasons for this failure to recover are not established although the extent of corticospinal tract damage is suggested to be a contributory factor. In this study, we investigated 30 patients with chronic stroke who had presented with severe upper limb impairment and asked whether it was possible to differentiate those with a subsequent good or poor recovery of the upper limb based solely on a T1-weighted structural brain scan. A support vector machine approach using voxel-wise lesion likelihood values was used to show that it was possible to classify patients as good or poor recoverers with variable accuracy depending on which brain regions were used to perform the classification. While considering damage within a corticospinal tract mask resulted in 73% classification accuracy, using other (non-corticospinal tract) motor areas provided 87% accuracy, and combining both resulted in 90% accuracy. This proof of concept approach highlights the relative importance of different anatomical structures in supporting post-stroke upper limb motor recovery and points towards methodologies that might be used to stratify patients in future restorative clinical trials.
10.1136/jnnp-2016-315030
Modification of Cerebellar Afferent Pathway in the Subacute Phase of Stroke.
Kim Youngkook,Kim Se-Hong,Kim Joon-Sung,Hong Bo Young
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND:This study aims to identify the relationship between corticopontocerebellar tract (CPCT) and corticospinal tract (CST) integrity as well as motor function after stroke. MATERIALS AND METHODS:A total of 33 patients with stroke (18 left, 15 right hemispheric lesions) who underwent diffusion tensor imaging within 2 months of stroke onset and 17 age- and sex-matched healthy controls were retrospectively enrolled. Tract volume and the asymmetry index based on tract volume (AI) of the CST and CPCT were used to identify structural changes in individual tracts and the correlation between those tracts. Motor function was assessed using the Medical Research Council (MRC) muscle scale, manual function test (MFT), functional ambulation category, and modified Barthel index. RESULTS:The volume of the affected CPCT was lower, and that of the unaffected CPCT was higher than the volumes in the control group (P < .001, P = .001, respectively). The CPCT AI showed a strong positive correlation with the CST AI in patients with either left or right hemispheric lesions (r = .779, P < .001; r = .732, P = .003, respectively). The CPCT AI negatively correlated with the MRC muscle scale of the shoulder, wrist, and ankle muscles (r = -.490, -.490, -.416; P = .004, .004, .016, respectively). A higher unaffected CPCT volume was indicative of less affected upper extremity function, as assessed by MFT (r= -.546, P = .029). CONCLUSIONS:Modification of the CPCT depended on CST integrity and was associated with the severity of hemiplegia and hemiplegic upper extremity function. The CPCT may complement the role of the CST and help to predict the motor function.
10.1016/j.jstrokecerebrovasdis.2018.04.039
Comparison of TMS and DTT for predicting motor outcome in intracerebral hemorrhage.
Jang Sung Ho,Ahn Sang Ho,Sakong Joon,Byun Woo Mok,Choi Byung Yun,Chang Chul Hoon,Bai Daiseg,Son Su Min
Journal of the neurological sciences
BACKGROUND:TMS (transcranial magnetic stimulation) and DTT (diffusion tensor tractography) have different advantages in evaluating stroke patients. TMS has good clinical accessibility and economical benefit. On the contrary, DTT has a unique advantage to visualize neural tracts three-dimensionally although it requires an expensive and large MRI machine. Many studies have demonstrated that TMS and DTT have predictive values for motor outcome in stroke patients. However, there has been no study on the comparison of these two evaluation tools. In the current study, we compared the abilities of TMS and DTT to predict upper motor outcome in patients with ICH (intracerebral hemorrhage). METHODS:Fifty-three consecutive patients with severe motor weakness were evaluated by TMS and DTT at the early stage (7-28 days) of ICH. Modified Brunnstrom classification (MBC) and the motricity index of upper extremity (UMI) were evaluated at onset and 6 months after onset. RESULTS:Patients with the presence of a motor evoked potential (MEP) in TMS or a preserved corticospinal tract (CST) in DTT showed better motor outcomes than those without (p=0.000). TMS showed higher positive predictive value than DTT. In contrast, DTT showed higher negative predictive value than TMS. CONCLUSIONS:TMS and DTT had different advantages in predicting motor outcome, and this result could be a reference to predict final neurological deficit at the early stage of ICH.
10.1016/j.jns.2009.10.019
Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information?
Schiemanck Sven K,Kwakkel Gert,Post Marcel W M,Kappelle L Jaap,Prevo Arie J H
Stroke
BACKGROUND AND PURPOSE:To investigate whether neuroimaging information has added predictive value compared with clinical information for independency in activities of daily living (ADL) 1 year after stroke. METHODS:Seventy-five first-ever middle cerebral artery stroke survivors were evaluated in logistic regression analyses. Model 1 was derived on the basis of clinical variables; for model 2, neuroimaging variables were added to model 1. Independent variables were stroke severity (National Institutes of Health Stroke Scale), consciousness (Glasgow Coma Scale), urinary continence, demographic variables (age, gender, relationship, educational level), hospital of admission, and clinical instruments: sitting balance (trunk control test), motor functioning (Motricity Index), and ADL (Barthel Index). Neuroimaging variables, determined on conventional MRI scans, included: number of days to scanning, lesion volume, lesion localization (cortex/subcortex), hemisphere, and the presence of white matter lesions. ADL independency was defined as 19 and 20 points on Barthel Index. Differences in accuracy of prediction of ADL independence between models 1 and 2 were analyzed by comparing areas under the curve (AUC) in a receiver operating characteristic analysis. RESULTS:Model 1 contained as significant predictors: age and ADL (AUC 0.84), correctly predicting 77%. In model 2, number of days to scanning, hemisphere, and lesion volume were added to model 1, increasing the AUC from 0.84 to 0.87, accurately predicting 83% of the surviving patients. CONCLUSIONS:Clinical variables in the second week after stroke are good predictors for independency in ADL 1 year after stroke. Neuroimaging variables on conventional MRI scans do not have added value in long-term prediction of ADL.
10.1161/01.STR.0000206462.09410.6f
Poststroke Impairment and Recovery Are Predicted by Task-Specific Regionalization of Injury.
Jeffers Matthew S,Touvykine Boris,Ripley Allyson,Lahey Gillian,Carter Anthony,Dancause Numa,Corbett Dale
The Journal of neuroscience : the official journal of the Society for Neuroscience
Lesion size and location affect the magnitude of impairment and recovery following stroke, but the precise relationship between these variables and functional outcome is unknown. Herein, we systematically varied the size of strokes in motor cortex and surrounding regions to assess effects on impairment and recovery of function. Female Sprague Dawley rats ( = 64) were evaluated for skilled reaching, spontaneous limb use, and limb placement over a 7 week period after stroke. Exploration and reaching were also tested in a free ranging, more naturalistic, environment. MRI voxel-based analysis of injury volume and its likelihood of including the caudal forelimb area (CFA), rostral forelimb area (RFA), hindlimb (HL) cortex (based on intracranial microstimulation), or their bordering regions were related to both impairment and recovery. Severity of impairment on each task was best predicted by injury in unique regions: impaired reaching, by damage in voxels encompassing CFA/RFA; hindlimb placement, by damage in HL; and spontaneous forelimb use, by damage in CFA. An entirely different set of voxels predicted recovery of function: damage lateral to RFA reduced recovery of reaching, damage medial to HL reduced recovery of hindlimb placing, and damage lateral to CFA reduced recovery of spontaneous limb use. Precise lesion location is an important, but heretofore relatively neglected, prognostic factor in both preclinical and clinical stroke studies, especially those using region-specific therapies, such as transcranial magnetic stimulation. By estimating lesion location relative to cortical motor representations, we established the relationship between individualized lesion location, and functional impairment and recovery in reaching/grasping, spontaneous limb use, and hindlimb placement during walking. We confirmed that stroke results in impairments to specific motor domains linked to the damaged cortical subregion and that damage encroaching on adjacent regions reduces the ability to recover from initial lesion-induced impairments. Each motor domain encompasses unique brain regions that are most associated with recovery and likely represent targets where beneficial reorganization is taking place. Future clinical trials should use individualized therapies (e.g., transcranial magnetic stimulation, intracerebral stem/progenitor cells) that consider precise lesion location and the specific functional impairments of each subject since these variables can markedly affect therapeutic efficacy.
10.1523/JNEUROSCI.0057-20.2020
Reduced functional network connectivity is associated with upper limb dysfunction in acute ischemic brainstem stroke.
Brain imaging and behavior
This study aimed to detect alterations in intra- and inter-network functional connectivity (FC) of multiple networks in acute brainstem ischemic stroke patients, and the relationship between FC and movement assessment scores to assess their ability to predict upper extremity motor impairment. Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from acute brainstem ischemic stroke patients (n = 50) and healthy controls (HCs) (n = 45). Resting-state networks (RSNs) were established based on independent component analysis (ICA) and the functional network connectivity (FNC) analysis was performed. Subsequently, correlation analysis was subsequently used to explore the relationship between FNC abnormalities and upper extremity motor impairment. Altered FC within default mode network (DMN), executive control network (ECN), the salience network (SN), auditory network (AN), and cerebellum network (CN) were found in the acute brainstem ischemic stroke group relative to HCs. Moreover, different patterns of altered network interactions were found between the patients and HCs, including the SN-CN, SN-AN, and ECN-DMN connections. Correlations between functional disconnection and upper limb dysfunction measurements in acute brainstem ischemic stroke patients were also found. This study intimated that widespread FNC impairment and altered integration existed in brainstem ischemic stroke at acute stage, suggesting that FNC disruption may be applied for early diagnosis and prediction of upper limb dysfunction in acute brainstem ischemic stroke.
10.1007/s11682-021-00554-0
Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing.
McGregor Heather R,Gribble Paul L
Journal of neurophysiology
Action observation can facilitate the acquisition of novel motor skills; however, there is considerable individual variability in the extent to which observation promotes motor learning. Here we tested the hypothesis that individual differences in brain function or structure can predict subsequent observation-related gains in motor learning. Subjects underwent an anatomical MRI scan and resting-state fMRI scans to assess preobservation gray matter volume and preobservation resting-state functional connectivity (FC), respectively. On the following day, subjects observed a video of a tutor adapting her reaches to a novel force field. After observation, subjects performed reaches in a force field as a behavioral assessment of gains in motor learning resulting from observation. We found that individual differences in resting-state FC, but not gray matter volume, predicted postobservation gains in motor learning. Preobservation resting-state FC between left primary somatosensory cortex and bilateral dorsal premotor cortex, primary motor cortex, and primary somatosensory cortex and left superior parietal lobule was positively correlated with behavioral measures of postobservation motor learning. Sensory-motor resting-state FC can thus predict the extent to which observation will promote subsequent motor learning. We show that individual differences in preobservation brain function can predict subsequent observation-related gains in motor learning. Preobservation resting-state functional connectivity within a sensory-motor network may be used as a biomarker for the extent to which observation promotes motor learning. This kind of information may be useful if observation is to be used as a way to boost neuroplasticity and sensory-motor recovery for patients undergoing rehabilitation for diseases that impair movement such as stroke.
10.1152/jn.00275.2017
Motor Recovery Prediction With Clinical Assessment and Local Diffusion Homogeneity After Acute Subcortical Infarction.
Liu Gang,Tan Shuangquan,Dang Chao,Peng Kangqiang,Xie Chuanmiao,Xing Shihui,Zeng Jinsheng
Stroke
BACKGROUND AND PURPOSE:Initial clinical assessment or conventional diffusion tensor imaging parameters alone do not reliably predict poststroke recovery of motor function. Recently, local diffusion homogeneity (LDH) has been proposed to represent the local coherence of water molecule diffusion and can serve as a complementary marker for investigating white matter alterations of the brain. We aimed to determine whether a combination of initial clinical assessment and LDH could predict motor recovery after acute subcortical infarction. METHODS:Standard upper extremity Fugl-Meyer assessment and diffusion tensor imaging were performed 1, 4, and 12 weeks after onset in 50 patients with subcortical infarction. Proportional recovery model residuals were used to assign patients to proportional recovery and poor recovery groups. Tract-based spatial statistics analysis was used to compare diffusion differences between proportional and poor recovery outcomes. Multivariate logistic regression model was used to identify the predictors of motor improvement within 12 weeks after stroke. RESULTS:The poor recovery group had lower LDH than the proportional recovery group, mainly in the ipsilesional corticospinal tract in the superior corona radiate and posterior limb of internal capsule 1 week after stroke (<0.005; family-wise error corrected). Multivariate logistic regression analysis indicated that both initial Fugl-Meyer assessment and LDH in the ipsilesional corticospinal tract in the superior corona radiate and posterior limb of internal capsule were predictors of motor improvement within 12 weeks after stroke (G=47.22; <0.001). Leave-one-out cross-validation confirmed a positive predictive value of 0.818, a negative predictive value of 0.833, and an accuracy of 0.824 (<0.00 001; permutation test). CONCLUSIONS:These results suggest that a combination of clinical assessment and LDH in the ipsilesional corticospinal tract in the acute phase can accurately predict resolution of upper limb impairment within 12 weeks after subcortical infarction.
10.1161/STROKEAHA.117.017060
PREP2: A biomarker-based algorithm for predicting upper limb function after stroke.
Stinear Cathy M,Byblow Winston D,Ackerley Suzanne J,Smith Marie-Claire,Borges Victor M,Barber P Alan
Annals of clinical and translational neurology
Objective:Recovery of motor function is important for regaining independence after stroke, but difficult to predict for individual patients. Our aim was to develop an efficient, accurate, and accessible algorithm for use in clinical settings. Clinical, neurophysiological, and neuroimaging biomarkers of corticospinal integrity obtained within days of stroke were combined to predict likely upper limb motor outcomes 3 months after stroke. Methods:Data from 207 patients recruited within 3 days of stroke [103 females (50%), median age 72 (range 18-98) years] were included in a Classification and Regression Tree analysis to predict upper limb function 3 months poststroke. Results:The analysis produced an algorithm that sequentially combined a measure of upper limb impairment; age; the presence or absence of upper limb motor evoked potentials elicited with transcranial magnetic stimulation; and stroke lesion load obtained from MRI or stroke severity assessed with the NIHSS score. The algorithm makes correct predictions for 75% of patients. A key biomarker obtained with transcranial magnetic stimulation is required for one third of patients. This biomarker combined with NIHSS score can be used in place of more costly magnetic resonance imaging, with no loss of prediction accuracy. Interpretation:The new algorithm is more accurate, efficient, and accessible than its predecessors, which may support its use in clinical practice. While further work is needed to potentially incorporate sensory and cognitive factors, the algorithm can be used within days of stroke to provide accurate predictions of upper limb functional outcomes at 3 months after stroke. www.presto.auckland.ac.nz.
10.1002/acn3.488
Contralesional Cortical Structural Reorganization Contributes to Motor Recovery after Sub-Cortical Stroke: A Longitudinal Voxel-Based Morphometry Study.
Cai Jianxin,Ji Qiling,Xin Ruiqiang,Zhang Dianping,Na Xu,Peng Ruchen,Li Kuncheng
Frontiers in human neuroscience
Although changes in brain gray matter after stroke have been identified in some neuroimaging studies, lesion heterogeneity and individual variability make the detection of potential neuronal reorganization difficult. This study attempted to investigate the potential structural cortical reorganization after sub-cortical stroke using a longitudinal voxel-based gray matter volume (GMV) analysis. Eleven right-handed patients with first-onset, subcortical, ischemic infarctions involving the basal ganglia regions underwent structural magnetic resonance imaging in addition to National Institutes of Health Stroke Scale (NIHSS) and Motricity Index (MI) assessments in the acute (<5 days) and chronic stages (1 year later). The GMVs were calculated and compared between the two stages using nonparametric permutation paired t-tests. Moreover, the Spearman correlations between the GMV changes and clinical recoveries were analyzed. Compared with the acute stage, significant decreases in GMV were observed in the ipsilesional (IL) precentral gyrus (PreCG), paracentral gyrus (ParaCG), and contralesional (CL) cerebellar lobule VII in the chronic stage. Additionally, significant increases in GMV were found in the CL orbitofrontal cortex (OFC) and middle (MFG) and inferior frontal gyri (IFG). Furthermore, severe GMV atrophy in the IL PreCG predicted poorer clinical recovery, and greater GMV increases in the CL OFG and MFG predicted better clinical recovery. Our findings suggest that structural reorganization of the CL "cognitive" cortices might contribute to motor recovery after sub-cortical stroke.
10.3389/fnhum.2016.00393
Toward individualized medicine in stroke-The TiMeS project: Protocol of longitudinal, multi-modal, multi-domain study in stroke.
Frontiers in neurology
Despite recent improvements, complete motor recovery occurs in <15% of stroke patients. To improve the therapeutic outcomes, there is a strong need to tailor treatments to each individual patient. However, there is a lack of knowledge concerning the precise neuronal mechanisms underlying the degree and course of motor recovery and its individual differences, especially in the view of brain network properties despite the fact that it became more and more clear that stroke is a network disorder. The TiMeS project is a longitudinal exploratory study aiming at characterizing stroke phenotypes of a large, representative stroke cohort through an extensive, multi-modal and multi-domain evaluation. The ultimate goal of the study is to identify prognostic biomarkers allowing to predict the individual degree and course of motor recovery and its underlying neuronal mechanisms paving the way for novel interventions and treatment stratification for the individual patients. A total of up to 100 patients will be assessed at 4 timepoints over the first year after the stroke: during the first (T1) and third (T2) week, then three (T3) and twelve (T4) months after stroke onset. To assess underlying mechanisms of recovery with a focus on network analyses and brain connectivity, we will apply synergistic state-of-the-art systems neuroscience methods including functional, diffusion, and structural magnetic resonance imaging (MRI), and electrophysiological evaluation based on transcranial magnetic stimulation (TMS) coupled with electroencephalography (EEG) and electromyography (EMG). In addition, an extensive, multi-domain neuropsychological evaluation will be performed at each timepoint, covering all sensorimotor and cognitive domains. This project will significantly add to the understanding of underlying mechanisms of motor recovery with a strong focus on the interactions between the motor and other cognitive domains and multimodal network analyses. The population-based, multi-dimensional dataset will serve as a basis to develop biomarkers to predict outcome and promote personalized stratification toward individually tailored treatment concepts using neuro-technologies, thus paving the way toward personalized precision medicine approaches in stroke rehabilitation.
10.3389/fneur.2022.939640
Indirect Structural Connectivity Identifies Changes in Brain Networks After Stroke.
Sotelo Miguel R,Kalinosky Benjamin T,Goodfriend Karin,Hyngstrom Allison S,Schmit Brian D
Brain connectivity
The purpose of this study was (1) to identify changes in structural connectivity after stroke and (2) to relate changes in indirect connectivity to post-stroke impairment. A novel measure of indirect connectivity was implemented to assess the impact of stroke on brain connectivity. Probabilistic tractography was performed on 13 chronic stroke and 16 control participants to estimate connectivity between gray matter (GM) regions. The Fugl-Meyer assessment of motor impairment was measured for stroke participants. Network measures of direct and indirect connectivity were calculated, and these measures were linearly combined with measures of white matter integrity to predict motor impairment. We found significantly reduced indirect connectivity in the frontal and parietal lobes, ipsilesional subcortical regions, and bilateral cerebellum after stroke. When added to the regression analysis, the volume of GM with reduced indirect connectivity significantly improved the correlation between image parameters and upper extremity motor impairment ( = 0.71, < 0.05). This study provides evidence of changes in indirect connectivity in regions remote from the lesion, particularly in the cerebellum and regions in the fronto-parietal cortices, and these changes correlate with upper extremity motor impairment. These results highlight the value of using measures of indirect connectivity to identify the effect of stroke on brain networks. Impact statement Changes in indirect structural connectivity occur in regions distant from a lesion after stroke, highlighting the impact that stroke has on brain functional networks. Specifically, losses in indirect structural connectivity occur in hubs with high centrality, including the fronto-parietal cortices and cerebellum. These losses in indirect connectivity more accurately reflect motor impairments than measures of direct structural connectivity. As a consequence, indirect structural connectivity appears to be important to recovery after stroke and imaging biomarkers that incorporate indirect structural connectivity might improve prognostication of stroke outcomes.
10.1089/brain.2019.0725
Interhemispheric Functional Connectivity in the Primary Motor Cortex Assessed by Resting-State Functional Magnetic Resonance Imaging Aids Long-Term Recovery Prediction among Subacute Stroke Patients with Severe Hand Weakness.
Min Yu-Sun,Park Jang Woo,Park Eunhee,Kim Ae-Ryoung,Cha Hyunsil,Gwak Dae-Won,Jung Seung-Hwan,Chang Yongmin,Jung Tae-Du
Journal of clinical medicine
This study aimed to evaluate the usefulness of interhemispheric functional connectivity (FC) as a predictor of motor recovery in severe hand impairment and to determine the cutoff FC level as a clinically useful parameter. Patients with stroke ( = 22; age, 59.9 ± 13.7 years) who presented with unilateral severe upper-limb paresis and were confirmed to elicit no motor-evoked potential responses were selected. FC was measured using resting-state functional magnetic resonance imaging (rsfMRI) scans at 1 month from stroke onset. The good recovery group showed a higher FC value than the poor recovery group ( = 0.034). In contrast, there was no statistical difference in FC value between the good recovery and healthy control groups ( = 0.182). Additionally, the healthy control group showed a higher FC value than that shown by the poor recovery group ( = 0.0002). Good and poor recovery were determined based on Brunnstrom stage of upper-limb function at 6 months as the standard, and receiver operating characteristic curve indicated that a cutoff score of 0.013 had the greatest prognostic ability. In conclusion, interhemispheric FC measurement using rsfMRI scans may provide useful clinical information for predicting hand motor recovery during stroke rehabilitation.
10.3390/jcm9040975
Baseline Predictors of Response to Repetitive Task Practice in Chronic Stroke.
Neurorehabilitation and neural repair
BACKGROUND:Repetitive task practice reduces mean upper extremity motor impairment in of patients with chronic stroke, but response is highly variable. A method to predict meaningful reduction in impairment in response to training based on biomarkers and other data collected prior to an intervention is needed to establish realistic rehabilitation goals and to effectively allocate resources. OBJECTIVES:To identify prognostic factors and better understand the biological substrate for reductions in arm impairment in response to repetitive task practice among patients with chronic (≥6 months) post-stroke hemiparesis. METHODS:The intervention is a form of repetitive task practice using a combination of robot-assisted therapy and functional arm use in real-world tasks. Baseline measures include the Fugl-Meyer Assessment, Wolf Motor Function Test, Action Research Arm Test, Stroke Impact Scale, questionnaires on pain and expectancy, MRI, transcranial magnetic stimulation, kinematics, accelerometry, and genomic testing. RESULTS:Mean increase in FM-UE was 4.6 ± 1.0 SE, median 2.5. Approximately one-third of participants had a clinically meaningful response to the intervention, defined as an increase in FM ≥ 5. The selected logistic regression model had a receiver operating curve with AUC = .988 (Std Error = .011, 95% Wald confidence limits: .967-1) showed little evidence of overfitting. Six variables that predicted response represented impairment, functional, and genomic measures. CONCLUSION:A simple weighted sum of 6 baseline factors can accurately predict clinically meaningful impairment reduction after outpatient intensive practice intervention in chronic stroke. Reduction of impairment may be a critical first step to functional improvement. Further validation and generalization of this model will increase its utility in clinical decision-making.
10.1177/15459683221095171
Pathway-Specific Mediation Effect Between Structure, Function, and Motor Impairment After Subcortical Stroke.
Neurology
BACKGROUND AND OBJECTIVE:To investigate the pathway-specific correspondence between structural and functional changes resulting from focal subcortical stroke and their causal influence on clinical symptom. METHODS:In this retrospective, cross-sectional study, we mainly focused on patients with unilateral subcortical chronic stroke with moderate-severe motor impairment assessed by Fugl-Meyer Assessment (upper extremity) and healthy controls. All participants underwent both resting-state fMRI and diffusion tensor imaging. To parse the pathway-specific structure-function covariation, we performed association analyses between the fine-grained corticospinal tracts (CSTs) originating from 6 subareas of the sensorimotor cortex and functional connectivity (FC) of the corresponding subarea, along with the refined corpus callosum (CC) sections and interhemispheric FC. A mediation analysis with FC as the mediator was used to further assess the pathway-specific effects of structural damage on motor impairment. RESULTS:Thirty-five patients (mean age 52.7 ± 10.2 years, 27 men) and 43 healthy controls (mean age 56.2 ± 9.3 years, 21 men) were enrolled. Among the 6 CSTs, we identified 9 structurally and functionally covaried pathways, originating from the ipsilesional primary motor area (M1), dorsal premotor area (PMd), and primary somatosensory cortex ( < 0.05, corrected). FC for the bilateral M1, PMd, and ventral premotor cortex covaried with secondary degeneration of the corresponding CC sections ( < 0.05, corrected). Moreover, these covarying structures and functions were significantly correlated with the Fugl-Meyer Assessment (upper extremity) scores ( < 0.05, uncorrected). In particular, FC between the ipsilesional PMd and contralesional cerebellum (β = -0.141, < 0.05, CI = [-0.319 to -0.015]) and interhemispheric FC of the PMd (β = 0.169, < 0.05, CI = [0.015-0.391]) showed significant mediation effects in the prediction of motor impairment with structural damage of the CST and CC. DISCUSSIONS:This study reveals causal influence of structural and functional pathways on motor impairment after subcortical stroke and provides a promising way to investigate pathway-specific structure-function coupling. Clinically, our findings may offer a circuit-based evidence for the PMd as a critical neuromodulation target in more impaired patients with stroke and also suggest the cerebellum as a potential target.
10.1212/WNL.0000000000201495
White matter integrity of contralesional and transcallosal tracts may predict response to upper limb task-specific training in chronic stroke.
Mattos Daniela J S,Rutlin Jerrel,Hong Xin,Zinn Kristina,Shimony Joshua S,Carter Alexandre R
NeuroImage. Clinical
OBJECTIVE:To investigate white matter (WM) plasticity induced by intensive upper limb (UL) task specific training (TST) in chronic stroke. METHODS:Diffusion tensor imaging data and UL function measured by the Action Research Arm Test (ARAT) were collected in 30 individuals with chronic stroke prior to and after intensive TST. ANOVAs tested the effects of training on the entire sample and on the Responders [ΔARAT ≥ 5.8, N = 13] and Non-Responders [ΔARAT < 5.8, N = 17] groups. Baseline fractional anisotropy (FA) values were correlated with ARATpost TST controlling for baseline ARAT and age to identify voxels predictive of response to TST. RESULTS:While ARAT scores increased following training (p < 0.0001), FA changes within major WM tracts were not significant at p < 0.05. In the Responder group, larger baseline FA of both contralesional (CL) and transcallosal tracts predicted larger ARAT scores post-TST. Subcortical lesions and more severe damage to transcallosal tracts were more pronounced in the Non-Responder than in the Responder group. CONCLUSIONS:The motor improvements post-TST in the Responder group may reflect the engagement of interhemispheric processes not available to the Non-Responder group. Future studies should clarify differences in the role of CL and transcallosal pathways as biomarkers of recovery in response to training for individuals with cortical and subcortical stroke. This knowledge may help to identify sources of heterogeneity in stroke recovery, which is necessary for the development of customized rehabilitation interventions.
10.1016/j.nicl.2021.102710
Multiscale topological properties of functional brain networks during motor imagery after stroke.
De Vico Fallani Fabrizio,Pichiorri Floriana,Morone Giovanni,Molinari Marco,Babiloni Fabio,Cincotti Febo,Mattia Donatella
NeuroImage
In recent years, network analyses have been used to evaluate brain reorganization following stroke. However, many studies have often focused on single topological scales, leading to an incomplete model of how focal brain lesions affect multiple network properties simultaneously and how changes on smaller scales influence those on larger scales. In an EEG-based experiment on the performance of hand motor imagery (MI) in 20 patients with unilateral stroke, we observed that the anatomic lesion affects the functional brain network on multiple levels. In the beta (13-30 Hz) frequency band, the MI of the affected hand (Ahand) elicited a significantly lower smallworldness and local efficiency (Eloc) versus the unaffected hand (Uhand). Notably, the abnormal reduction in Eloc significantly depended on the increase in interhemispheric connectivity, which was in turn determined primarily by the rise of regional connectivity in the parieto-occipital sites of the affected hemisphere. Further, in contrast to the Uhand MI, in which significantly high connectivity was observed for the contralateral sensorimotor regions of the unaffected hemisphere, the regions with increased connectivity during the Ahand MI lay in the frontal and parietal regions of the contralaterally affected hemisphere. Finally, the overall sensorimotor function of our patients, as measured by Fugl-Meyer Assessment (FMA) index, was significantly predicted by the connectivity of their affected hemisphere. These results improve on our understanding of stroke-induced alterations in functional brain networks.
10.1016/j.neuroimage.2013.06.039
Machine Learning for Predicting Motor Improvement After Acute Subcortical Infarction Using Baseline Whole Brain Volumes.
Liu Gang,Wu Jiewei,Dang Chao,Tan Shuangquan,Peng Kangqiang,Guo Yaomin,Xing Shihui,Xie Chuanmiao,Zeng Jinsheng,Tang Xiaoying
Neurorehabilitation and neural repair
Neuroimaging biomarkers are valuable predictors of motor improvement after stroke, but there is a gap between published evidence and clinical usage. In this work, we aimed to investigate whether machine learning techniques, when applied to a combination of baseline whole brain volumes and clinical data, can accurately predict individual motor outcome after stroke. Upper extremity Fugl-Meyer Assessments (FMA-UE) were conducted 1 week and 12 weeks, and structural MRI was performed 1 week, after onset in 56 patients with subcortical infarction. Proportional recovery model residuals were employed to assign patients to proportional and poor recovery groups (34 vs 22). A sophisticated machine learning scheme, consisting of conditional infomax feature extraction, synthetic minority over-sampling technique for nominal and continuous, and bagging classification, was employed to predict motor outcomes, with the input features being a combination of baseline whole brain volumes and clinical data (FMA-UE scores). The proposed machine learning scheme yielded an overall balanced accuracy of 87.71% in predicting proportional vs poor recovery outcomes, a sensitivity of 93.77% in correctly identifying poor recovery outcomes, and a ROC AUC of 89.74%. Compared with only using clinical data, adding whole brain volumes can significantly improve the classification performance, especially in terms of the overall balanced accuracy (from 80.88% to 87.71%) and the sensitivity (from 92.23% to 93.77%). Experimental results suggest that a combination of baseline whole brain volumes and clinical data, when equipped with appropriate machine learning techniques, may provide valuable information for personalized rehabilitation planning after subcortical infarction.
10.1177/15459683211054178
Axial Diffusivity of the Corona Radiata at 24 Hours Post-Stroke: A New Biomarker for Motor and Global Outcome.
Moulton Eric,Amor-Sahli Mélika,Perlbarg Vincent,Pires Christine,Crozier Sophie,Galanaud Damien,Valabregue Romain,Yger Marion,Baronnet-Chauvet Flore,Samson Yves,Dormont Didier,Rosso Charlotte
PloS one
Fractional anisotropy (FA) is an effective marker of motor outcome at the chronic stage of stroke yet proves to be less efficient at early time points. This study aims to determine which diffusion metric in which location is the best marker of long-term stroke outcome after thrombolysis with diffusion tensor imaging (DTI) at 24 hours post-stroke. Twenty-eight thrombolyzed patients underwent DTI at 24 hours post-stroke onset. Ipsilesional and contralesional FA, mean (MD), axial (AD), and radial (RD) diffusivities values were calculated in different Regions-of-Interest (ROIs): (1) the white matter underlying the precentral gyrus (M1), (2) the corona radiata (CoRad), (3) the posterior limb of the internal capsule (PLIC) and (4) the cerebral peduncles (CP). NIHSS scores were acquired at admission, day 1, and day 7; modified Rankin Scores (mRS) at 3 months. Significant decreases were found in FA, MD, and AD of the ipsilesional CoRad and M1. MD and AD were also significantly lower in the PLIC. The ratio of ipsi and contralesional AD of the CoRad (CoRad-rAD) was the strongest diffusion parameter correlated with motor NIHSS scores on day 7 and with the mRS at 3 months. A Receiver-Operator Curve analysis yielded a model for the CoRad-rAD to predict good outcome based on upper limb NIHSS motor scores and mRS with high specificity and sensitivity. FA values were not correlated with clinical outcome. In conclusion, axial diffusivity of the CoRad from clinical DTI at 24 hours post-stroke is the most appropriate diffusion metric for quantifying stroke damage to predict outcome, suggesting the importance of early axonal damage.
10.1371/journal.pone.0142910
White matter integrity is a stronger predictor of motor function than BOLD response in patients with stroke.
Qiu Mingguo,Darling Warren G,Morecraft Robert J,Ni Chun Chun,Rajendra Justin,Butler Andrew J
Neurorehabilitation and neural repair
OBJECTIVE:Neuroimaging techniques, such as diffusion tensor imaging (DTI) and blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI), provide insights into the functional reorganization of the cortical motor system after stroke. This study explores the relationship between upper extremity motor function, white matter integrity, and BOLD response of cortical motor areas. METHODS:Seventeen patients met study inclusion criteria; of these 12 completed DTI assessment of white matter integrity and 9 completed fMRI assessment of motor-related activation. Primary clinical outcome measures were the Wolf Motor Function Test (WMFT) and the upper limb portion of the Fugl-Meyer (FM) motor assessment. Structural integrity of the posterior limb of the internal capsule was assessed by examining the fractional anisotropy (FA) asymmetry in the PLIC. Laterality index of motor cortical areas was measured as the BOLD response in each patient during a finger pinch task. Linear regression analyses were performed to determine whether clinical outcome was associated with structural or functional MRI measures. RESULTS:There were strong relationships between clinical outcome measures and FA asymmetry (eg, FM score [R(2) = .655, P = .001] and WMFT asymmetry score [R(2) = .651, P < .002]) but relationships with fMRI measures were weaker. CONCLUSION:Clinical motor function is more closely related to the white matter integrity of the internal capsule than to BOLD response of motor areas in patients 3 to 9 months after stroke. Thus, use of DTI to assess white matter integrity in the internal capsule may provide more useful information than fMRI to interpret motor deficits following supratentorial brain injury.
10.1177/1545968310389183
Can the site of brain lesion predict improved motor function after low-TENS treatment on the post-stroke paretic arm?
Sonde L,Bronge L,Kalimo H,Viitanen M
Clinical rehabilitation
OBJECTIVES:Previous reports suggest that afferent stimulation improves arm motor function in patients suffering from stroke. The aim of this pilot study was to test the hypothesis that the brain lesion location determines the response to low-frequency (1.7 Hz) transcutaneous electric nerve stimulation (Low-TENS) therapy. DESIGN:Magnetic resonance imaging (MRI) was performed on 14 patients who had previously received Low-TENS on the paretic arm after stroke. METHODS:MR images were classified with two different methods. First, lesions in the cortical and the subcortical areas were registered. Secondly, any change in a described periventricular white matter (PVWM) area was recorded. Interactions between the lesion site, as detected by MRI, and response to Low-TENS treatment were analysed. RESULTS:Arm motor function after Low-TENS treatment in relation to lesion in different brain areas showed that absence of lesions in the PVWM area increased the possibility for improved motor capacity after afferent stimulation. CONCLUSIONS:The site of lesion may play a role in prognosis/outcome after Low-TENS treatment but this hypothesis should be further tested in a larger prospective study.
10.1191/026921501680425261
Location of lesion determines motor vs. cognitive consequences in patients with cerebellar stroke.
NeuroImage. Clinical
Cerebellar lesions can cause motor deficits and/or the cerebellar cognitive affective syndrome (CCAS; Schmahmann's syndrome). We used voxel-based lesion-symptom mapping to test the hypothesis that the cerebellar motor syndrome results from anterior lobe damage whereas lesions in the posterolateral cerebellum produce the CCAS. Eighteen patients with isolated cerebellar stroke (13 males, 5 females; 20-66 years old) were evaluated using measures of ataxia and neurocognitive ability. Patients showed a wide range of motor and cognitive performance, from normal to severely impaired; individual deficits varied according to lesion location within the cerebellum. Patients with damage to cerebellar lobules III-VI had worse ataxia scores: as predicted, the cerebellar motor syndrome resulted from lesions involving the anterior cerebellum. Poorer performance on fine motor tasks was associated primarily with strokes affecting the anterior lobe extending into lobule VI, with right-handed finger tapping and peg-placement associated with damage to the right cerebellum, and left-handed finger tapping associated with left cerebellar damage. Patients with the CCAS in the absence of cerebellar motor syndrome had damage to posterior lobe regions, with lesions leading to significantly poorer scores on language (e.g. right Crus I and II extending through IX), spatial (bilateral Crus I, Crus II, and right lobule VIII), and executive function measures (lobules VII-VIII). These data reveal clinically significant functional regions underpinning movement and cognition in the cerebellum, with a broad anterior-posterior distinction. Motor and cognitive outcomes following cerebellar damage appear to reflect the disruption of different cerebro-cerebellar motor and cognitive loops.
10.1016/j.nicl.2016.10.013
Functional reorganization and prediction of motor recovery after a stroke: A graph theoretical analysis of functional networks.
Lee Jungsoo,Lee Minji,Kim Dae-Shik,Kim Yun-Hee
Restorative neurology and neuroscience
PURPOSE:This study investigated the changes in the network topological configuration of the ipsilesional and contralesional hemispheres after a stroke and the indicators for the prediction of motor recovery using a graph theoretical approach in networks obtained from functional magnetic resonance imaging (fMRI). METHODS:A longitudinal observational experiments (2 weeks and 1, 3, and 6 months after onset) were conducted on 12 patients after a stroke. We investigated the network reorganization during recovery in the ipsilesional and contralesional hemispheres by examining changes of graph indices related to network randomization. We predicted the recovery of motor function by examining the relationship between specific network measures and improved motor function scores. RESULTS:The ipsilesional hemispheric network showed active reorganization during recovery after a stroke. The randomness of the network significantly increased for 3 months post-stroke. We described an indicator for the prediction of the recovery of motor function from graph indices: the characteristic path length. As the path length of the ipsilesional network was lower immediately after onset, the better recovery could be expected after 3 months. CONCLUSIONS:This approach were helpful for understanding dynamic reorganizations of both hemispheric networks after a stroke and finding the implication for recovery.
10.3233/RNN-140467
Pre-therapy Neural State of Bilateral Motor and Premotor Cortices Predicts Therapy Gain After Subcortical Stroke: A Pilot Study.
Cirstea Carmen M,Lee Phil,Craciunas Sorin C,Choi In-Young,Burris Joseph E,Nudo Randolph J
American journal of physical medicine & rehabilitation
OBJECTIVE:The aim of the study was to examine whether neural state of spared motor and premotor cortices captured before a therapy predicts therapy-related motor gains in chronic subcortical stroke. DESIGN:Ten survivors, presenting chronic moderate upper limb impairment, underwent proton magnetic resonance spectroscopy, magnetic resonance imaging, clinical, and kinematics assessments before a 4-wk impairment-oriented training. Clinical/kinematics assessments were repeated after therapy, and motor gain was defined as positive values of clinical upper limb/elbow motion changes and negative values of trunk motion changes. Candidate predictors were N-acetylaspartate-neuronal marker, glutamate-glutamine-indicator of glutamatergic neurotransmission, and myo-inositol-glial marker, measured bilaterally within the upper limb territory in motor and premotor (premotor cortex, supplementary motor area) cortices. Traditional predictors (age, stroke length, pre-therapy upper limb clinical impairment, infarct volume) were also investigated. RESULTS:Poor motor gain was associated with lower glutamate-glutamine levels in ipsilesional primary motor cortex and premotor cortex (r = 0.77, P = 0.01 and r = 0.78, P = 0.008, respectively), lower N-acetylaspartate in ipsilesional premotor cortex (r = 0.69, P = 0.02), higher glutamate-glutamine in contralesional primary motor cortex (r = -0.68, P = 0.03), and lower glutamate-glutamine in contralesional supplementary motor area (r = 0.64, P = 0.04). These predictors outperformed myo-inositol metrics and traditional predictors (P ≈ 0.05-1.0). CONCLUSIONS:Glutamatergic state of bilateral motor and premotor cortices and neuronal state of ipsilesional premotor cortex may be important for predicting motor outcome in the context of a restorative therapy.
10.1097/PHM.0000000000000791
Dynamic Relationship Between Interhemispheric Functional Connectivity and Corticospinal Tract Changing Pattern After Subcortical Stroke.
Frontiers in aging neuroscience
Background and Purpose:Increased interhemispheric resting-state functional connectivity (rsFC) between the bilateral primary motor cortex (M1) compensates for corticospinal tract (CST) impairment, which facilitates motor recovery in chronic subcortical stroke. However, there is a lack of data on the evolution patterns and correlations between M1-M1 rsFC and diffusion indices of CSTs with different origins after subcortical stroke and their relations with long-term motor outcomes. Methods:A total of 44 patients with subcortical stroke underwent longitudinal structural and functional magnetic resonance imaging (MRI) examinations and clinical assessments at four time points. Diffusion tensor imaging was used to extract fractional anisotropy (FA) values of the affected CSTs with different origins. Resting-state functional MRI was used to calculate the M1-M1 rsFC. Longitudinal patterns of functional and anatomic changes in connections were explored using a linear mixed-effects model. Dynamic relationships between M1-M1 rsFC and FA values of the affected specific CSTs and the impact of these variations on the long-term motor outcomes were analyzed in patients with subcortical stroke. Results:Stroke patients showed a significantly decreased FA in the affected specific CSTs and a gradually increasing M1-M1 rsFC from the acute to the chronic stage. The FA of the affected M1 fiber was negatively correlated with the M1-M1 rsFC from the subacute to the chronic stage, FA of the affected supplementary motor area fiber was negatively correlated with the M1-M1 rsFC in the subacute stage, and FA of the affected M1 fiber in the acute stage was correlated with the long-term motor recovery after subcortical stroke. Conclusion:Our findings show that the FA of the affected M1 fiber in the acute stage had the most significant correlation with long-term motor recovery and may be used as an imaging biomarker for predicting motor outcomes after stroke. The compensatory role of the M1-M1 rsFC enhancement may start from the subacute stage in stroke patients with CST impairment.
10.3389/fnagi.2022.870718
Can the integrity of the corticospinal tract predict the long-term motor outcome in poststroke hemiplegic patients?
Kim Ae Ryoung,Kim Dae Hyun,Park So Young,Kyeong Sunghyon,Kim Yong Wook,Lee Seung Koo,Kim Deog Young
Neuroreport
This study aimed to investigate the long-term motor outcome according to early diffusion tensor tractography findings for the affected corticospinal tract (CST) in poststroke hemiplegic patients. A total of 48 supratentorial subacute patients after stroke were enrolled, who had a brain MRI scan within 6 weeks from onset, and no stroke recurrence reported within the 2-year follow-up period. Diffusion tensor images were obtained and CSTs were reconstructed. The participants were classified into three groups: type A, the CST originating from the primary motor cortex was preserved around the lesion area; type B, the CST was similar to type A, except that the fiber originated from the area adjacent to the primary motor cortex; and type C, the CST was interrupted or not shown. Motor functions using Fugl-Meyer Motor Assessment (FMA), the Box and Block Test (BBT), and Functional Ambulation Category, and cognitive function using Mini-Mental Status Examination (MMSE) were measured at baseline and at 2 years from stroke onset. Changes in FMA and BBT were significantly different according to diffusion tensor tractography type at follow-up (P<0.05), but Functional Ambulation Category and Mini-Mental Status Examination were not. In post-hoc analysis, groups A and B showed greater significant improvements on the BBT and on the upper FMA subscale (shoulder/elbow, wrist, and hand) compared with group C (corrected P<0.05), but did not on lower FMA. This study showed the importance of CST integrity for stoke motor recovery. The early integrity of the CST may be useful in predicting long-term motor outcomes, specifically with motor recovery of the upper extremity and hand function.
10.1097/WNR.0000000000000994
Atrophy of spared gray matter tissue predicts poorer motor recovery and rehabilitation response in chronic stroke.
Gauthier Lynne V,Taub Edward,Mark Victor W,Barghi Ameen,Uswatte Gitendra
Stroke
BACKGROUND AND PURPOSE:Although the motor deficit after stroke is clearly due to the structural brain damage that has been sustained, this relationship is attenuated from the acute to chronic phases. We investigated the possibility that motor impairment and response to constraint-induced movement therapy in patients with chronic stroke may relate more strongly to the structural integrity of brain structures remote from the lesion than to measures of overt tissue damage. METHODS:Voxel-based morphometry analysis was performed on MRI scans from 80 patients with chronic stroke to investigate whether variations in gray matter density were correlated with extent of residual motor impairment or with constraint-induced movement therapy-induced motor recovery. RESULTS:Decreased gray matter density in noninfarcted motor regions was significantly correlated with magnitude of residual motor deficit. In addition, reduced gray matter density in multiple remote brain regions predicted a lesser extent of motor improvement from constraint-induced movement therapy. CONCLUSIONS:Atrophy in seemingly healthy parts of the brain that are distant from the infarct accounts for at least a portion of the sustained motor deficit in chronic stroke.
10.1161/STROKEAHA.111.633255
Early motor evoked potentials in acute stroke: adjunctive measure to MRI for assessment of prognosis in acute stroke within 6 hours.
Wöhrle Johannes C,Behrens Stephan,Mielke Orell,Hennerici Michael G
Cerebrovascular diseases (Basel, Switzerland)
BACKGROUND:In acute stroke, a magnetic resonance (MR) perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI) mismatch (PWI>DWI mismatch) may indicate tissue at risk for infarction and poor prognosis. However, different to early enthusiasm about this surrogate marker, its validity has shown several drawbacks in individual patients. Rather than relying on imaging, we evaluated motor evoked potentials (MEP) as a measure of cerebral function in the acute stroke setting. METHODS:Thirteen patients with acute hemiparetic stroke underwent time to peak PWI and DWI within 6 h after onset as well as recordings of early MEP of first dorsal interosseous muscles. Outcome was assessed by the Unified Neurological Stroke Scale and Barthel Index at day 42. RESULTS:Of 8 patients with PWI>DWI mismatch, 4 patients with normal MEP had a good clinical outcome and 4 patients with absent or pathological MEP had an unfavourable outcome (p < 0.05, Fisher's exact test). In all patients without PWI>DWI mismatch, MEP findings predicted clinical outcome. Normal MEP at day 0--but not PWI/DWI findings--significantly correlated with a good clinical outcome. CONCLUSIONS:Early MEP recordings in acute stroke patients provide valid prognostic information; they may become more useful for specific treatment decisions than presently available MRI surrogate parameters.
10.1159/000079265
Diffusion tensor imaging in hemorrhagic stroke.
Chaudhary Neeraj,Pandey Aditya S,Gemmete Joseph J,Hua Ya,Huang Yining,Gu Yuxiang,Xi Guohua
Experimental neurology
Diffusion tensor imaging (DTI) has evolved considerably over the last decade to now be knocking on the doors of wider clinical applications. There have been several efforts over the last decade to seek valuable and reliable application of DTI in different neurological disorders. The role of DTI in predicting outcomes in patients with brain tumors has been extensively studied and has become a fairly established clinical tool in this scenario. More recently DTI has been applied in mild traumatic brain injury to predict clinical outcomes based on DTI of the white matter tracts. The resolution of white matter fiber tractography based on DTI has improved over the years with increased magnet strength and better tractography post-processing. The role of DTI in hemorrhagic stroke has been studied preliminarily in the scientific literature. There is some evidence that DTI may be efficacious in predicting outcomes of motor function in animal models of intracranial hemorrhage. Only a handful of studies of DTI have been performed in subarachnoid hemorrhage or intraventricular hemorrhage scenarios. In this manuscript we will review the evolution of DTI, the existing evidence for its role in hemorrhagic stroke and discuss possible application of this non-invasive evaluation technique of human cerebral white matter tracts in the future.
10.1016/j.expneurol.2015.05.011
Identifying Resting-State Functional Connectivity Changes in the Motor Cortex Using fNIRS During Recovery from Stroke.
Arun K M,Smitha K A,Sylaja P N,Kesavadas Chandrasekharan
Brain topography
Resting-state functional imaging has been used to study the functional reorganization of the brain. The application of functional near-infrared spectroscopy (fNIRS) to assess resting-state functional connectivity (rsFC) has already been demonstrated in recent years. The present study aimed to identify the difference in rsFC patterns during the recovery from the upper-limb deficit due to stroke. Twenty patients with mild stroke having an onset of four to eight weeks were recruited from the stroke clinic of our institute and an equal number of healthy volunteers were included in the study after ethical committee approval. The fNIRS signals were recorded bilaterally over the premotor area and supplementary motor area and over the primary motor cortex. Pearson Correlation is the method used to compute rsFC for the healthy group and patient group. For the healthy group, both intra-hemispheric and inter-hemispheric connections were stronger. RSFC analysis demonstrated changes from the healthy pattern for the patient group with an upper-limb deficit. The left hemisphere affected group showed disrupted ipsilesional and an increased contra-lesional connectivity. The longitudinal data analysis of rsFC showed improvement in the connections in the ipsilesional hemisphere between the primary motor area, somatosensory area, and premotor areas. In the future, the rsFC changes during the recovery could be used to predict the extent of recovery from stroke motor deficits.
10.1007/s10548-020-00785-2
Three-dimensional anisotropy contrast magnetic resonance axonography to predict the prognosis for motor function in patients suffering from stroke.
Watanabe T,Honda Y,Fujii Y,Koyama M,Matsuzawa H,Tanaka R
Journal of neurosurgery
OBJECT:The purpose of this study was to assess how early wallerian degeneration in the corticospinal tracts of patients who had suffered from stroke was detected using three-dimensional anisotropy contrast (3D-AC) magnetic resonance (MR) axonography and to explore the possibility of predicting the prognosis for motor function in these patients. METHODS:Ten healthy volunteers and 16 stroke patients with hemiparesis were studied using MR images including 3D-AC MR axonography images obtained using a 1.5-tesla MR imaging system. The axonography was performed using an echoplanar imaging method. All patients underwent MR studies 2, 3, and 10 weeks after stroke onset. To detect wallerian degeneration, the diffusion anisotropy in the corticospinal tracts at the level of the upper pons was evaluated on axial images. These MR findings were compared with the patients' motor functions, which were classified according to the Brunnstrom criteria 12 weeks after the onset of stroke. In all patients with poor recovery (Brunnstrom Stages I-IV), wallerian degeneration, which was demonstrated as a reduction in diffusion anisotropy on axonography images, could be observed in the corticospinal tracts; this degeneration was not found in patients with good recovery (Stages V and VI). Axonography could be used to detect degeneration between 2 and 3 weeks after stroke onset. On conventional T2-weighted MR images, hyperintense areas indicating wallerian degeneration were not detected until 10 weeks after stroke onset. CONCLUSIONS:With the aid of 3D-AC MR axonography, wallerian degeneration can be detected in the corticospinal tracts during the early stage of stroke (2-3 weeks after onset), much earlier than it can be detected using T2-weighted MR imaging. The procedure of 3D-AC MR axonography may be useful in predicting motor function prognosis in stroke patients.
10.3171/jns.2001.94.6.0955
Recovery-related indicators of motor network plasticity according to impairment severity after stroke.
Lee J,Park E,Lee A,Chang W H,Kim D-S,Kim Y-H
European journal of neurology
BACKGROUND AND PURPOSE:Brain connectivity analysis has been widely used to investigate brain plasticity and recovery-related indicators of patients with stroke. However, results remain controversial because of interindividual variability of initial impairment and subsequent recovery of function. In this study, we aimed to investigate the differences in network plasticity and motor recovery-related indicators according to initial severity. METHODS:We divided participants (16 males and 14 females, aged 54.2 ± 12.0 years) into groups of different severity by Fugl-Mayer Assessment score, i.e. moderate (50-84), severe (20-49) and extremely severe (<20) impairment groups. Longitudinal resting-state functional magnetic resonance imaging data were acquired at 2 weeks and 3 months after onset. The differences in network plasticity and recovery-related indicators between groups were investigated using network distance and graph measurements. RESULTS:As the level of impairment increased, the network balance was more disrupted. Network balance, interhemispheric connectivity and network efficiency were recovered at 3 months only in the moderate impairment group. However, this was not the case in the extremely severe impairment group. A single connection strength between the ipsilesional primary motor cortex and ventral premotor cortex was implicated in the recovery of motor function for the extremely severe impairment group. The connections of the ipsilesional primary motor cortex-ventral premotor cortex were positively associated with motor recovery as the patients were more severely impaired. CONCLUSIONS:Differences in plasticity and recovery-related indicators of motor networks were noted according to impairment severity. Our results may suggest meaningful implications for recovery prediction and treatment strategies in future stroke research.
10.1111/ene.13377
Early Fiber Number Ratio Is a Surrogate of Corticospinal Tract Integrity and Predicts Motor Recovery After Stroke.
Bigourdan Antoine,Munsch Fanny,Coupé Pierrick,Guttmann Charles R G,Sagnier Sharmila,Renou Pauline,Debruxelles Sabrina,Poli Mathilde,Dousset Vincent,Sibon Igor,Tourdias Thomas
Stroke
BACKGROUND AND PURPOSE:The contribution of imaging metrics to predict poststroke motor recovery needs to be clarified. We tested the added value of early diffusion tensor imaging (DTI) of the corticospinal tract toward predicting long-term motor recovery. METHODS:One hundred seventeen patients were prospectively assessed at 24 to 72 hours and 1 year after ischemic stroke with diffusion tensor imaging and motor scores (Fugl-Meyer). The initial fiber number ratio (iFNr) and final fiber number ratio were computed as the number of streamlines along the affected corticospinal tract normalized to the unaffected side and were compared with each other. The prediction of motor recovery (ΔFugl-Meyer) was first modeled using initial Fugl-Meyer and iFNr. Multivariate ordinal logistic regression models were also used to study the association of iFNr, initial Fugl-Meyer, age, and stroke volume with Fugl-Meyer at 1 year. RESULTS:The iFNr correlated with the final fiber number ratio at 1 year (r=0.70; P<0.0001). The initial Fugl-Meyer strongly predicted motor recovery (≈73% of initial impairment) for all patients except those with initial severe stroke (Fugl-Meyer<50). For these severe patients (n=26), initial Fugl-Meyer was not correlated with motor recovery (R(2)=0.13; p=ns), whereas iFNr showed strong correlation (R(2)=0.56; P<0.0001). In multivariate analysis, the iFNr was an independent predictor of motor outcome (β=2.601; 95% confidence interval=0.304-5.110; P=0.031), improving prediction compared with using only initial Fugl-Meyer, age, and stroke volume (P=0.026). CONCLUSIONS:Early measurement of FNr at 24 to 72 hours poststroke is a surrogate marker of corticospinal tract integrity and provides independent prediction of motor outcome at 1 year especially for patients with severe initial impairment.
10.1161/STROKEAHA.115.011576
Investigating the structure-function relationship of the corticomotor system early after stroke using machine learning.
Chong Benjamin,Wang Alan,Borges Victor,Byblow Winston D,Alan Barber P,Stinear Cathy
NeuroImage. Clinical
BACKGROUND:Motor outcomes after stroke can be predicted using structural and functional biomarkers of the descending corticomotor pathway, typically measured using magnetic resonance imaging and transcranial magnetic stimulation, respectively. However, the precise structural determinants of intact corticomotor function are unknown. Identifying structure-function links in the corticomotor pathway could provide valuable insight into the mechanisms of post-stroke motor impairment. This study used supervised machine learning to classify upper limb motor evoked potential status using MRI metrics obtained early after stroke. METHODS:Retrospective data from 91 patients (49 women, age 35-97 years) with moderate to severe upper limb weakness within a week after stroke were included in this study. Support vector machine classifiers were trained using metrics from T1- and diffusion-weighted MRI to classify motor evoked potential status, empirically measured using transcranial magnetic stimulation. RESULTS:Support vector machine classification of motor evoked potential status was 81% accurate, with false positives more common than false negatives. Important structural MRI metrics included diffusion anisotropy asymmetry in the supplementary and pre-supplementary motor tracts, maximum cross-sectional lesion overlap in the sensorimotor tract and ventral premotor tract, and mean diffusivity asymmetry in the posterior limbs of the internal capsule. INTERPRETATIONS:MRI measures of corticomotor structure are good but imperfect predictors of corticomotor function. Residual corticomotor function after stroke depends on both the extent of cross-sectional macrostructural tract damage and preservation of white-matter microstructural integrity. Analysing the corticomotor pathway using a multivariable MRI approach across multiple tracts may yield more information than univariate biomarker analyses.
10.1016/j.nicl.2021.102935
Acute damage to the posterior limb of the internal capsule on diffusion tensor tractography as an early imaging predictor of motor outcome after stroke.
Puig J,Pedraza S,Blasco G,Daunis-I-Estadella J,Prados F,Remollo S,Prats-Galino A,Soria G,Boada I,Castellanos M,Serena J
AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE:Early prediction of motor outcome is of interest in stroke management. We aimed to determine whether lesion location at DTT is predictive of motor outcome after acute stroke and whether this information improves the predictive accuracy of the clinical scores. MATERIALS AND METHODS:We evaluated 60 consecutive patients within 12 hours of middle cerebral artery stroke onset. We used DTT to evaluate CST involvement in the motor cortex and premotor cortex, centrum semiovale, corona radiata, and PLIC and in combinations of these regions at admission, at day 3, and at day 30. Severity of limb weakness was assessed by using the motor subindex scores of the National Institutes of Health Stroke Scale (5a, 5b, 6a, 6b). We calculated volumes of infarct and fractional anisotropy values in the CST of the pons. RESULTS:Acute damage to the PLIC was the best predictor associated with poor motor outcome, axonal damage, and clinical severity at admission (P < .001). There was no significant correlation between acute infarct volume and motor outcome at day 90 (P = .176, r = 0.485). The sensitivity, specificity, and positive and negative predictive values of acute CST involvement at the level of the PLIC for motor outcome at day 90 were 73.7%, 100%, 100%, and 89.1%, respectively. In the acute stage, DTT predicted motor outcome at day 90 better than the clinical scores (R(2) = 75.50, F = 80.09, P < .001). CONCLUSIONS:In the acute setting, DTT is promising for stroke mapping to predict motor outcome. Acute CST damage at the level of the PLIC is a significant predictor of unfavorable motor outcome.
10.3174/ajnr.A2400
The microstructural status of the corpus callosum is associated with the degree of motor function and neurological deficit in stroke patients.
Li Yongxin,Wu Ping,Liang Fanrong,Huang Wenhua
PloS one
Human neuroimaging studies and animal models have suggested that white matter damage from ischemic stroke leads to the functional and structural reorganization of perilesional and remote brain regions. However, the quantitative relationship between the transcallosal tract integrity and clinical motor performance score after stroke remains unexplored. The current study employed a tract-based spatial statistics (TBSS) analysis on diffusion tensor imaging (DTI) to investigate the relationship between white matter diffusivity changes and the clinical scores in stroke patients. Probabilistic fiber tracking was also used to identify structural connectivity patterns in the patients. Thirteen ischemic stroke patients and fifteen healthy control subjects participated in this study. TBSS analyses showed that the corpus callosum (CC) and bilateral corticospinal tracts (CST) in the stroke patients exhibited significantly decreased fractional anisotropy and increased axial and radial diffusivity compared with those of the controls. Correlation analyses revealed that the motor and neurological deficit scores in the stroke patients were associated with the value of diffusivity indices in the CC. Compared with the healthy control group, probabilistic fiber tracking analyses revealed that significant changes in the inter-hemispheric fiber connections between the left and right motor cortex in the stroke patients were primarily located in the genu and body of the CC, left anterior thalamic radiation and inferior fronto-occipital fasciculus, bilateral CST, anterior/superior corona radiate, cingulum and superior longitudinal fasciculus, strongly suggesting that ischemic induces inter-hemispheric network disturbances and disrupts the white matter fibers connecting motor regions. In conclusion, the results of the present study show that DTI-derived measures in the CC can be used to predict the severity of motor skill and neurological deficit in stroke patients. Changes in structural connectivity pattern tracking between the left and right motor areas, particularly in the body of the CC, might reflect functional reorganization and behavioral deficit.
10.1371/journal.pone.0122615
Ischemic involvement of the primary motor cortex is a prognostic factor in acute stroke.
Kaya Dilaver,Dincer Alp,Arman Fehim,Bakirci Nadi,Erzen Canan,Pamir M Necmettin
International journal of stroke : official journal of the International Stroke Society
BACKGROUND:The location of the primary motor cortex can be detected in healthy adults using the findings of 'T2 hypointensity' and the 'double layer sign' on 3 T diffusion-weighted imaging. The aim of this study was to assess whether ischemic involvement of the primary motor cortex can be identified on 3 T diffusion-weighted imaging within six-hours after stroke onset and to evaluate whether this finding could predict clinical outcome three-months after ischemic stroke. METHODS:Sixty-five patients who had paralysis and ischemia of the anterior circulation underwent 3 T magnetic resonance imaging within six-hours of symptom onset. Follow-up MRI was obtained at 72 h. Anatomic localization and ischemic involvement of the primary motor cortex were evaluated on diffusion-weighted imaging by two investigators. Ischemic involvement on the primary motor cortex was classified into three grades. Ischemic lesion volumes were measured. We compared the favorable outcomes at three-months between subjects with and without ischemic involvement on the primary motor cortex using the NIHSS and modified Rankin Scale. RESULTS:Ischemic involvement on the primary motor cortex was identified in 52% of patients. Interrater agreement coefficients were 0·93 for the identification of ischemic involvement of primary motor cortex. As defined by scores on the modified Rankin Scale, among the patients with ischemic involvement of the primary motor cortex were worse than the patients without ischemic involvement of the primary motor cortex (P = 0·01). The mean ischemic lesion volume at baseline diffusion-weighted imaging was 38·7 ± 41·7 cm(3) and was 89·8 ± 93·6 cm(3) at follow-up T2-WI. Ischemic involvement on the primary motor cortex (odds ratio: 14·7) was a determinant for worse outcome. CONCLUSIONS:3T diffusion-weighted imaging can identify ischemic involvement on the primary motor cortex and may provide useful information for predicting outcome during the hyperacute stage. Ischemic involvement on the primary motor cortex has a significant negative impact on recovery.
10.1111/j.1747-4949.2011.00640.x
Brain oscillatory activity as a biomarker of motor recovery in chronic stroke.
Ray Andreas M,Figueiredo Thiago D C,López-Larraz Eduardo,Birbaumer Niels,Ramos-Murguialday Ander
Human brain mapping
In the present work, we investigated the relationship of oscillatory sensorimotor brain activity to motor recovery. The neurophysiological data of 30 chronic stroke patients with severe upper-limb paralysis are the basis of the observational study presented here. These patients underwent an intervention including movement training based on combined brain-machine interfaces and physiotherapy of several weeks recorded in a double-blinded randomized clinical trial. We analyzed the alpha oscillations over the motor cortex of 22 of these patients employing multilevel linear predictive modeling. We identified a significant correlation between the evolution of the alpha desynchronization during rehabilitative intervention and clinical improvement. Moreover, we observed that the initial alpha desynchronization conditions its modulation during intervention: Patients showing a strong alpha desynchronization at the beginning of the training improved if they increased their alpha desynchronization. Patients showing a small alpha desynchronization at initial training stages improved if they decreased it further on both hemispheres. In all patients, a progressive shift of desynchronization toward the ipsilesional hemisphere correlates significantly with clinical improvement regardless of lesion location. The results indicate that initial alpha desynchronization might be key for stratification of patients undergoing BMI interventions and that its interhemispheric balance plays an important role in motor recovery.
10.1002/hbm.24876
Degeneration of corpus callosum and recovery of motor function after stroke: a multimodal magnetic resonance imaging study.
Wang Ling E,Tittgemeyer Marc,Imperati Davide,Diekhoff Svenja,Ameli Mitra,Fink Gereon R,Grefkes Christian
Human brain mapping
Animal models of stroke demonstrated that white matter ischemia may cause both axonal damage and myelin degradation distant from the core lesion, thereby impacting on behavior and functional outcome after stroke. We here used parameters derived from diffusion magnetic resonance imaging (MRI) to investigate the effect of focal white matter ischemia on functional reorganization within the motor system. Patients (n = 18) suffering from hand motor deficits in the subacute or chronic stage after subcortical stroke and healthy controls (n = 12) were scanned with both diffusion MRI and functional MRI while performing a motor task with the left or right hand. A laterality index was employed on activated voxels to assess functional reorganization across hemispheres. Regression analyses revealed that diffusion MRI parameters of both the ipsilesional corticospinal tract (CST) and corpus callosum (CC) predicted increased activation of the unaffected hemisphere during movements of the stroke-affected hand. Changes in diffusion MRI parameters possibly reflecting axonal damage and/or destruction of myelin sheath correlated with a stronger bilateral recruitment of motor areas and poorer motor performance. Probabilistic fiber tracking analyses revealed that the region in the CC correlating with the fMRI laterality index and motor deficits connected to sensorimotor cortex, supplementary motor area, ventral premotor cortex, superior parietal lobule, and temporoparietal junction. The results suggest that degeneration of transcallosal fibers connecting higher order sensorimotor regions constitute a relevant factor influencing cortical reorganization and motor outcome after subcortical stroke.
10.1002/hbm.21417
Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke.
Proceedings of the National Academy of Sciences of the United States of America
Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain-behavior relationships in stroke.
10.1073/pnas.1521083113
Acute Diffusivity Biomarkers for Prediction of Motor and Language Outcome in Mild-to-Severe Stroke Patients.
Moulton Eric,Magno Serena,Valabregue Romain,Amor-Sahli Melika,Pires Christine,Lehéricy Stéphane,Leger Anne,Samson Yves,Rosso Charlotte
Stroke
Background and Purpose- Early severity of stroke symptoms-especially in mild-to-severe stroke patients-are imperfect predictors of long-term motor and aphasia outcome. Motor function and language processing heavily rely on the preservation of important white matter fasciculi in the brain. Axial diffusivity (AD) from the diffusion tensor imaging model has repeatedly shown to accurately reflect acute axonal damage and is thus optimal to probe the integrity of important white matter bundles and their relationship with long-term outcome. Our aim was to investigate the independent prognostic value of the AD of white matter tracts in the motor and language network evaluated at 24 hours poststroke for motor and aphasia outcome at 3 months poststroke. Methods- Seventeen (motor cohort) and 28 (aphasia cohort) thrombolyzed patients with initial mild-to-severe stroke underwent a diffusion tensor imaging sequence at 24 hours poststroke. Motor and language outcome were evaluated at 3 months poststroke with a composite motor score and the aphasia handicap scale. We first used stepwise regression to determine which classic (age, initial motor or aphasia severity, and lesion volume) and imaging (ratio of affected/unaffected AD of motor and language fasciculi) factors were related to outcome. Second, to determine the specificity of our a priori choices of fasciculi, we performed voxel-based analyses to determine if the same, additional, or altogether new regions were associated with long-term outcome. Results- The ratio of AD in the corticospinal tract was the sole predictor of long-term motor outcome, and the ratio of AD in the arcuate fasciculus-along with age and initial aphasia severity-was an independent predictor of 3-month aphasia outcome. White matter regions overlapping with these fasciculi naturally emerged in the corresponding voxel-based analyses. Conclusions- AD of the corticospinal tract and arcuate fasciculus are effective biomarkers of long-term motor and aphasia outcome, respectively.
10.1161/STROKEAHA.119.024946
Tractometry-Based Estimation of Corticospinal Tract Injury to Assess Initial Impairment and Predict Functional Outcomes in Ischemic Stroke Patients.
Journal of magnetic resonance imaging : JMRI
BACKGROUND:Corticospinal tract (CST) injury has been shown to exert a major influence on functional recovery after ischemic stroke. PURPOSE:To evaluate the prognostic value of CST injury estimated using a recent developed tractometry-based method. STUDY TYPE:Prospective. POPULATION:Forty-eight patients with CST damage induced by stroke lesion who underwent brain magnetic resonance imaging within 7 days from onset. SEQUENCE:Diffusion-weighted imaging (b = 1000 seconds/mm ) and diffusion kurtosis imaging (DKI) spin-echo echo-planar sequence with three b-values (0, 1250, and 2500 seconds/mm ) at 3.0 T. ASSESSMENT:A recently developed approach that combines tract segmentation and orientation mapping was used for CST-specific tractography and tractometry. CST injury was estimated using the proposed method with diffusion metrics extracted from DKI sequence and with the first principal component (PC1) of the metrics. We also calculated the weighted lesion load (wLL) for comparison. Clinical evaluation included the National Institutes of Health Stroke Score in the acute phase and the modified Rankin scale at 3 months post-stroke. The correlations between CST injury and initial motor impairment, as well as the prognostic values of CST injury for functional outcomes were evaluated. STATISTICAL TESTS:Pearson correlation and logistic regression. Area under the receiver operating characteristic curve. P < 0.05 was considered statistically significant. RESULTS:CST injury calculated with diffusion metrics except fractional anisotropy all showed significant correlations with initial motor impairment. PC1 achieved the largest correlation coefficient (R = 0.65) compared with wLL and other diffusion metrics. In addition to wLL, DKI_AK, AFD_total, and PC1 maximum all showed predictive values for functional outcomes. DATA CONCLUSION:Structural injury to CST is important for the assessment of the extent of injury and the prediction of functional outcome. The method proposed in our study could provide an imaging indicator to quantify the CST injury after ischemic stroke. LEVEL OF EVIDENCE:2 TECHNICAL EFFICACY: Stage 1.
10.1002/jmri.27911
Does Measurement of Corticospinal Tract Involvement Add Value to Clinical Behavioral Biomarkers in Predicting Motor Recovery after Stroke?
Neural plasticity
Background:The prediction of motor recovery after stroke is an important issue, and various prediction models have been proposed using either clinical behavioral or neurological biomarkers. This study sought to identify the effects of clinical behavioral biomarkers combined with corticospinal tract (CST) injury measurement on the prediction of motor recovery after stroke. Methods:The region of interest was drawn on the normalized brain magnetic resonance imaging scans of patients with first-ever unilateral hemispheric stroke, and the degree of CST injury was calculated in a total of 67 such subjects. Patients who had initial minor deficits and showed a ceiling effect on motor recovery were excluded. To predict the follow-up Fugl-Meyer assessment (FMA) scores, correlation and regression analyses were performed using various clinical behavioral biomarkers, including age, sex, lesion location, and initial FMA scores and CST injury measurements. Results:Only the initial FMA-upper extremity (UE) score was statistically correlated with the follow-up FMA-UE score at ≥2 months after the onset (adjusted = 0.626), and the relationship between CST injury and follow-up FMA-UE score was unclear ( = 53). Hierarchical clustering between the initial and follow-up FMA-UE scores showed three clusters. After exclusion of a cluster with an initial FMA-UE ≥ 35, the prediction of the follow-up FMA-UE score was possible by incorporating the initial FMA-UE score and CST injury measurements ( = 39). However, the explanatory power decreased (adjusted = 0.445), and the unique contribution of the CST injury (10.1%) was lower than that of the initial FMA-UE score (26.7%). With respect to the FMA-lower extremity score, CST injury was not related to recovery. Conclusions:Motor recovery of the upper and lower extremities after stroke could be predicted using the initial FMA score. CST injury was significant for the prediction of motor recovery of the upper extremity in patients with severe initial motor deficits (FMA-UE < 35); however, its portion of prediction of motor recovery was low. The prediction of poststroke motor recovery using the initial motor deficit was not improved by the addition of CST injury measurements.
10.1155/2020/8883839
White matter tract disruption is associated with ipsilateral hand impairment in subacute stroke: a diffusion MRI study.
Neuroradiology
PURPOSE:The ipsilateral hand (ILH) is impaired after unilateral stroke, but the underlying mechanisms remain unresolved. Based on the degeneracy theory of network connectivity that many connectivity patterns are functionally equivalent, we hypothesized that ILH impairment would result from the summation of microstructural white matter (WM) disruption in the motor network, with a task-related profile. We aimed to determine the WM disruption patterns associated with ILH impairment. METHODS:This was a cross-sectional analysis of patients in the ISIS-HERMES Study with ILH and diffusion-MRI data collected 1 month post-stroke. Patients performed three tasks, the Purdue Pegboard Test (PPT), handgrip strength, and movement time. Fractional anisotropy (FA) derived from diffusion MRI was measured in 33 WM regions. We used linear regression models controlling for age, sex, and education to determine WM regions associated with ILH impairment. RESULTS:PPT was impaired in 42%, grip in 59%, and movement time in 24% of 29 included patients (mean age, 51.9 ± 10.5 years; 21 men). PPT was predicted by ipsilesional corticospinal tract (i-CST) (B = 17.95; p = 0.002) and superior longitudinal Fasciculus (i-SLF) (B = 20.52; p = 0.008); handgrip by i-CST (B = 109.58; p = 0.016) and contralesional anterior corona radiata (B = 42.69; p = 0.039); and movement time by the corpus callosum (B = - 1810.03; p = 0.003) i-SLF (B = - 917.45; p = 0.015), contralesional pons-CST (B = 1744.31; p = 0.016), and i-corticoreticulospinal pathway (B = - 380.54; p = 0.037). CONCLUSION:ILH impairment was associated with WM disruption to a combination of ipsilateral and contralesional tracts with a pattern influenced by task-related processes, supporting the degeneracy theory. We propose to integrate ILH assessment in rehabilitation programs and treatment interventions such as neuromodulation.
10.1007/s00234-022-02927-8
Cortical thickness and metabolite concentration in chronic stroke and the relationship with motor function.
Jones Paul W,Borich Michael R,Vavsour Irene,Mackay Alex,Boyd Lara A
Restorative neurology and neuroscience
BACKGROUND:Hemiparesis is one of the most prevalent chronic disabilities after stroke. Biochemical and structural magnetic resonance imaging approaches may be employed to study the neural substrates underpinning upper-extremity (UE) recovery after chronic stroke. OBJECTIVE:The purposes of this study were to 1) quantify anatomical and metabolic differences in the precentral gyrus, and 2) test the relationships between anatomical and metabolic differences, and hemiparetic arm function in individuals in the chronic stage of stroke recovery. Our hypotheses were: 1) the Stroke group would exhibit reduced precentral gyrus cortical thickness and lower concentrations of total N-acetylaspartate (tNAA) and glutamate+glutamine (Glx) in the ipsilesional motor cortex; and 2) that each of these measures would be associated with UE motor function after stroke. METHODS:Seventeen individuals with chronic (>6 months) subcortical ischemic stroke and eleven neurologically healthy controls were recruited. Single voxel proton magnetic resonance spectroscopy (H1MRS) was performed to measure metabolite concentrations of tNAA and Glx in the precentral gyrus in both ipsilesional and contralesional hemispheres. Surface-based cortical morphometry was used to quantify precentral gyral thickness. Upper-extremity motor function was assessed using the Wolf Motor Function Test (WMFT). RESULTS:Results demonstrated significantly lower ipsilesional tNAA and Glx concentrations and precentral gyrus thickness in the Stroke group. Ipsilesional tNAA and Glx concentration and precentral gyrus thickness was significantly lower in the ipsilesional hemisphere in the Stroke group. Parametric correlation analyses revealed a significant positive relationship between precentral gyrus thickness and tNAA concentration bilaterally. Multivariate regression analyses revealed that ipsilesional concentrations of tNAA and Glx predicted the largest amount of variance in WMFT scores. Cortical thickness measures alone did not predict a significant amount of variance in WMFT scores. CONCLUSION:While stroke impairs both structure and biochemistry in the ipsilesional hemisphere our data suggest that tNAA has the strongest relationship with motor function.
10.3233/RNN-150623
Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI.
Kato Hiroyuki,Izumiyama Masahiro,Koizumi Hideaki,Takahashi Akira,Itoyama Yasuto
Stroke
BACKGROUND AND PURPOSE:Motor functional recovery from stroke can occur, but the mechanisms underlying this restorative process remain to be elucidated. We used near-infrared spectroscopic (NIRS) topography in comparison with functional MRI (fMRI) to evaluate the compensatory motor activation of cortical regions in patients who recovered from hemiparesis after cortical cerebral infarction. METHODS:We examined 6 right-handed patients who suffered cerebral infarction of the middle cerebral artery territory with minimal or mild residual contralateral hemiparesis (4 men and 2 women, 59 to 79 years old, all had left hemiparesis). Both fMRI and NIRS were studied during a hand movement task at chronic stages. Five right-handed, normal subjects (3 men and 2 women, 44 to 81 years old) served as controls. RESULTS:fMRI and NIRS detected very similar cerebral cortical activation, although NIRS detected only superficial activation. The spatial resolution of NIRS was less than that of fMRI, but NIRS provided a dynamic profile of activation. Normal subjects activated predominantly the contralateral primary sensorimotor cortex and supplementary motor areas during each hand movement. All the stroke patients exhibited the normal activation pattern during normal hand movement. On affected hand movement, the stroke patients showed extended activation not only in the contralateral motor cortex but also in the ipsilateral motor cortex (primary motor cortex and supplementary motor areas). CONCLUSIONS:Both fMRI and NIRS studies provided evidence for the contribution of ipsilateral motor cortical compensation or reorganization to the recovery from poststroke hemiparesis. The result demonstrated that NIRS was a unique tool to monitor poststroke alterations in cortical motor functions.
Lesion load of the corticospinal tract predicts motor impairment in chronic stroke.
Zhu Lin L,Lindenberg Robert,Alexander Michael P,Schlaug Gottfried
Stroke
BACKGROUND AND PURPOSE:Previous studies have shown motor impairment after a stroke relates to lesion size and location, but unexplained variability in recovery still exists. In this study, we used lesion-mapping techniques in combination with diffusion tensor imaging to quantitatively test the hypothesis that motor recovery in patients with chronic stroke is inversely related to the proportion of the corticospinal tract (CST) affected by the lesion. METHODS:We studied 50 patients with chronic stroke, all of whom presented with moderate to severe motor impairments in the acute stage, using high-resolution anatomic MRI. We evaluated the degree of motor impairment with the Upper Extremity module of the Fugl-Meyer Assessment. To analyze the relationship between CST damage and impairment scores, we calculated a CST-lesion load for each patient by overlaying the patient's lesion map with a probabilistic tract derived from diffusion tensor images of age-matched healthy subjects. RESULTS:CST-lesion load was a significant predictor of motor deficit. Infarct size, despite correlating with motor scores, did not significantly predict impairment. CONCLUSIONS:Our results show the degree of functional motor deficit after a stroke is highly dependent on the overlap of the lesion with the CST and not lesion size per se. In the future, automated calculation of CST-lesion load may allow more precise prediction of motor impairment after stroke.
10.1161/STROKEAHA.109.577023
Decreased corticospinal tract fractional anisotropy predicts long-term motor outcome after stroke.
Puig Josep,Blasco Gerard,Daunis-I-Estadella Josep,Thomalla Götz,Castellanos Mar,Figueras Jaume,Remollo Sebastián,van Eendenburg Cecile,Sánchez-González Javier,Serena Joaquín,Pedraza Salvador
Stroke
BACKGROUND AND PURPOSE:Nearly 50% of patients have residual motor deficits after stroke, and long-term motor outcome is difficult to predict. We assessed the predictive value of axonal damage to the corticospinal tract indexed by diffusion tensor imaging fractional anisotropy for long-term motor outcome. METHODS:Consecutive patients with middle cerebral artery stroke underwent multimodal MRI, including diffusion tensor imaging ≤12 hours, 3 days, and 30 days after onset. Clinical severity, infarct volume, location of corticospinal tract damage on diffusion tensor tractography, and ratios of fractional anisotropy (rFA) between affected and unaffected sides of the corticospinal tract at the pons were evaluated. Severity of motor deficit at 2 years was categorized using the Motricity Index as no deficit (Motricity Index, 100), slight-moderate deficit (Motricity Index, 99-50), or severe deficit (Motricity Index, <50). RESULTS:We evaluated 70 patients (28 women; 72±12 years). rFA values at day 30 correlated with the degree of motor deficit at 2 years (P<0.001). rFA at day 30 was the only independent predictor of long-term motor outcome (odds ratio, 1.60; 95% confidence interval, 1.26-2.03; P<0.001). The sensitivity, specificity, and positive and negative predictive values of the cutoffs rFA<0.982 for predicting slight-moderate deficit and rFA<0.689 for severe deficit were 94.4%, 84.6%, 73.9%, and 97.1%, respectively, and 100%, 83.3%, 81.3%, and 100%, respectively. CONCLUSIONS:rFA at day 30 is an independent predictor of long-term motor outcome after stroke.
10.1161/STROKEAHA.111.000382
The new insights into human brain imaging after stroke.
Journal of neuroscience research
Over the last two decades, developments of human brain stroke imaging have raised several questions about the place of new MRI biomarkers in the acute management of stroke and the prediction of poststroke outcome. Recent studies have demonstrated the main role of perfusion-weighted imaging in the identification of the best cerebral perfusion profile for a better response after reperfusion therapies in acute ischemic stroke. A major issue remains the early prediction of stroke outcome. While voxel-based lesion-symptom mapping emphasized the influence of stroke location, the analysis of the brain parenchyma underpinning the stroke lesion showed the relevance of prestroke cerebral status, including cortical atrophy, white matter integrity, or presence of chronic cortical cerebral microinfarcts. Moreover, besides the evaluation of the visually abnormal brain tissue, the analysis of normal-appearing brain parenchyma using diffusion tensor imaging and magnetization transfer imaging or spectroscopy offered new biomarkers to improve the prediction of the prognosis and new targets to follow in therapeutic trials. The aim of this review was to depict the main new radiological biomarkers reported in the last two decades that will provide a more thorough prediction of functional, motor, and neuropsychological outcome following the stroke. These new developments in neuroimaging might be a cornerstone in the emerging personalized medicine for stroke patients.
10.1002/jnr.24525
Structural and functional connectivity of motor circuits after perinatal stroke: A machine learning study.
NeuroImage. Clinical
Developmental neuroplasticity allows young brains to adapt via experiences early in life and also to compensate after injury. Why certain individuals are more adaptable remains underexplored. Perinatal stroke is an ideal human model of neuroplasticity with focal lesions acquired near birth in a healthy brain. Machine learning can identify complex patterns in multi-dimensional datasets. We used machine learning to identify structural and functional connectivity biomarkers most predictive of motor function. Forty-nine children with perinatal stroke and 27 controls were studied. Functional connectivity was quantified by fluctuations in blood oxygen-level dependent (BOLD) signal between regions. White matter tractography of corticospinal tracts quantified structural connectivity. Motor function was assessed using validated bimanual and unimanual tests. RELIEFF feature selection and random forest regression models identified predictors of each motor outcome using neuroimaging and demographic features. Unilateral motor outcomes were predicted with highest accuracy (8/54 features r = 0.58, 11/54 features, r = 0.34) but bimanual function required more features (51/54 features, r = 0.38). Connectivity of both hemispheres had important roles as did cortical and subcortical regions. Lesion size, age at scan, and type of stroke were predictive but not highly ranked. Machine learning regression models may represent a powerful tool in identifying neuroimaging biomarkers associated with clinical motor function in perinatal stroke and may inform personalized targets for neuromodulation.
10.1016/j.nicl.2020.102508
Contralesional motor cortex activation depends on ipsilesional corticospinal tract integrity in well-recovered subcortical stroke patients.
Lotze Martin,Beutling Willy,Loibl Moritz,Domin Martin,Platz Thomas,Schminke Ulf,Byblow Winston D
Neurorehabilitation and neural repair
BACKGROUND:The relationship between structural and functional integrity of descending motor pathways can predict the potential for motor recovery after stroke. The authors examine the relationship between brain imaging biomarkers within contralesional and ipsilesional hemispheres and hand function in well-recovered patients after subcortical stroke at the level of the internal capsule. OBJECTIVE: MEASURES:of functional activation and integrity of the ipsilesional corticospinal tract might predict paretic hand function. METHODS:A total of 14 patients in the chronic stable phase of motor recovery after subcortical stroke and 24 healthy age-matched individuals participated in the study. Functional MRI was used to examine BOLD contrast during passive wrist flexion-extension and paced or maximum-velocity active fist clenching. Functional integrity of the corticospinal pathway was assessed by transcranial magnetic stimulation to obtain motor-evoked potentials (MEPs) in the first dorsal interosseus muscle of the paretic and nonparetic hands. Fractional anisotropy and the proportion of traces between hemispheres in the posterior limb of both internal capsules were quantified using diffusion-weighted MRI. RESULTS:Patients with smaller MEPs had a weaker paretic hand and more primary motor cortex activation in their affected hemisphere. Asymmetry between white matter tracts of either hemisphere was associated with reduced precision grip strength and increased BOLD activation within the contralesional dorsal premotor cortex for demanding hand tasks. CONCLUSION:There may be beneficial reorganization in contralesional secondary motor areas with increasing damage to the corticospinal tract after subcortical stroke. Associations between clinical, functional, and structural integrity measures in chronic stroke may lead to a better understanding of motor recovery processes.
10.1177/1545968311427706
Leukoaraiosis Predicts Short-term Cognitive But not Motor Recovery in Ischemic Stroke Patients During Rehabilitation.
Khan Muhib,Heiser Heather,Bernicchi Nathan,Packard Laurel,Parker Jessica L,Edwardson Matthew A,Silver Brian,Elisevich Kost V,Henninger Nils
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND:Leukoaraiosis has been shown to impact functional outcomes after acute ischemic stroke. However, its association with domain specific recovery after ischemic stroke is uncertain. We sought to determine whether pre-existing leukoaraiosis is associated with short-term motor and cognitive recovery after stroke. METHODS:We retrospectively studied ischemic stroke patients admitted to acute inpatient rehabilitation (AIR) between January 2013 and September 2015. Patient baseline characteristics, infarct volume, prestroke modified Rankin Scale, stroke cause, rehabilitation length of stay, and Functional Independence Measure (FIM) scores were recorded. Leukoaraiosis severity was graded on brain magnetic resonance imaging using the Fazekas scale. Multiple linear regression was used to determine factors independently associated with the total, cognitive, and motor FIM scores at AIR discharge, respectively. RESULTS:Of 1600 ischemic stroke patients screened, 109 patients were included in the final analysis. After adjustment, the initial National Institute of Health Stroke Scale (β -0.541, confidence interval [CI] -0.993 to -0.888; P = 0.020) and pre-existing leukoaraiosis severity (β -1.448, CI -2.861 to -0.034; P = 0.045) independently predicted the total FIM score. Domain specific analysis showed that infarct volume (β -0.012, CI -0.019 to -0.005; P = 0.002) and leukoaraiosis severity (β -0.822, CI -1.223 to -0.410; P = 0.0001) independently predicted FIM cognitive scores at discharge from AIR. Leukoaraiosis did not predict FIM motor score (P = 0.17). CONCLUSIONS:Leukoaraiosis severity is an independent predictor of total and cognitive, but not motor FIM scores after AIR for acute ischemic stroke. This highlights that leukoaraiosis affects poststroke recovery in a domain specific fashion, information that may aid counseling of patients and families as well as tailor rehabilitative efforts.
10.1016/j.jstrokecerebrovasdis.2019.02.037
Neural function, injury, and stroke subtype predict treatment gains after stroke.
Annals of neurology
OBJECTIVE:This study was undertaken to better understand the high variability in response seen when treating human subjects with restorative therapies poststroke. Preclinical studies suggest that neural function, neural injury, and clinical status each influence treatment gains; therefore, the current study hypothesized that a multivariate approach incorporating these 3 measures would have the greatest predictive value. METHODS:Patients 3 to 6 months poststroke underwent a battery of assessments before receiving 3 weeks of standardized upper extremity robotic therapy. Candidate predictors included measures of brain injury (including to gray and white matter), neural function (cortical function and cortical connectivity), and clinical status (demographics/medical history, cognitive/mood, and impairment). RESULTS:Among all 29 patients, predictors of treatment gains identified measures of brain injury (smaller corticospinal tract [CST] injury), cortical function (greater ipsilesional motor cortex [M1] activation), and cortical connectivity (greater interhemispheric M1-M1 connectivity). Multivariate modeling found that best prediction was achieved using both CST injury and M1-M1 connectivity (r(2) = 0.44, p = 0.002), a result confirmed using Lasso regression. A threshold was defined whereby no subject with >63% CST injury achieved clinically significant gains. Results differed according to stroke subtype; gains in patients with lacunar stroke were best predicted by a measure of intrahemispheric connectivity. INTERPRETATION:Response to a restorative therapy after stroke is best predicted by a model that includes measures of both neural injury and function. Neuroimaging measures were the best predictors and may have an ascendant role in clinical decision making for poststroke rehabilitation, which remains largely reliant on behavioral assessments. Results differed across stroke subtypes, suggesting the utility of lesion-specific strategies.
10.1002/ana.24309
Relationship Between Motor Function, DTI, and Neurophysiological Parameters in Patients with Stroke in the Recovery Rehabilitation unit.
Okamoto Yoshitaka,Ishii Daisuke,Yamamoto Satoshi,Ishibashi Kiyoshige,Wakatabi Masahiro,Kohno Yutaka,Numata Kenji
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES:We investigated the relationship between pyramidal tract evaluation indexes (i.e., diffusion tensor imaging, transcranial magnetic stimulation (TMS)-induced motor-evoked potential (MEP), and central motor conduction time (CMCT) on admission to the recovery rehabilitation unit) and motor functions at discharge in patients with ischemic or hemorrhagic stroke. MATERIALS AND METHODS:Seventeen patients were recruited (12 men; 57.9 ± 10.3 years). The mean fractional anisotropy (FA) values of the right and left posterior limbs of the internal capsule were estimated using a computer-automated method. We determined the ratios of FA values in the affected and unaffected hemispheres (rFA), TMS-induced MEP, and the ratios of CMCT in the affected and unaffected hemispheres (rCMCT) and examined their association with motor functions (Fugl-Meyer Assessment (FMA) and Action Research Arm Test (ARAT)) at discharge. RESULTS:Higher rFA values of the posterior limb of the internal capsule on admission to the recovery rehabilitation unit led to a better recovery of upper limb function (FMA: r = 0.78, p < 0.001; ARAT: r = 0.74, p = 0.001). Patients without MEP had poorer recovery of upper limb function than those with MEP (FMA: p < 0.001; ARAT: p = 0.001). The higher the rCMCT, the poorer the recovery of upper limb function (ARAT: r = -0.93, p < 0.001). However, no association was observed between the pyramidal tract evaluation indexes and recovery of lower limb motor function. CONCLUSIONS:Evaluating the pyramidal tract is useful for predicting upper limb function prognosis, but not for lower limb function prognosis.
10.1016/j.jstrokecerebrovasdis.2021.105889
Ability of an altered functional coupling between resting-state networks to predict behavioral outcomes in subcortical ischemic stroke: A longitudinal study.
Frontiers in aging neuroscience
Stroke can be viewed as an acute disruption of an individual's connectome caused by a focal or widespread loss of blood flow. Although individuals exhibit connectivity changes in multiple functional networks after stroke, the neural mechanisms that underlie the longitudinal reorganization of the connectivity patterns are still unclear. The study aimed to determine whether brain network connectivity patterns after stroke can predict longitudinal behavioral outcomes. Nineteen patients with stroke with subcortical lesions underwent two sessions of resting-state functional magnetic resonance imaging scanning at a 1-month interval. By independent component analysis, the functional connectivity within and between multiple brain networks (including the default mode network, the dorsal attention network, the limbic network, the visual network, and the frontoparietal network) was disrupted after stroke and partial recovery at the second time point. Additionally, regression analyses revealed that the connectivity between the limbic and dorsal attention networks at the first time point showed sufficient reliability in predicting the clinical scores (Fugl-Meyer Assessment and Neurological Deficit Scores) at the second time point. The overall findings suggest that functional coupling between the dorsal attention and limbic networks after stroke can be regarded as a biomarker to predict longitudinal clinical outcomes in motor function and the degree of neurological functional deficit. Overall, the present study provided a novel opportunity to improve prognostic ability after subcortical strokes.
10.3389/fnagi.2022.933567
Functional lateralization in cingulate cortex predicts motor recovery after basal ganglia stroke.
Li Yao,Chen Zengai,Su Xin,Zhang Xiaoliu,Wang Ping,Zhu Yajing,Xu Qun,Xu Jianrong,Tong Shanbao
Neuroscience letters
The basal ganglia (BG) is involved in higher order motor control such as movement planning and execution of complex motor synergies. Neuroimaging study on stroke patients specifically with BG lesions would help to clarify the consequence of BG damage on motor control. In this paper, we performed a longitudinal study in the stroke patients with lesions in BG regions across three motor recovery stages, i.e., less than 2week (Session 1), 1-3m (Session 2) and more than 3m (Session 3). The patients showed an activation shift from bilateral hemispheres during early sessions (<3m) to the ipsilesional cortex in late session (>3m), suggesting a compensation effect from the contralesional hemisphere during motor recovery. We found that the lateralization of cerebellum(CB) for affected hand task correlated with patients' concurrent Fugl-Meyer index (FMI) in Session 2. Moreover, the cingulate cortex lateralization index in Session 2 was shown to significantly correlate with subsequent FMI change between Session 3 and Session 2, which serves as a prognostic marker for motor recovery. Our findings consolidated the close interactions between BG and CB during the motor recovery after stroke. The dominance of activation in contralateral cingulate cortex was associated with a better motor recovery, suggesting the important role of ipsilesional attention modulation in the early stage after BG stroke.
10.1016/j.neulet.2015.12.051
Predicting behavioural response to TDCS in chronic motor stroke.
O'Shea Jacinta,Boudrias Marie-Hélène,Stagg Charlotte Jane,Bachtiar Velicia,Kischka Udo,Blicher Jakob Udby,Johansen-Berg Heidi
NeuroImage
Transcranial direct current stimulation (TDCS) of primary motor cortex (M1) can transiently improve paretic hand function in chronic stroke. However, responses are variable so there is incentive to try to improve efficacy and or to predict response in individual patients. Both excitatory (Anodal) stimulation of ipsilesional M1 and inhibitory (Cathodal) stimulation of contralesional M1 can speed simple reaction time. Here we tested whether combining these two effects simultaneously, by using a bilateral M1-M1 electrode montage, would improve efficacy. We tested the physiological efficacy of Bilateral, Anodal or Cathodal TDCS in changing motor evoked potentials (MEPs) in the healthy brain and their behavioural efficacy in changing reaction times with the paretic hand in chronic stroke. In addition, we aimed to identify clinical or neurochemical predictors of patients' behavioural response to TDCS. There were three main findings: 1) unlike Anodal and Cathodal TDCS, Bilateral M1-M1 TDCS (1 mA, 20 min) had no significant effect on MEPs in the healthy brain or on reaction time with the paretic hand in chronic stroke patients; 2) GABA levels in ipsilesional M1 predicted patients' behavioural gains from Anodal TDCS; and 3) although patients were in the chronic phase, time since stroke (and its combination with Fugl-Meyer score) was a positive predictor of behavioural gain from Cathodal TDCS. These findings indicate the superiority of Anodal or Cathodal over Bilateral TDCS in changing motor cortico-spinal excitability in the healthy brain and in speeding reaction time in chronic stroke. The identified clinical and neurochemical markers of behavioural response should help to inform the optimization of TDCS delivery and to predict patient outcome variability in future TDCS intervention studies in chronic motor stroke.
10.1016/j.neuroimage.2013.05.096
Diffusion anisotrophy in the early stages of stroke can predict motor outcome.
Jang Sung Ho,Cho Sang-Hyun,Kim Yun-Hee,Han Bong Soo,Byun Woo Mok,Son Soo-Min,Kim Seong Ho,Lee Se Jin
Restorative neurology and neuroscience
PURPOSE:This study examined whether the degree of impairment of diffusion anisotrophy in the early stages of a stroke can predict the motor function outcome. METHODS:Thirty-one hemiplegic stroke patients were enrolled to this study. Diffusion anisotropy was measured by determining fractional anisotropy (FA) in the two ROIs (region of interests) at corona radiata (CR) and in the posterior limb of internal capsule (IC) during the early stages of stoke (average 7.9 days after stroke onset) and compared with motor outcome of the affected hand 3 months after stroke onset. RESULTS:Both ROIs (CR or IC) and lesion types (hemorrhage or infarction) did not have significant effect on the SBFA (symmetry of bilateral FA) and dMRC (medical research council score improvement), either. Patients with greater initial MRC score had significantly greater SBFA and dMRC. The regression equation between the dMRC (Y axis) and the SBFA (X axis) was semi-linear and significant (P < 0.05); for CR group, Y = 3.296 - 0.1192X + 0.0015X2; for IC group, Y = 2.342 - 0.0533X +0.0007(2). The regression lines had 'threshold points' where a minute SBFA change would make a steep increase in dMRC. CONCLUSION:The degree of impairment in diffusion anisotropy during the early stages of stroke appears to have the potential to predict motor outcome.
Motor cortex activation during treatment may predict therapeutic gains in paretic hand function after stroke.
Dong Yun,Dobkin Bruce H,Cen Steven Y,Wu Allan D,Winstein Carolee J
Stroke
BACKGROUND AND PURPOSE:Functional brain imaging after stroke offers insight into motor network adaptations. This exploratory study examined whether motor cortical activation captured during arm-focused therapy can predict paretic hand functional gains. METHODS:Eight hemiparetic patients had serial functional MRI (fMRI) while performing a pinch task before, midway, and after 2 weeks of constraint-induced therapy. The Wolf Motor Function Test (WMFT) was performed before and after intervention. RESULTS:There was a linear reduction in ipsilateral (contralesional) primary motor (M1) activation (voxel counts) across time. The midpoint M1 Laterality Index anticipated post-therapeutic change in time to perform the WMFT. The change in ipsilateral M1 voxel count (pre- to mid-) correlated with the change in mean WMFT time (pre- to post-). CONCLUSIONS:The relationship between brain activation during treatment and functional gains suggests a use for serial fMRI in predicting the success and optimal duration for a focused therapeutic intervention.
10.1161/01.STR.0000221281.69373.4e
Brain parenchymal fraction predicts motor improvement following intensive task-oriented motor rehabilitation for chronic stroke.
Rickards Tyler,Taub Edward,Sterling Chelsey,Graham Michael J,Barghi Ameen,Uswatte Gitendra,Mark Victor W
Restorative neurology and neuroscience
BACKGROUND AND PURPOSE:Infarct volume and location have a weak relationship with motor deficit in patients with chronic stroke. Recent research has focused on the relationship between spared or seemingly "healthy" neural tissue and motor function. In this study we examined MRI scans of patients with chronic stroke to determine if characteristics of seemingly normal parenchyma could predict either response to different forms of upper extremity physical rehabilitation or to pre-treatment motor status. METHODS:Individuals with chronic stroke (ages 60.6 ± 11.9 years) and mild/moderate upper extremity hemiparesis were administered either CI therapy (n = 14) or a comparison therapy (n = 29). The patients were assessed prior to and following therapy with MRI scans and the Wolf Motor Function Test (WMFT) Performance Time measure. Total voxels in combined grey matter (GM) and white matter (WM) segments (parenchymal volume) were divided by total voxels in GM, WM, and cerebrospinal fluid segments (intracranial volume) to obtain the brain parenchymal fraction (BPF). RESULTS:BPF correlated with treatment gains on the WMFT (r(43) = -0.31, p = 0.04). Significant correlations between pre-treatment motor function and BPF were not observed. CONCLUSIONS:Individuals with greater BPFs after stroke show larger arm function gains after CI therapy, suggesting that reductions in volume of normal-appearing tissue may relate to ability to benefit from rehabilitation therapy in chronic stroke.
10.3233/RNN-2012-110211
Hemispheric asymmetry in myelin after stroke is related to motor impairment and function.
Lakhani Bimal,Hayward Kathryn S,Boyd Lara A
NeuroImage. Clinical
The relationships between impairment, function, arm use and underlying brain structure following stroke remain unclear. Although diffusion weighted imaging is useful in broadly assessing white matter structure, it has limited utility in identifying specific underlying neurobiological components, such as myelin. The purpose of the present study was to explore relationships between myelination and impairment, function and activity in individuals with chronic stroke. Assessments of paretic upper-extremity impairment and function were administered, and 72-hour accelerometer based activity monitoring was conducted on 19 individuals with chronic stroke. Participants completed a magnetic resonance imaging protocol that included a high resolution T anatomical scan and a multi-component T relaxation imaging scan to quantify myelin water fraction (MWF). MWF was automatically parcellated from pre- and post-central subcortical regions of interest and quantified as an asymmetry ratio (contralesional/ipsilesional). Cluster analysis was used to group more and less impaired individuals based on Fugl-Meyer upper extremity scores. A significantly higher precentral MWF asymmetry ratio was found in the more impaired group compared to the less impaired group ( < 0.001). There were no relationships between MWF asymmetry ratio and upper-limb use. Stepwise multiple linear regression identified precentral MWF asymmetry as the only variable to significantly predict impairment and motor function in the upper extremity (UE). These results suggest that asymmetric myelination in a motor specific brain area is a significant predictor of upper-extremity impairment and function in individuals with chronic stroke. As such, myelination may be utilized as a more specific marker of the neurobiological changes that predict long term impairment and recovery from stroke.
10.1016/j.nicl.2017.01.009
Relationship between upper limb function and functional neural connectivity among motor related-areas during recovery stage after stroke.
Hoshino Takashi,Oguchi Kazuyo,Inoue Kenji,Hoshino Aiko,Hoshiyama Minoru
Topics in stroke rehabilitation
Neural biomarkers to predict motor recovery have been used in the field of rehabilitation. Functional connectivity (FC) among the brain regions recorded by functional magnetic resonance imaging systems have been reported, but convenient method to estimate FC for clinical situation has not been established.: This observational study investigated the relationship between neural functional connectivity obtained by electroencephalography (EEG) and the upper limb function in patients during recovery stage after stroke.: Twenty-four patients in the recovery stage between 4 and 8 weeks after the onset of stroke (mean age: 62 ± 12 (SD)) were enrolled. The EEG signals were obtained by five electrodes placed on the motor-related areas (C3, C4, FC3, FC4, and FCz in the International 10-20 system) for 60 sec at rest and during finger movement on the affected side, and amplitude envelope correlations as measures of FC among the areas were calculated. Fugl-Meyer Assessment (FMA) was used to assess upper limb motor function.: The FMA scores evaluated at 4W (33 ± 24 (SD)) were improved by 8W (42 ± 23) ( < .001). The FCs in α and β bands calculated between the electrodes in the ipsi-lesional hemisphere were correlated negatively with the FMA score at 4W after stroke. The FCs obtained at 4W could be used to predict the FMA score at 8W after stroke.: The FCs recorded at rest, as well as during the finger motor task, by the five electrodes placed on motor-related areas could be used to predict the motor function and recovery of the upper limb affected by stroke. The results indicate the possibility of using FCs recorded by conventional EEG with electrodes as biomarkers to predict motor recovery after stroke.
10.1080/10749357.2019.1658429
Corticospinal tract lesion load: An imaging biomarker for stroke motor outcomes.
Feng Wuwei,Wang Jasmine,Chhatbar Pratik Y,Doughty Christopher,Landsittel Douglas,Lioutas Vasileios-Arsenios,Kautz Steven A,Schlaug Gottfried
Annals of neurology
OBJECTIVE:The aim of this work was to investigate whether an imaging measure of corticospinal tract (CST) injury in the acute phase can predict motor outcome at 3 months in comparison to clinical assessment of initial motor impairment. METHODS:A two-site prospective cohort study followed up a group of first-ever ischemic stroke patients using the Upper-Extremity Fugl-Meyer (UE-FM) Scale to measure motor impairment in the acute phase and at 3 months. A weighted CST lesion load (wCST-LL) was calculated by overlaying the patient's lesion map on magnetic resonance imaging with a probabilistic CST constructed from healthy control subjects. Regression models were fit to assess the predictive value of wCST-LL and compared with initial motor impairment. RESULTS:Seventy-six patients (37 from cohort 1 and 39 from cohort 2) completed the study. wCST-LL as well as assessment of motor impairment (UE-FM) in the acute phase correlated with motor impairment (UE-FM) at 3 months in both cohort 1 (R(2) = 0.69 vs. R(2) = 0.67; p = 0.43) and cohort 2 (R(2) = 0.69 vs. R(2) = 0.62; p = 0.25). In the severely impaired subgroup (defined as UE-FM ≤ 10 at baseline), wCST-LL correlated with outcomes significantly better than clinical assessment (R(2) = 0.47 vs. R(2) = 0.11; p = 0.03). In the nonseverely impaired subgroup, stroke patients recovered approximately 70% of their maximal recovery potential. All stroke patients in both cohorts had poor motor outcomes at 3 months (defined as UE-FM ≤ 25) when wCST-LL was ≥ 7.0 cc (positive predictive value was 100%). INTERPRETATION:wCST-LL, an imaging biomarker determined in the acute phase, can predict poststroke motor outcomes at 3 months, especially in patients with severe impairment at baseline.
10.1002/ana.24510
Predicting functional motor potential in chronic stroke patients using diffusion tensor imaging.
Lindenberg Robert,Zhu Lin L,Rüber Theodor,Schlaug Gottfried
Human brain mapping
Electrophysiological and neuroimaging studies suggest that the integrity of ipsilesional and inter-hemispheric motor circuits is important for motor recovery after stroke. However, the extent to which each of these tracts contributes to the variance in outcome remains unclear. We examined whether diffusion tensor imaging (DTI)-derived measures of corticospinal and transcallosal tracts predict motor improvement in an experimental neurorehabilitation trial. 15 chronic stroke patients received bihemispheric transcranial direct current stimulation and simultaneous physical/occupational therapy for five consecutive days. Motor impairment was assessed prior to and after the intervention. At baseline, the patients underwent DTI; probabilistic fiber tracking was used to reconstruct the pyramidal tract (PT), alternate descending motor fibers (aMF), and transcallosal fibers connecting primary motor cortices (M1-M1). Ipsilesional corticospinal tracts (PT, aMF) and M1-M1 showed significantly decreased fractional anisotropy (FA) and increased directional diffusivities when compared to age-matched healthy controls. Partial correlations revealed that greater gains in motor function were related to higher FA values and lower directional diffusivities of transcallosal and ipsilesional corticospinal tracts. M1-M1 diffusivity had the greatest predictive value. An additional slice-by-slice analysis of FA values along the corticospinal tracts demonstrated that the more the ipsilesional FA profiles of patients resembled those of healthy controls, the greater their functional improvement. In conclusion, our study shows that DTI-derived measures can be used to predict functional potential for subsequent motor recovery in chronic stroke patients. Diffusivity parameters of individual tracts and tract combinations may help in assessing a patient's individual recovery potential and in determining optimal neurorehabilitative interventions.
10.1002/hbm.21266
Reorganization of Motor Execution Networks During Sub-Acute Phase After Stroke.
Cheng Lin,Wu Zhiyuan,Sun Junfeng,Fu Yi,Wang Xinning,Yang Guo-Yuan,Miao Fei,Tong Shanbao
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Numerous studies focused on brain reorganization after stroke from aspects of task-related brain activity and resting-state brain networks. However, studies focusing on the longitudinal reorganization of task-state brain networks were scarce. In this study, functional magnetic resonance imaging data were collected from twelve stroke patients during blocked finger-tapping task at four post-stroke time points (less than 10 days, around 2 weeks, 1 month and 3 months), respectively. The dynamic changes and prognostic value of the network parameters (i.e., topological parameters, functional connectivity and nodal parameters) in task-state motor execution networks were thoroughly evaluated. We found that the topological configuration (clustering coefficient and characteristic path length) of task-state motor execution networks underwent significant shift during stroke recovery. Especially, we found the topological configuration of task-state motor execution networks at the early recovery stage were capable of predicting the motor function restoration during sub-acute phase. In addition, we found increasing functional connectivity between ipsilesional cerebellum and motor cortices in task-state motor execution networks. In general, this study demonstrated the reorganization and prognostic value of task-state brain network after stroke, which provides new insights into understanding the brain reorganization and rehabilitation after stroke.
10.1109/TNSRE.2015.2401978
Combination of Serum Neurofilament Light Chain Levels and MRI Markers to Predict Cognitive Function in Ischemic Stroke.
Peng Yuan,Li Qianfeng,Qin Lei,He Yating,Luo Xun,Lan Yue,Chen Xin,Wang Xin,Wang Qing Mei
Neurorehabilitation and neural repair
BACKGROUND:It is important to predict poststroke cognitive outcome to guide individualized treatment and prevention strategy. We aimed to evaluate the predictive value of the combination of a serum biomarker for axonal damage (neurofilament light chain [NfL]) and neuroimaging markers (volume of infarction and white matter hyperintensities [WMH]) for neuronal abnormality in poststroke cognitive outcome. METHODS:A total of 1028 patients were screened; among them, 144 patients with acute ischemic stroke (stroke group) and 30 patients without stroke (control group) were enrolled. Serum NfL levels of samples obtained from both groups were measured through single molecule array assay. Neuroimaging markers of neuroaxonal injury, including infarct volume and WMH in the stroke group were quantified on magnetic resonance images using an in-house MATLAB code (MATLAB 2017; MathWorks). The primary outcome was the functional independence measure (FIM) cognitive subscores on discharge. We assessed the association of serum NfL levels and neuroimaging markers with cognitive outcome. The prognosis value of the combination of serum NfL levels and imaging markers for predicting FIM cognitive subscores on discharge was calculated using the area under curve (AUC) of the receiver operating characteristic. RESULTS:Serum NfL levels of the stroke group were 9-fold higher than those of the control group (1449.7 vs 157.2 pg/mL, n = 144/30, < .001). There was a correlation of serum NfL levels with infarct volume ( = 0.530, < .001) and functional outcome, including FIM cognitive subscores ( = -0.387, < .001) and FIM motor subscores on admission ( = -0.306, < .001), but not with WMH volume after adjusting for infarct volume ( = -0.196, = .245). Serum NfL levels on admission independently predicted poststroke FIM cognitive subscores on discharge (AUC = 0.672, < .001). The predictive value for poststroke cognitive outcome was improved by combining serum NfL levels with infarct and WMH volume (AUC = 0.760, < .001). CONCLUSION:The combination of serum NfL levels with volume of infarct and WMH shows an improved predictive value for cognitive function during acute rehabilitation phase after stroke, providing a promising panel of biomarkers for prognosis and guidance of treatment.
10.1177/1545968321989354
Stronger prediction of motor recovery and outcome post-stroke by cortico-spinal tract integrity than functional connectivity.
Lin Leanne Y,Ramsey Lenny,Metcalf Nicholas V,Rengachary Jennifer,Shulman Gordon L,Shimony Joshua S,Corbetta Maurizio
PloS one
OBJECTIVES:To examine longitudinal changes in structural and functional connectivity post-stroke in patients with motor impairment, and define their importance for recovery and outcome at 12 months. METHODS:First-time stroke patients (N = 31) were studied at 1-2 weeks, 3 months, and 12 months post-injury with a validated motor battery and resting-state fMRI to measure inter-hemispheric functional connectivity (FC). Fractional anisotropy (FA) of the cortico-spinal tract (CST) was derived from diffusion tensor imaging as a measure of white matter organization. ANOVAs were used to test for changes in FC, FA, and motor performance scores over time, and regression analysis related motor outcome to clinical and neuroimaging variables. RESULTS:FA of the ipsilesional CST improved significantly from 3 to 12 months and was strongly correlated with motor performance. FA improved even in the absence of direct damage to the CST. Inter-hemispheric FC also improved over time, but did not correlate with motor performance at 12 months. Clinical variables (early motor score, education level, and age) predicted 80.4% of the variation of motor outcome, and FA increased the predictability to 84.6%. FC did not contribute to the prediction of motor outcome. CONCLUSIONS:Stroke causes changes to the CST microstructure that can account for behavioral variability even in the absence of demonstrable lesion. Ipsilesional CST undergoes remodeling post-stroke, even past the three-month window when most of the motor recovery happens. FA of the CST, but not inter-hemispheric FC, can improve to the prediction of motor outcome based on early motor scores.
10.1371/journal.pone.0202504
Microstructural properties of premotor pathways predict visuomotor performance in chronic stroke.
Archer Derek B,Misra Gaurav,Patten Carolynn,Coombes Stephen A
Human brain mapping
Microstructural properties of the corticospinal tract (CST) descending from the motor cortex predict strength and motor skill in the chronic phase after stroke. Much less is known about the relation between brain microstructure and visuomotor processing after stroke. In this study, individual's poststroke and age-matched controls performed a unimanual force task separately with each hand at three levels of visual gain. We collected diffusion MRI data and used probabilistic tractography algorithms to identify the primary and premotor CSTs. Fractional anisotropy (FA) within each tract was used to predict changes in force variability across different levels of visual gain. Our observations revealed that individuals poststroke reduced force variability with an increase in visual gain, performed the force task with greater variability as compared with controls across all gain levels, and had lower FA in the primary motor and premotor CSTs. Our results also demonstrated that the CST descending from the premotor cortex, rather than the primary motor cortex, best predicted force variability. Together, these findings demonstrate that the microstructural properties of the premotor CST predict visual gain-related changes in force variability in individuals poststroke. Hum Brain Mapp 37:2039-2054, 2016. © 2016 Wiley Periodicals, Inc.
10.1002/hbm.23155
Performance Comparison of Different Neuroimaging Methods for Predicting Upper Limb Motor Outcomes in Patients after Stroke.
Neural plasticity
Several neuroimaging methods have been proposed to assess the integrity of the corticospinal tract (CST) for predicting recovery of motor function after stroke, including conventional structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI). In this study, we aimed to compare the predicative performance of these methods using different neuroimaging modalities and optimize the prediction protocol for upper limb motor function after stroke in a clinical environment. We assessed 28 first-ever stroke patients with upper limb motor impairment. We used the upper extremity module of the Fugl-Meyer assessment (UE-FM) within 1 month of onset (baseline) and again 3 months poststroke. sMRI (T1- and T2-based) was used to measure CST-weighted lesion load (CST-wLL), and DTI was used to measure the fractional anisotropy asymmetry index (FAAI) and the ratio of fractional anisotropy (rFA). The CST-wLL within 1 month poststroke was closely correlated with upper limb motor outcomes and recovery potential. CST-wLL ≥ 2.068 cc indicated serious CST damage and a poor outcome (100%). CST-wLL < 1.799 cc was correlated with a considerable rate (>70%) of upper limb motor function recovery. CST-wLL showed a comparable area under the curve (AUC) to that of the CST-FAAI ( = 0.71). Inclusion of extra-CST-FAAI did not significantly increase the AUC ( = 0.58). Our findings suggest that sMRI-derived CST-wLL is a precise predictor of upper limb motor outcomes 3 months poststroke. We recommend this parameter as a predictive imaging biomarker for classifying patients' recovery prognosis in clinical practice. Conversely, including DTI appeared to induce no significant benefits.
10.1155/2022/4203698
Individual prediction of chronic motor outcome in the acute post-stroke stage: Behavioral parameters versus functional imaging.
Rehme Anne K,Volz Lukas J,Feis Delia-Lisa,Eickhoff Simon B,Fink Gereon R,Grefkes Christian
Human brain mapping
Several neurobiological factors have been found to correlate with functional recovery after brain lesions. However, predicting the individual potential of recovery remains difficult. Here we used multivariate support vector machine (SVM) classification to explore the prognostic value of functional magnetic resonance imaging (fMRI) to predict individual motor outcome at 4-6 months post-stroke. To this end, 21 first-ever stroke patients with hand motor deficits participated in an fMRI hand motor task in the first few days post-stroke. Motor impairment was quantified assessing grip force and the Action Research Arm Test. Linear SVM classifiers were trained to predict good versus poor motor outcome of unseen new patients. We found that fMRI activity acquired in the first week post-stroke correctly predicted the outcome for 86% of all patients. In contrast, the concurrent assessment of motor function provided 76% accuracy with low sensitivity (<60%). Furthermore, the outcome of patients with initially moderate impairment and high outcome variability could not be predicted based on motor tests. In contrast, fMRI provided 87.5% prediction accuracy in these patients. Classifications were driven by activity in ipsilesional motor areas and contralesional cerebellum. The accuracy of subacute fMRI data (two weeks post-stroke), age, time post-stroke, lesion volume, and location were at 50%-chance-level. In conclusion, multivariate decoding of fMRI data with SVM early after stroke enables a robust prediction of motor recovery. The potential for recovery is influenced by the initial dysfunction of the active motor system, particularly in those patients whose outcome cannot be predicted by behavioral tests.
10.1002/hbm.22936
Association of Extrapyramidal Tracts' Integrity With Performance in Fine Motor Skills After Stroke.
Rimmele D Leander,Frey Benedikt M,Cheng Bastian,Schulz Robert,Krawinkel Lutz A,Bönstrup Marlene,Braass Hanna,Gerloff Christian,Thomalla Götz
Stroke
Background and Purpose- Tractography by diffusion tensor imaging has extended our knowledge on the contribution of damage to different pathways to residual motor function after stroke. Integrity of the corticospinal tract (CST), for example, has been identified to characterize and predict its course. Yet there is only scarce data that allow a judgment on the impact of extrapyramidal pathways between the basal ganglia on motor function poststroke. We aimed at studying their association with performance in fine motor skills after stroke. Methods- We performed probabilistic tractography and reconstructed nigro-pallidal tracts connecting substantia nigra and globus pallidus, as well as the CST in 26 healthy subjects. Resulting tracts were registered to the individual images of 20 patients 3 months after stroke, and their microstructural integrity was measured by fractional anisotropy. Clinical examination of the patients' gross (grip force) and fine (nine-hole peg test) motor skills was performed 1 year after stroke. For assessment of factors influencing nine-hole peg test, we used a multivariate model. Results- Nigro-pallidal tracts were traceable in all participants, had no overlap to the CST and passed the nucleus subthalamicus. In stroke patients, nigro-pallidal tracts ipsilateral to the stroke lesion showed a significantly reduced fractional anisotropy (ratio, 0.96±0.02; P=0.021). One year after stroke, nine-hole peg test values were significantly slower for the affected hand, while grip force was comparable between both hands. Reduced integrity of the nigro-pallidal tracts was associated with worse performance in the nine-hole peg test ( P=0.040), as was reduced integrity of the CST ( P<0.001) and younger age ( P<0.001). Conclusions- Nigro-pallidal tracts with containing connections of the nucleus subthalamicus represent a relevant part of the extrapyramidal system and specifically contribute to residual fine motor skills after stroke beyond the well-known contribution of the CST. They may deliver supportive information for prediction of motor recovery after stroke.
10.1161/STROKEAHA.118.022706
Corticospinal Tract Injury Estimated From Acute Stroke Imaging Predicts Upper Extremity Motor Recovery After Stroke.
Lin David J,Cloutier Alison M,Erler Kimberly S,Cassidy Jessica M,Snider Samuel B,Ranford Jessica,Parlman Kristin,Giatsidis Fabio,Burke James F,Schwamm Lee H,Finklestein Seth P,Hochberg Leigh R,Cramer Steven C
Stroke
Background and Purpose- Injury to the corticospinal tract (CST) has been shown to have a major effect on upper extremity motor recovery after stroke. This study aimed to examine how well CST injury, measured from neuroimaging acquired during the acute stroke workup, predicts upper extremity motor recovery. Methods- Patients with upper extremity weakness after ischemic stroke were assessed using the upper extremity Fugl-Meyer during the acute stroke hospitalization and again at 3-month follow-up. CST injury was quantified and compared, using 4 different methods, from images obtained as part of the stroke standard-of-care workup. Logistic and linear regression were performed using CST injury to predict ΔFugl-Meyer. Injury to primary motor and premotor cortices were included as potential modifiers of the effect of CST injury on recovery. Results- N=48 patients were enrolled 4.2±2.7 days poststroke and completed 3-month follow-up (median 90-day modified Rankin Scale score, 3; interquartile range, 1.5). CST injury distinguished patients who reached their recovery potential (as predicted from initial impairment) from those who did not, with area under the curve values ranging from 0.70 to 0.8. In addition, CST injury explained ≈20% of the variance in the magnitude of upper extremity recovery, even after controlling for the severity of initial impairment. Results were consistent when comparing 4 different methods of measuring CST injury. Extent of injury to primary motor and premotor cortices did not significantly influence the predictive value that CST injury had for recovery. Conclusions- Structural injury to the CST, as estimated from standard-of-care imaging available during the acute stroke hospitalization, is a robust way to distinguish patients who achieve their predicted recovery potential and explains a significant amount of the variance in poststroke upper extremity motor recovery.
10.1161/STROKEAHA.119.025898
Axial diffusivity changes in the motor pathway above stroke foci and functional recovery after subcortical infarction.
Liu Gang,Peng Kangqiang,Dang Chao,Tan Shuangquan,Chen Hongbing,Xie Chuanmiao,Xing Shihui,Zeng Jinsheng
Restorative neurology and neuroscience
BACKGROUND:Secondary degeneration of the fiber tract of the motor pathway below infarct foci and functional recovery after stroke have been well demonstrated, but the role of the fiber tract above stroke foci remains unclear. OBJECTIVE:This study aimed to investigate diffusion changes in motor fibers above the lesion and identify predictors of motor improvement within 12 weeks after subcortical infarction. METHODS:Diffusion tensor imaging and the Fugl-Meyer (FM) scale were conducted 1, 4, and 12 weeks (W) after a subcortical infarct. Proportional recovery model residuals were used to assign patients to proportional recovery and poor recovery groups. Region of interest analysis was used to assess diffusion changes in the motor pathway above and below a stroke lesion. Multivariable linear regression was employed to identify predictors of motor improvement within 12 weeks after stroke. RESULTS:Axial diffusivity (AD) in the underlying white matter of the ipsilesional primary motor area (PMA) and cerebral peduncle (CP) in both proportional and poor recovery groups was lower at W1 compared to the controls and values in the contralesional PMA and CP (all P < 0.05). Subsequently, AD in the ipsilesional CP became relatively stable, while AD in the ipsilesional PMA significantly increased from W4 to W12 after stroke (P < 0.05). In all of the patients, changes in the FM scores were greater in those with higher changes in AD of the ipsilesional PMA. Only initial impairment or lesion volume was predictive of motor improvement within 12 weeks after stroke in patients with proportional or poor recovery. CONCLUSION:Increases of AD in the motor pathway above stroke foci may be associated with motor recovery after subcortical infarction. Early measurement of diffusion metrics in the ipsilesional non-ischemic motor pathway has limited value in predicting future motor improvement patterns (proportional or poor recovery).
10.3233/RNN-170747
Connectivity-Related Roles of Contralesional Brain Regions for Motor Performance Early after Stroke.
Hensel Lukas,Tscherpel Caroline,Freytag Jana,Ritter Stella,Rehme Anne K,Volz Lukas J,Eickhoff Simon B,Fink Gereon R,Grefkes Christian
Cerebral cortex (New York, N.Y. : 1991)
Hemiparesis after stroke is associated with increased neural activity not only in the lesioned but also in the contralesional hemisphere. While most studies have focused on the role of contralesional primary motor cortex (M1) activity for motor performance, data on other areas within the unaffected hemisphere are scarce, especially early after stroke. We here combined functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) to elucidate the contribution of contralesional M1, dorsal premotor cortex (dPMC), and anterior intraparietal sulcus (aIPS) for the stroke-affected hand within the first 10 days after stroke. We used "online" TMS to interfere with neural activity at subject-specific fMRI coordinates while recording 3D movement kinematics. Interfering with aIPS activity improved tapping performance in patients, but not healthy controls, suggesting a maladaptive role of this region early poststroke. Analyzing effective connectivity parameters using a Lasso prediction model revealed that behavioral TMS effects were predicted by the coupling of the stimulated aIPS with dPMC and ipsilesional M1. In conclusion, we found a strong link between patterns of frontoparietal connectivity and TMS effects, indicating a detrimental influence of the contralesional aIPS on motor performance early after stroke.
10.1093/cercor/bhaa270
Prediction of the motor prognosis with diffusion tensor imaging in hemorrhagic stroke: a meta-analysis.
Chang Min Cheol,Kwak Sang Gyu,Park Donghwi
Journal of integrative neuroscience
This paper investigates whether diffusion tensor imaging performed within 2 weeks of intracerebral hemorrhage onset could predict the motor outcome by categorizing previous diffusion tensor imaging studies based on the time-point of performing diffusion tensor imaging (<2 weeks and ≥2 weeks after intracerebral hemorrhage onset). A comprehensive database search on PubMed, Embase, Cochrane Library, and SCOPUS was conducted. The pooled estimate was acquired using correlation analysis between the diffusion tensor imaging parameters of fractional anisotropy and motor recovery based on the period of stroke onset. In the results, out of 511 retrieved articles, eight were finally included in the meta-analysis. In patients who underwent diffusion tensor imaging within 2 weeks of intracerebral hemorrhage onset, a random-effects model revealed that the ratio of fractional anisotropy is a significant predictor of motor recovery of the hemi-side extremity after intracerebral hemorrhage (p = 0.0015). In patients who underwent diffusion tensor imaging after 2 weeks of intracerebral hemorrhage onset, a fixed-effects model revealed that the ratio of fractional anisotropy was also a significant predictor of motor recovery of the hemi-side extremity after intracerebral hemorrhage (p < 0.0001). Our meta-analysis revealed that ratio of fractional anisotropy (rFa) calculated from diffusion tensor imaging (DTI) performed ≥2 weeks of intracerebral hemorrhage onset had a positive correlation with the motor outcomes after intracerebral hemorrhage (ICH). Also, although diffusion tensor imaging was performed <2 weeks after intracerebral hemorrhage onset, the ratio of fractional anisotropy calculated from diffusion tensor imaging helped predict the motor outcome. Further analyses, including a more significant number of studies focused on this topic, are warranted.
10.31083/j.jin2004102
Interactions Between the Corticospinal Tract and Premotor-Motor Pathways for Residual Motor Output After Stroke.
Schulz Robert,Park Eunhee,Lee Jungsoo,Chang Won Hyuk,Lee Ahee,Kim Yun-Hee,Hummel Friedhelm C
Stroke
BACKGROUND AND PURPOSE:Brain imaging has continuously enhanced our understanding how different brain networks contribute to motor recovery after stroke. However, the present models are still incomplete and do not fit for every patient. The interaction between the degree of damage of the corticospinal tract (CST) and of corticocortical motor connections, that is, the influence of the microstructural state of one connection on the importance of another has been largely neglected. METHODS:Applying diffusion-weighted imaging and probabilistic tractography, we investigated cross-network interactions between the integrity of ipsilesional CST and ipsilesional corticocortical motor pathways for variance in residual motor outcome in 53 patients with subacute stroke. RESULTS:The main finding was a significant interaction between the CST and corticocortical connections between the primary motor and ventral premotor cortex in relation to residual motor output. More specifically, the data indicate that the microstructural state of the connection primary motor-ventral premotor cortex plays only a role in patients with significant damage to the CST. In patients with slightly affected CST, this connection did not explain a relevant amount of variance in motor outcome. CONCLUSIONS:The present data show that patients with stroke with different degree of CST disruption differ in their dependency on structural premotor-motor connections for residual motor output. This finding might have important implications for future research on recovery prediction models and on responses to treatment strategies.
10.1161/STROKEAHA.117.016834
Corticospinal Fibers With Different Origins Impact Motor Outcome and Brain After Subcortical Stroke.
Liu Jingchun,Wang Caihong,Qin Wen,Ding Hao,Guo Jun,Han Tong,Cheng Jingliang,Yu Chunshui
Stroke
BACKGROUND AND PURPOSE:Motor deficit is the most common disability after stroke, and early prediction of motor outcome is critical for early interventions. Here, we constructed a fine map of the corticospinal tract (CST) for early prediction of motor outcome and for understanding the secondary brain changes after subcortical stroke. METHODS:Diffusion spectrum imaging data from 50 healthy adults were used to reconstruct fine maps of CST with different origins, including primary motor area (M1), primary sensory area (S1), premotor cortex, and supplementary motor area (SMA). Their diffusion properties correlated with motor functions in healthy adults. The impacts of the impairments of different CST on motor outcomes and on structural and functional changes of brain were investigated in 136 patients with subcortical stroke by combining CST damage-symptom association study and voxel-based lesion-symptom mapping. RESULTS:In healthy adults, the isotropy of M1 fiber correlated with walking endurance and that of SMA fiber with motor dexterity. In chronic stroke patients, the integrity of M1 and SMA fibers showed the most significant correlation with motor deficits. The percentage of early damage of M1 and SMA fibers correlated with that of chronic motor deficits. Voxel-based lesion-symptom mapping revealed that acute stroke lesions in the bilateral M1 and right SMA fibers were associated with chronic motor deficits. The early damage of M1 fiber negatively correlated with the integrity of M1-M1 fiber, and the early damage of SMA fiber negatively correlated with gray matter volume of the contralateral cerebellum in the chronic stage. CONCLUSIONS:The CST that originated from the M1 and SMA are closely associated with motor outcomes and brain structural changes, and the fine maps of CST from these 2 cortical areas are useful in assessing and predicting long-term motor outcome in patients with subcortical stroke.
10.1161/STROKEAHA.120.029508
Diffusional Kurtosis Imaging and Motor Outcome in Acute Ischemic Stroke.
Spampinato M V,Chan C,Jensen J H,Helpern J A,Bonilha L,Kautz S A,Nietert P J,Feng W
AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE:Motor impairment is the most common deficit after stroke. Our aim was to evaluate whether diffusional kurtosis imaging can detect corticospinal tract microstructural changes in the acute phase for patients with first-ever ischemic stroke and motor impairment and to assess the correlations between diffusional kurtosis imaging-derived diffusion metrics for the corticospinal tract and motor impairment 3 months poststroke. MATERIALS AND METHODS:We evaluated 17 patients with stroke who underwent brain MR imaging including diffusional kurtosis imaging within 4 days after the onset of symptoms. Neurologic evaluation included the Fugl-Meyer Upper Extremity Motor scale in the acute phase and 3 months poststroke. For the corticospinal tract in the lesioned and contralateral hemispheres, we estimated with diffusional kurtosis imaging both pure diffusion metrics, such as the mean diffusivity and mean kurtosis, and model-dependent quantities, such as the axonal water fraction. We evaluated the correlations between corticospinal tract diffusion metrics and the Fugl-Meyer Upper Extremity Motor scale at 3 months. RESULTS:Among all the diffusion metrics, the largest percentage signal changes of the lesioned hemisphere corticospinal tract were observed with axial kurtosis, with an average 12% increase compared with the contralateral corticospinal tract. The strongest associations between the 3-month Fugl-Meyer Upper Extremity Motor scale score and diffusion metrics were found for the lesioned/contralateral hemisphere corticospinal tract mean kurtosis (ρ = -0.85) and axial kurtosis (ρ = -0.78) ratios. CONCLUSIONS:This study was designed to be one of hypothesis generation. Diffusion metrics related to kurtosis were found to be more sensitive than conventional diffusivity metrics to early poststroke corticospinal tract microstructural changes and may have potential value in the prediction of motor impairment at 3 months.
10.3174/ajnr.A5180
Multimodal Imaging Biomarker-Based Model Using Stratification Strategies for Predicting Upper Extremity Motor Recovery in Severe Stroke Patients.
Lee Jungsoo,Kim Heegoo,Kim Jinuk,Chang Won Hyuk,Kim Yun-Hee
Neurorehabilitation and neural repair
. Various prognostic biomarkers for upper extremity (UE) motor recovery after stroke have been reported. However, most have relatively low predictive accuracy in severe stroke patients.. This study suggests an imaging biomarker-based model for effectively predicting UE recovery in severe stroke patients.. Of 104 ischemic stroke patients screened, 42 with severe motor impairment were included. All patients underwent structural, diffusion, and functional magnetic resonance imaging at 2 weeks and underwent motor function assessments at 2 weeks and 3 months after stroke onset. According to motor function recovery at 3 months, patients were divided into good and poor subgroups. The value of multimodal imaging biomarkers of lesion load, lesion volume, white matter integrity, and cortical functional connectivity for motor recovery prediction was investigated in each subgroup.. Imaging biomarkers varied depending on recovery pattern. The integrity of the cerebellar tract ( .005, = .432) was the primary biomarker in the good recovery group. In contrast, the sensory-related corpus callosum tract ( .026, = .332) and sensory-related functional connectivity ( .001, = .531) were primary biomarkers in the poor recovery group. A prediction model was proposed by applying each biomarker in the subgroup to patients with different motor evoked potential responses ( .001, = .853, root mean square error = 5.28).. Our results suggest an optimized imaging biomarker model for predicting UE motor recovery after stroke. This model can contribute to individualized management of severe stroke in a clinical setting.
10.1177/15459683211070278
Structural integrity of corticospinal motor fibers predicts motor impairment in chronic stroke.
Lindenberg R,Renga V,Zhu L L,Betzler F,Alsop D,Schlaug G
Neurology
OBJECTIVE:Motor impairment after stroke has been related to infarct size, infarct location, and integrity of motor tracts. To determine the value of diffusion tensor imaging (DTI) as a predictor of motor outcome and its role as a structural surrogate marker of impairment in chronic stroke, we tested correlations between motor impairment and DTI-derived measures of motor tract integrity. METHODS:Thirty-five chronic stroke patients with varying degrees of recovery underwent DTI and motor impairment assessments. Fibers originating from the precentral gyrus were traced and separated into pyramidal tract (PT) and alternate motor fibers (aMF). Asymmetry indices of fiber number and regional fractional anisotropy (FA) values comparing lesional with nonlesional hemispheres were correlated with motor impairment scores and compared to an age-matched control group. RESULTS:Fiber number and regional FA value asymmetry significantly differed between the groups with lower values in the patients' lesional hemispheres. Both measures significantly predicted motor impairment with stronger predictions when all motor tracts were combined as compared to predictions using only the PT. The pattern of motor tract damage (PT only vs PT and aMF) led to a classification of mild, moderate, or severe impairment with significant between-group differences in motor impairment scores. CONCLUSIONS:Diffusion tensor imaging-derived measures are valid structural markers of motor impairment. The integrity of all descending motor tracts, not merely the pyramidal tract, appears to account for stroke recovery. A 3-tier, hierarchical classification of impairment categories based on the pattern of motor tract damage is proposed that might be helpful in predicting recovery potential.
10.1212/WNL.0b013e3181ccc6d9
Task-related brain functional network reconfigurations relate to motor recovery in chronic subcortical stroke.
Scientific reports
Stroke leads to both regional brain functional disruptions and network reorganization. However, how brain functional networks reconfigure as task demand increases in stroke patients and whether such reorganization at baseline would facilitate post-stroke motor recovery are largely unknown. To address this gap, brain functional connectivity (FC) were examined at rest and motor tasks in eighteen chronic subcortical stroke patients and eleven age-matched healthy controls. Stroke patients underwent a 2-week intervention using a motor imagery-assisted brain computer interface-based (MI-BCI) training with or without transcranial direct current stimulation (tDCS). Motor recovery was determined by calculating the changes of the upper extremity component of the Fugl-Meyer Assessment (FMA) score between pre- and post-intervention divided by the pre-intervention FMA score. The results suggested that as task demand increased (i.e., from resting to passive unaffected hand gripping and to active affected hand gripping), patients showed greater FC disruptions in cognitive networks including the default and dorsal attention networks. Compared to controls, patients had lower task-related spatial similarity in the somatomotor-subcortical, default-somatomotor, salience/ventral attention-subcortical and subcortical-subcortical connections, suggesting greater inefficiency in motor execution. Importantly, higher baseline network-specific FC strength (e.g., dorsal attention and somatomotor) and more efficient brain network reconfigurations (e.g., somatomotor and subcortical) from rest to active affected hand gripping at baseline were related to better future motor recovery. Our findings underscore the importance of studying functional network reorganization during task-free and task conditions for motor recovery prediction in stroke.
10.1038/s41598-021-87789-5
Modeling functional network topology following stroke through graph theory: functional reorganization and motor recovery prediction.
Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
The study of functional reorganization following stroke has been steadily growing supported by advances in neuroimaging techniques, such as functional magnetic resonance imaging (fMRI). Concomitantly, graph theory has been increasingly employed in neuroscience to model the brain's functional connectivity (FC) and to investigate it in a variety of contexts. The aims of this study were: 1) to investigate the reorganization of network topology in the ipsilesional (IL) and contralesional (CL) hemispheres of stroke patients with (motor stroke group) and without (control stroke group) motor impairment, and 2) to predict motor recovery through the relationship between local topological variations of the functional network and increased motor function. We modeled the brain's FC as a graph using fMRI data, and we characterized its interactions with the following graph metrics: degree, clustering coefficient, characteristic path length, and betweenness centrality (BC). For both patient groups, BC yielded the largest variations between the two analyzed time points, especially in the motor stroke group. This group presented significant correlations (P<0.05) between average BC changes and the improvements in upper-extremity Fugl-Meyer (UE-FM) scores at the primary sensorimotor cortex and the supplementary motor area for the CL hemisphere. These regions participate in processes related to the selection, planning, and execution of movement. Generally, higher increases in average BC over these areas were related to larger improvements in UE-FM assessment. Although the sample was small, these results suggest the possibility of using BC as an indication of brain plasticity mechanisms following stroke.
10.1590/1414-431X2022e12036
Corticospinal Tract Microstructure Predicts Distal Arm Motor Improvements in Chronic Stroke.
Journal of neurologic physical therapy : JNPT
BACKGROUND AND PURPOSE:The corticospinal tract (CST) is a crucial brain pathway for distal arm and hand motor control. We aimed to determine whether a diffusion tensor imaging (DTI)-derived CST metric predicts distal upper extremity (UE) motor improvements in chronic stroke survivors. METHODS:We analyzed clinical and neuroimaging data from a randomized controlled rehabilitation trial. Participants completed clinical assessments and neuroimaging at baseline and clinical assessments 4 months later, postintervention. Using univariate linear regression analysis, we determined the linear relationship between the DTI-derived CST fractional anisotropy asymmetry (FAasym) and the percentage of baseline change in log-transformed average Wolf Motor Function Test time for distal items (ΔlnWMFT-distal_%). The least absolute shrinkage and selection operator (LASSO) linear regressions with cross-validation and bootstrapping were used to determine the relative weighting of CST FAasym, other brain metrics, clinical outcomes, and demographics on distal motor improvement. Logistic regression analyses were performed to test whether the CST FAasym can predict clinically significant UE motor improvement. RESULTS:lnWMFT-distal significantly improved at the group level. Baseline CST FAasym explained 26% of the variance in ΔlnWMFT-distal_%. A multivariate LASSO model including baseline CST FAasym, age, and UE Fugl-Meyer explained 39% of the variance in ΔlnWMFT-distal_%. Further, CST FAasym explained more variance in ΔlnWMFT-distal_% than the other significant predictors in the LASSO model. DISCUSSION AND CONCLUSIONS:CST microstructure is a significant predictor of improvement in distal UE motor function in the context of an UE rehabilitation trial in chronic stroke survivors with mild-to-moderate motor impairment.Video Abstract available for more insight from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A350).
10.1097/NPT.0000000000000363
Prediction of Motor Recovery after Stroke by Assessment of Corticospinal Tract Wallerian Degeneration Using Diffusion Tensor Imaging.
Darwish Hoda Salah,ElShafey Rasha,Kamel Hanaa
The Indian journal of radiology & imaging
To predict motor recovery after stroke by detection of diffusion tensor imaging (DTI) fractional anisotropy (FA) changes of corticospinal tract (CST) and correlate findings with clinical scores to provide more effective treatment and rehabilitation. Thirty patients with cerebral stroke were enrolled and underwent conventional magnetic resonance imaging and DTI at admission and 1 month after stroke. Mean diffusivity (MD), FA, FA ratio (rFA), and fiber number (FN) values of CST were calculated at the pons at admission and after 1 month of stroke. Three-dimensional reconstruction of bilateral CST and the structural changes of fibrous bands were observed. Severity of limb weakness was assessed by using the motor sub-index scores of the National Institutes of Health Stroke Scale (NIHSS) at admission, and after 1, 6, and 9 months for severity of limb weakness. The mean age of our patients was 61.32 ± 4.34 years, 17/30 (56.6%) were females, and 13/30 (43.4%) were males. In our study, 18/30 (60%) were hypertensive, 19/30 (63.3%) were diabetic, and 12/30 (40%) were smokers. A significant negative correlation was found between rFA and FN in the ipsilateral CST of the cerebral infarction at the rostral part of pons after 1 month of infarction and NIHSS score at 6 months ( = 0.377, = 0.04 and = 0.237, = 0.02, respectively). However, a positive insignificant correlation was found between MD and NIHSS ( = 0.345, = 0.635). The initial NIHSS score at the time of injury was 19.2 ± 4.3, which changed to 7.9 ± 2.4, 4.6 ± 1.9, and 3.3 ± 1.4 at 1, 6, and 9 months, respectively. DTI is a sensitive tool for early detection of Wallerian degeneration in the CST after stroke, and can predict motor performance to provide effective treatment and rehabilitation to improve quality of life.
10.1055/s-0041-1729671
Relation of white matter hyperintensities and motor deficits in chronic stroke.
Hicks Jarrod M,Taub Edward,Womble Brent,Barghi Ameen,Rickards Tyler,Mark Victor W,Uswatte Gitendra
Restorative neurology and neuroscience
BACKGROUND:Infarct size and location account for only a relatively small portion of post-stroke motor impairment, suggesting that other less obvious factors may be involved. OBJECTIVE:Examine the relationship between white matter hyperintensity (WMH) load among other factors and upper extremity motor deficit in patients with mild to moderate chronic stroke. METHODS:The magnetic resonance images of 28 patients were studied. WMH load was assessed as total WMH volume and WMH overlap with the corticospinal tract in the centrum semiovale. Hemiparetic arm function was measured using the Motor Activity Log (MAL) and Wolf Motor Function Test (WMFT). RESULTS:Hierarchical multiple regression models found WMH volume predicted motor deficits in both real-world arm use (MAL;ΔR2 = 0.12, F(1, 22) = 4.73, p = 0.04) and in arm motor capacity as measured by a laboratory motor function test (WMFT;ΔR2 = 0.18, F(1, 22) = 6.32, p = 0.02) over and above age and lesion characteristics. However, these models accounted for less than half of the variance in post-stroke motor deficits. CONCLUSION:The results suggest that WMH may be an important factor to consider in stroke-related upper extremity motor impairment. Nonetheless, the basis of the largest part of the post-stroke motor deficit remains unaccounted for by structural CNS factors. This component may be behavioral or learned, involving learned nonuse.
10.3233/RNN-170746
Differential early predictive factors for upper and lower extremity motor recovery after ischaemic stroke.
Lee J,Kim H,Kim J,Lee H-J,Chang W H,Kim Y-H
European journal of neurology
BACKGROUND AND PURPOSE:Various clinical and neuroimaging predictive factors have been identified for the recovery of upper extremity (UE) motor function after stroke. However, few studies have addressed factors related to the recovery of lower extremity (LE) motor function after stroke or performed direct comparisons of UE and LE motor recovery in the same set of patients. In this study, predictive factors for UE and LE motor recovery after stroke were investigated using clinical and neuroimaging characteristics. METHODS:Forty-two subacute ischaemic stroke patients underwent structural and functional magnetic resonance imaging data acquisition and cognitive/behavioral assessments using the Fugl-Meyer assessment, the National Institutes of Health Stroke Scale (NIHSS) and the Mini-Mental State Examination (MMSE) 2 weeks after stroke onset. Neuroimaging factors, including corticospinal tract (CST) fractional anisotropy, lesion volume, CST lesion load and interhemispheric homotopic functional connectivity, were extracted. The outcome of motor function was assessed by Fugl-Meyer assessment scores 3 months after onset. RESULTS:Early clinical and neuroimaging factors for predicting motor recovery were noticeably different for UE and LE. UE motor function recovery was related to age, NIHSS, MMSE, CST lesion load, lesion volume, ipsilesional CST integrity and interhemispheric homotopic functional connectivity. In contrast, LE motor recovery was related to ipsilesional and contralesional CST integrity and MMSE. Specifically, LE recovery showed a strong relationship to the preservation of cognitive function compared with motor impairment. CONCLUSIONS:Our results indicate that different mechanisms underlie UE and LE motor recovery after stroke. LE motor recovery seems to be more intensively modulated by cognitive functions than UE.
10.1111/ene.14494
Decoding post-stroke motor function from structural brain imaging.
NeuroImage. Clinical
Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine learning in structural imaging to investigate diseases that involve brain injury presents an additional challenge, especially in conditions like stroke, due to the high variability across patients regarding characteristics of the lesions. Extracting data from anatomical images in a way that translates brain damage information into features to be used as input to learning algorithms is still an open question. One of the most common approaches to capture regional information from brain injury is to obtain the lesion load per region (i.e. the proportion of voxels in anatomical structures that are considered to be damaged). However, no systematic evaluation has yet been performed to compare this approach with using patterns of voxels (i.e. considering each voxel as a single feature). In this paper we compared both approaches applying Gaussian Process Regression to decode motor scores in 50 chronic stroke patients based solely on data derived from structural MRI. For both approaches we compared different ways to delimit anatomical areas: regions of interest from an anatomical atlas, the corticospinal tract, a mask obtained from fMRI analysis with a motor task in healthy controls and regions selected using lesion-symptom mapping. Our analysis showed that extracting features through patterns of voxels that represent lesion probability produced better results than quantifying the lesion load per region. In particular, from the different ways to delimit anatomical areas compared, the best performance was obtained with a combination of a range of cortical and subcortical motor areas as well as the corticospinal tract. These results will inform the appropriate methodology for predicting long term motor outcomes from early post-stroke structural brain imaging.
10.1016/j.nicl.2016.07.014
Clinical Imaging-Derived Metrics of Corticospinal Tract Structural Integrity Are Associated With Post-stroke Motor Outcomes: A Retrospective Study.
Frontiers in neurology
OBJECTIVE:The primary objective of this study was to retrospectively investigate associations between clinical magnetic resonance imaging-based (MRI) metrics of corticospinal tract (CST) status and paretic upper extremity (PUE) motor recovery in patients that completed acute inpatient rehabilitation (AR) post-stroke. METHODS:We conducted a longitudinal chart review of patients post-stroke who received care in the Emory University Hospital system during acute hospitalization, AR, and outpatient therapy. We extracted demographic information, stroke characteristics, and longitudinal documentation of post-stroke motor function from institutional electronic medical records. Serial assessments of paretic shoulder abduction and finger extension were estimated (E-SAFE) and an estimated Action Research Arm Test (E-ARAT) score was used to quantify 3-month PUE motor function outcome. Clinically-diagnostic MRI were used to create lesion masks that were spatially normalized and overlaid onto a white matter tract atlas delineating CST contributions emanating from six cortical seed regions to obtain the percentage of CST lesion overlap. Metric associations were investigated with correlation and cluster analyses, Kruskal-Wallis tests, classification and regression tree analysis. RESULTS:Thirty-four patients met study eligibility criteria. All CST overlap percentages were correlated with E-ARAT however, ventral premotor tract (PMv) overlap was the only tract that remained significantly correlated after multiple comparisons adjustment. Lesion overlap percentage in CST contributions from all seed regions was significantly different between outcome categories. Using MRI metrics alone, dorsal premotor (PMd) and PMv tracts classified recovery outcome category with 79.4% accuracy. When clinical and MRI metrics were combined, AR E-SAFE, patient age, and overall CST lesion overlap classified patients with 88.2% accuracy. CONCLUSIONS:Study findings revealed clinical MRI-derived CST lesion overlap was associated with PUE motor outcome post-stroke and that cortical projections within the CST, particularly those emanating from non-M1 cortical areas, prominently ventral premotor (PMv) and dorsal premotor (PMd) cortices, distinguished between PUE outcome groups. Exploratory predictive models using clinical MRI metrics, either alone or in combination with clinical measures, were able to accurately identify recovery outcome category for the study cohort during both the acute and early subacute phases of post-stroke recovery. Prospective studies are recommended to determine the predictive utility of including clinical imaging-based biomarkers of white matter tract structural integrity in predictive models of post-stroke recovery.
10.3389/fneur.2022.804133
Early ADC changes in motor structures predict outcome of acute stroke better than lesion volume.
Rosso C,Colliot O,Pires C,Delmaire C,Valabrègue R,Crozier S,Dormont D,Baillet S,Samson Y,Lehéricy S
Journal of neuroradiology. Journal de neuroradiologie
OBJECTIVES:The lesion volume assessed from diffusion-weighted imaging (DWI) within the first six hours to first week following stroke onset has been proposed as a predictor of functional outcome in clinical studies. However, the prediction accuracy decreases when the DWI lesion volume is measured during the earliest stages of patient evaluation. In this study, our hypothesis was that the combination of lesion location (motor-related regions) and diffusivity measures (such as Apparent Diffusion Coefficient [ADC]) at the acute stage of stroke predict clinical outcome. PATIENTS AND METHODS:Seventy-nine consecutive acute carotid territory stroke patients (median age: 62 years) were included in the study and outcome at three months was assessed using the modified Rankin scale (good outcome: mRS 0-2; poor outcome: mRS 3-5). DWI was acquired within the first six hours of stroke onset (H2) and the following day (D1). Apparent Diffusion Coefficient (ADC) values were measured in the corticospinal tract (CST), the primary motor cortex (M1), the supplementary motor area (SMA), the putamen in the affected hemisphere, and in the contralateral cerebellum to predict stroke outcome. RESULTS:Prediction of poor vs. good outcome at the individual level at H2 (D1, respectively) was achieved with 74% accuracy, 95%CI: 53-89% (75%, 95% CI: 61-89%, respectively) when patients were classified from ADC values measured in the putamen and CST. Prediction accuracy from DWI volumes reached only 62% (95%CI: 42-79%) at H2 and 69% (95%CI: 50-85%) at D1. CONCLUSION:We therefore show that measures of ADC at the acute stage in deeper motor structures (putamen and CST) are better predictors of stroke outcome than DWI lesion volume.
10.1016/j.neurad.2010.05.001
Proportional Recovery From Lower Limb Motor Impairment After Stroke.
Smith Marie-Claire,Byblow Winston D,Barber P Alan,Stinear Cathy M
Stroke
BACKGROUND AND PURPOSE:In people with preserved corticospinal tract (CST) function after stroke, upper limb impairment resolves by ≈70% within 3 months. This is known as the proportional recovery rule. Patients without CST function do not fit this rule and have worse upper limb outcomes. This study investigated resolution of motor impairment in the lower limb (LL). METHODS:Patients with stroke and LL weakness were assessed 3 days and 3 months after stroke with the LL Fugl-Meyer. CST integrity was determined in a subset of patients using transcranial magnetic stimulation to test for LL motor-evoked potentials and magnetic resonance imaging to measure CST lesion load. Linear regression analyses were conducted to predict resolution of motor impairment (ΔFugl-Meyer) including factors initial impairment, motor-evoked potential status, CST lesion load, and LL therapy dose. RESULTS:Thirty-two patients completed 3-month follow-up and recovered 74% (95% confidence interval, 60%-88%) of initial LL motor impairment. Initial impairment was the only significant predictor of resolution of motor impairment. There was no identifiable cluster of patients who did not fit the proportional recovery rule. Measures of CST integrity did not predict proportional LL recovery. CONCLUSIONS:LL impairment resolves by ≈70% within 3 months after stroke. The absence of a nonfitter group may be because of differences in the neuroanatomical organization of descending motor tracts to the upper limb and LL. Proportional recovery of the LL is not influenced by therapy dose providing further evidence that it reflects a fundamental biological process.
10.1161/STROKEAHA.116.016478
Anatomy and physiology predict response to motor cortex stimulation after stroke.
Nouri Sarvenaz,Cramer Steven C
Neurology
OBJECTIVES:Preclinical studies found that epidural motor cortex stimulation improved motor deficits after stroke, but a phase III trial in humans did not corroborate these results. The current retrospective analysis examined subjects randomized to stimulation in order to identify features distinguishing responders from nonresponders. METHODS:Anatomic (MRI measures of gray matter thickness and of white matter tract injury) and physiologic methods (motor evoked responses) were examined as predictors of treatment response. RESULTS:Among 60 subjects randomized to cortical stimulation, both anatomic and physiologic measures at baseline predicted behavioral response to therapy. Anatomically, those achieving the primary efficacy endpoint had a smaller fraction of the corticospinal tract injured by stroke compared to those who did not (44% vs 72%, p < 0.04), and rarely had severe tract injury. Physiologically, the primary efficacy endpoint was reached more often (67%) by those with preserved motor evoked responses (MER) upon cortical stimulation compared to those lacking MER (27%, p < 0.05). Those with an elicitable MER also had a lower rate of precentral gyrus injury (0% vs 33%, p < 0.05) by stroke, as compared to those lacking MER, and had higher gray matter volume compared to those lacking MER in regions including ipsilesional precentral gyrus. CONCLUSIONS:In this clinical stroke trial, the more that the physiologic integrity of the motor system was preserved, the more likely that a patient was to derive gains from subsequent therapy, consistent with preclinical models. Functional and structural preservation of key brain substrates are important to deriving gain from a restorative therapy.
10.1212/WNL.0b013e31822e1482
MRI can Predict the Response to Therapeutic Repetitive Transcranial Magnetic Stimulation (rTMS) in Stroke Patients.
Emara Tamer,El Nahas Nevine,Elkader Hanaa Abd,Ashour Samia,El Etrebi Anwar
Journal of vascular and interventional neurology
BACKGROUND:Previous studies suggest that purposeful modulation of excitability by up regulation in primary motor area (M1) in the lesioned hemisphere or down regulation of excitability in M1 intact hemisphere can influence function in the paretic hand.. OBJECTIVES:1- To determine if magnetic resonance imaging (MRI) delineation of lesion has an impact on the modality and site of rTMS stimulation, and 2- To determine whether MRI can predict the degree of recovery of motor function after rTMS treatment. METHODS:A total of 60 ischemic stroke patients were recruited. Physical examination, mini mental state examination, activities of daily living assessment, motor subscale of the activity index (AI) and fine hand movement assessment were performed initially and then 2 weeks later (after the end of therapeutic course), then at 4, 8, and 12 weeks. MRI was performed for all patients and used to localize the site and extent of lesion. The patients were divided to 3 group consisting of 20 patients each: group 1 received repetitive rTMS 5hz at 90% motor threshold for 2.5min on the infarcted hemisphere, group 2 received rTMS 1hz at 110% motor threshold for 2.5min on the intact hemisphere, and group 3 received sham stimulation. All patients received standard physical therapy following each rTMS session. RESULTS:Patients with total anterior circulation stroke demonstrated on MRI showed no significant improvement when compared to those with partial anterior circulation, lacunar or posterior circulation strokes. The patients with cortical strokes experienced less improvement when compared with those with subcortical strokes especially with 1 hz stimulation to intact hemisphere. CONCLUSION:MRI can help predict the response to rTMS for stroke rehabilitation and assist the clinician choose the mode and site of rTMS application.
Multimodal magnetic resonance imaging correlates of motor outcome after stroke using machine learning.
Yang Hea Eun,Kyeong Sunghyon,Kang Hyunkoo,Kim Dae Hyun
Neuroscience letters
This study applied machine learning regression to predict motor function after stroke based on multimodal magnetic resonance imaging. Fifty-four stroke patients, who underwent T1 weighted, diffusion tensor, and resting state functional magnetic resonance imaging were retrospectively included. The kernel rigid regression machine algorithm was applied to gray and white matter maps in T1 weighted, fractional anisotropy and mean diffusivity maps in diffusion tensor, and two motor-related independent component analysis maps in resting state functional magnetic resonance imaging to predict Fugl-Meyer motor assessment scores with the covariate as the onset duration after stroke. The results were validated using the leave-one-subject-out cross-validation method. This study is the first to apply machine learning in this area using multimodal magnetic resonance imaging data, which constitutes the main novelty. Multimodal magnetic resonance imaging correctly predicted the Fugl-Meyer motor assessment score in 72 % of cases with a normalized mean squared error of 5.93 (p value = 0.0020). The ipsilesional premotor, periventricular, and contralesional cerebellar areas were shown to be of relatively high importance in the prediction. Machine learning using multimodal magnetic resonance imaging data after a stroke may predict motor outcome.
10.1016/j.neulet.2020.135451
Machine Learning Methods Predict Individual Upper-Limb Motor Impairment Following Therapy in Chronic Stroke.
Tozlu Ceren,Edwards Dylan,Boes Aaron,Labar Douglas,Tsagaris K Zoe,Silverstein Joshua,Pepper Lane Heather,Sabuncu Mert R,Liu Charles,Kuceyeski Amy
Neurorehabilitation and neural repair
. Accurate prediction of clinical impairment in upper-extremity motor function following therapy in chronic stroke patients is a difficult task for clinicians but is key in prescribing appropriate therapeutic strategies. Machine learning is a highly promising avenue with which to improve prediction accuracy in clinical practice. . The objective was to evaluate the performance of 5 machine learning methods in predicting postintervention upper-extremity motor impairment in chronic stroke patients using demographic, clinical, neurophysiological, and imaging input variables. . A total of 102 patients (female: 31%, age 61 ± 11 years) were included. The upper-extremity Fugl-Meyer Assessment (UE-FMA) was used to assess motor impairment of the upper limb before and after intervention. Elastic net (EN), support vector machines, artificial neural networks, classification and regression trees, and random forest were used to predict postintervention UE-FMA. The performances of methods were compared using cross-validated . . EN performed significantly better than other methods in predicting postintervention UE-FMA using demographic and baseline clinical data (median < .05). Preintervention UE-FMA and the difference in motor threshold (MT) between the affected and unaffected hemispheres were the strongest predictors. The difference in MT had greater importance than the absence or presence of a motor-evoked potential (MEP) in the affected hemisphere. . Machine learning methods may enable clinicians to accurately predict a chronic stroke patient's postintervention UE-FMA. Interhemispheric difference in the MT is an important predictor of chronic stroke patients' response to therapy and, therefore, could be included in prospective studies.
10.1177/1545968320909796
Coherent neural oscillations inform early stroke motor recovery.
Cassidy Jessica M,Wodeyar Anirudh,Srinivasan Ramesh,Cramer Steven C
Human brain mapping
Neural oscillations may contain important information pertaining to stroke rehabilitation. This study examined the predictive performance of electroencephalography-derived neural oscillations following stroke using a data-driven approach. Individuals with stroke admitted to an inpatient rehabilitation facility completed a resting-state electroencephalography recording and structural neuroimaging around the time of admission and motor testing at admission and discharge. Using a lasso regression model with cross-validation, we determined the extent of motor recovery (admission to discharge change in Functional Independence Measurement motor subscale score) prediction from electroencephalography, baseline motor status, and corticospinal tract injury. In 27 participants, coherence in a 1-30 Hz band between leads overlying ipsilesional primary motor cortex and 16 leads over bilateral hemispheres predicted 61.8% of the variance in motor recovery. High beta (20-30 Hz) and alpha (8-12 Hz) frequencies contributed most to the model demonstrating both positive and negative associations with motor recovery, including high beta leads in supplementary motor areas and ipsilesional ventral premotor and parietal regions and alpha leads overlying contralesional temporal-parietal and ipsilesional parietal regions. Electroencephalography power, baseline motor status, and corticospinal tract injury did not significantly predict motor recovery during hospitalization (R = 0-6.2%). Findings underscore the relevance of oscillatory synchronization in early stroke rehabilitation while highlighting contributions from beta and alpha frequency bands and frontal, parietal, and temporal-parietal regions overlooked by traditional hypothesis-driven prediction models.
10.1002/hbm.25643
Motor tract integrity predicts walking recovery: A diffusion MRI study in subacute stroke.
Soulard Julie,Huber Coline,Baillieul Sebastien,Thuriot Antoine,Renard Felix,Aubert Broche Bérengère,Krainik Alexandre,Vuillerme Nicolas,Jaillard Assia,
Neurology
OBJECTIVE:To identify candidate biomarkers of walking recovery with motor tract integrity measurements using fractional anisotropy (FA) from the corticospinal tract (CST) and alternative motor pathways in patients with moderate to severe subacute stroke. METHODS:Walking recovery was first assessed with generalized linear mixed model (GLMM) with repeated measures of walking scores (WS) over 2 years of follow-up in a longitudinal study of 29 patients with subacute ischemic stroke. Baseline FA measures from the ipsilesional and contralesional CST (i-CST and c-CST), cortico-reticulospinal pathway (i-CRP and c-CRP), and cerebellar peduncles were derived from a 60-direction diffusion MRI sequence on a 3T scanner. We performed correlation tests between WS and FA measures. Third, we investigated using GLMM whether motor tract integrity contributes to predict walking recovery. RESULTS:We observed significant improvements of WS over time with a plateau reached at ≈6 months after stroke. WS significantly correlated with FA measures from i-CST, c-CST, i-CRP, and bilateral cerebellar peduncles. Walking recovery was predicted by FA measures from 3 tracts: i-CST, i-CRP, and contralesional superior cerebellar peduncle (c-SCP). Diffusion tensor imaging (DTI) predictors captured 80.5% of the unexplained variance of the model without DTI. CONCLUSIONS:We identified i-CST and alternative motor-related tracts (namely i-CRP and c-SCP) as candidate biomarkers of walking recovery. The role of the SCP in walk recovery may rely on cerebellar nuclei projections to the thalamus, red nucleus, and reticular formation. Our findings suggest that a set of white matter tracts, part of subcortical motor networks, contribute to walking recovery in patients with moderate to severe stroke.
10.1212/WNL.0000000000008755
A new early and automated MRI-based predictor of motor improvement after stroke.
Granziera Cristina,Daducci Alessandro,Meskaldji Djalel E,Roche Alexis,Maeder Philippe,Michel Patrik,Hadjikhani Nouchine,Sorensen A Gregory,Frackowiak Richard S,Thiran Jean-Philippe,Meuli Reto,Krueger Gunnar
Neurology
OBJECTIVES:In this study, we investigated the structural plasticity of the contralesional motor network in ischemic stroke patients using diffusion magnetic resonance imaging (MRI) and explored a model that combines a MRI-based metric of contralesional network integrity and clinical data to predict functional outcome at 6 months after stroke. METHODS:MRI and clinical examinations were performed in 12 patients in the acute phase, at 1 and 6 months after stroke. Twelve age- and gender-matched controls underwent 2 MRIs 1 month apart. Structural remodeling after stroke was assessed using diffusion MRI with an automated measurement of generalized fractional anisotropy (GFA), which was calculated along connections between contralesional cortical motor areas. The predictive model of poststroke functional outcome was computed using a linear regression of acute GFA measures and the clinical assessment. RESULTS:GFA changes in the contralesional motor tracts were found in all patients and differed significantly from controls (0.001 ≤ p < 0.05). GFA changes in intrahemispheric and interhemispheric motor tracts correlated with age (p ≤ 0.01); those in intrahemispheric motor tracts correlated strongly with clinical scores and stroke sizes (p ≤ 0.001). GFA measured in the acute phase together with a routine motor score and age were a strong predictor of motor outcome at 6 months (r(2) = 0.96, p = 0.0002). CONCLUSION:These findings represent a proof of principle that contralesional diffusion MRI measures may provide reliable information for personalized rehabilitation planning after ischemic motor stroke.
10.1212/WNL.0b013e31825f25e7
Prediction of motor recovery after ischemic stroke: Clinical and diffusion tensor imaging study.
Shaheen Hala A,Sayed Sayed S,Magdy Mostafa M,Saad Mohamed A,Magdy Ahmad M,Daker Lamiaa I
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND:The severity of stroke-induced disruption to the corticospinal tract (CST) would be predictable to affect motor outcome. Diffusion tensor imaging (DTI) is a noninvasive technique that can be applied to assess the structural integrity of the CST. AIM OF THE WORK:To assess the value of DTI in patients early presenting with acute ischemic stroke as a prognostic modality to predict the clinical outcome PATIENTS AND METHODS: Thirty-four patients with acute ischemic stroke underwent clinical assessment using the National Institutes of Health Stroke Scale (NIHSS), Modified Rankin Scale (mRS), Medical Research Council (MRC) score, Morticity Index (MI), and DTI to detect the degree of reduction of fractional anisotropy (FA), and pattern of CST at baseline and after 6 months follow up. Seventeen age, sex matched controls underwent DTI assessment. RESULTS:The stroke patients showed a significant reduction in the baseline FA values of the CSTs on the affected sides compared to the contralateral sides and controls. Moreover, they showed lower mean baseline FA lesion side and FA ratio(rFA) compared to follow up. The patients with high baseline FA, rFA showed good recovery response with cut off values of 0.483, 0.948 respectively. There was a significant negative correlation between baseline FA on the lesion side, rFA and follow up NIHSS, and MRS scores and they had a significant positive correlation with follow up MI scores. CONCLUSION:Patients with higher baseline FA, rFA values were correlated with better motor recovery, and could predict the motor recovery in ischemic stroke patients.
10.1016/j.jocn.2021.12.029
Primary motor cortex in stroke: a functional MRI-guided proton MR spectroscopic study.
Cirstea Carmen M,Brooks William M,Craciunas Sorin C,Popescu Elena A,Choi In-Young,Lee Phil,Bani-Ahmed Ali,Yeh Hung-Wen,Savage Cary R,Cohen Leonardo G,Nudo Randolph J
Stroke
BACKGROUND AND PURPOSE:Our goal was to investigate whether certain metabolites, specific to neurons, glial cells, or the neuronal-glial neurotransmission system, in primary motor cortices (M1), are altered and correlated with clinical motor severity in chronic stroke. METHODS:Fourteen survivors of a single ischemic stroke located outside the M1 and 14 age-matched healthy control subjects were included. At >6 months after stroke, N-acetylaspartate, myo-inositol, and glutamate/glutamine were measured using proton magnetic resonance spectroscopic imaging (in-plane resolution=5×5 mm(2)) in radiologically normal-appearing gray matter of the hand representation area, identified by functional MRI, in each M1. Metabolite concentrations and analyses of metabolite correlations within M1 were determined. Relationships between metabolite concentrations and arm motor impairment were also evaluated. RESULTS:The stroke survivors showed lower N-acetylaspartate and higher myo-inositol across ipsilesional and contralesional M1 compared with control subjects. Significant correlations between N-acetylaspartate and glutamate/glutamine were found in either M1. Ipsilesional N-acetylaspartate and glutamate/glutamine were positively correlated with arm motor impairment and contralesional N-acetylaspartate with time after stroke. CONCLUSIONS:Our preliminary data demonstrated significant alterations of neuronal-glial interactions in spared M1 with the ipsilesional alterations related to stroke severity and contralesional alterations to stroke duration. Thus, MR spectroscopy might be a sensitive method to quantify relevant metabolite changes after stroke and consequently increase our knowledge of the factors leading from these changes in spared motor cortex to motor impairment after stroke.
10.1161/STROKEAHA.110.601047
Prediction of Motor Outcome of Stroke Patients Using a Deep Learning Algorithm with Brain MRI as Input Data.
European neurology
BACKGROUND:Deep learning techniques can outperform traditional machine learning techniques and learn from unstructured and perceptual data, such as images and languages. We evaluated whether a convolutional neural network (CNN) model using whole axial brain T2-weighted magnetic resonance (MR) images as input data can help predict motor outcomes of the upper and lower limbs at the chronic stage in stroke patients. METHODS:We collected MR images taken at the early stage of stroke in 1,233 consecutive stroke patients. We categorized modified Brunnstrom classification (MBC) scores of ≥5 and functional ambulatory category (FAC) scores of ≥4 at 6 months after stroke as favorable outcomes in the upper and lower limbs, respectively, and MBC scores of <5 and FAC scores of <4 as poor outcomes. We applied a CNN to train the image data. Of the 1,233 patients, 70% (863 patients) were randomly selected for the training set and the remaining 30% (370 patients) were assigned to the validation set. RESULTS:In the prediction of upper limb motor function on the validation dataset, the area under the curve (AUC) was 0.768, and for lower limb motor function, the AUC was 0.828. CONCLUSION:We showed that a CNN model trained using whole-brain axial T2-weighted MR images of stroke patients would help predict upper and lower limb motor function at the chronic stage.
10.1159/000525222
Corticospinal tract diffusion abnormalities early after stroke predict motor outcome.
Neurorehabilitation and neural repair
BACKGROUND:Prognosis of long-term motor outcome of acute stroke patients with severe motor impairment is difficult to determine. OBJECTIVE:Our primary goal was to evaluate the prognostic value of corticospinal tract (CST) injury on motor outcome of the upper limb compared with motor impairment level and lesion volume. METHODS:In all, 10 acute stroke patients with moderately severe to severe motor impairment of the upper limb underwent diffusion tensor imaging (DTI) and testing of upper limb strength and dexterity at acute, subacute, and chronic poststroke time points. A density-weighted CST atlas was constructed using DTI tractography data from normal participants. This CST atlas was applied, using a largely automated process, to DTI data from patients to quantify CST injury at each time point. Differences in axial diffusivity (AD), radial diffusivity (RD), and fractional anisotropy (FA) of the ipsilesional CST relative to the contralesional CST were measured. RESULTS:Acute loss in CST AD correlated most strongly and significantly with subacute and chronic strength and dexterity and remained significant after adjusting for acute motor impairment or lesion volume. Subacute loss in CST FA correlated most strongly with chronic dexterity, whereas subacute behavioral measures of limb strength correlated most strongly with chronic strength measures. CONCLUSIONS:Loss in acute CST AD and subacute CST FA are strong prognostic indicators of future motor functions of the upper limb for stroke patients with substantial initial motor impairment. DTI-derived measure of CST injury early after stroke may have utility in health care planning and in design of acute stroke clinical trials.
10.1177/1545968314521896
Recovery and Prediction of Bimanual Hand Use After Stroke.
Plantin Jeanette,Verneau Marion,Godbolt Alison K,Pennati Gaia Valentina,Laurencikas Evaldas,Johansson Birgitta,Krumlinde-Sundholm Lena,Baron Jean-Claude,Borg Jörgen,Lindberg Påvel G
Neurology
OBJECTIVE:To determine similarities and differences in key predictors of recovery of bimanual hand use and unimanual motor impairment after stroke. METHOD:In this prospective longitudinal study, 89 patients with first-ever stroke with arm paresis were assessed at 3 weeks and 3 and 6 months after stroke onset. Bimanual activity performance was assessed with the Adult Assisting Hand Assessment Stroke (Ad-AHA), and unimanual motor impairment was assessed with the Fugl-Meyer Assessment (FMA). Candidate predictors included shoulder abduction and finger extension measured by the corresponding FMA items (FMA-SAFE; range 0-4) and sensory and cognitive impairment. MRI was used to measure weighted corticospinal tract lesion load (wCST-LL) and resting-state interhemispheric functional connectivity (FC). RESULTS:Initial Ad-AHA performance was poor but improved over time in all (mild-severe) impairment subgroups. Ad-AHA correlated with FMA at each time point ( > 0.88, < 0.001), and recovery trajectories were similar. In patients with moderate to severe initial FMA, FMA-SAFE score was the strongest predictor of Ad-AHA outcome ( = 0.81) and degree of recovery ( = 0.64). Two-point discrimination explained additional variance in Ad-AHA outcome ( = 0.05). Repeated analyses without FMA-SAFE score identified wCST-LL and cognitive impairment as additional predictors. A wCST-LL >5.5 cm strongly predicted low to minimal FMA/Ad-AHA recovery (≤10 and 20 points respectively, specificity = 0.91). FC explained some additional variance to FMA-SAFE score only in unimanual recovery. CONCLUSION:Although recovery of bimanual activity depends on the extent of corticospinal tract injury and initial sensory and cognitive impairments, FMA-SAFE score captures most of the variance explained by these mechanisms. FMA-SAFE score, a straightforward clinical measure, strongly predicts bimanual recovery. CLINICALTRIALSGOV IDENTIFIER:NCT02878304. CLASSIFICATION OF EVIDENCE:This study provides Class I evidence that the FMA-SAFE score predicts bimanual recovery after stroke.
10.1212/WNL.0000000000012366
Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.
Du Juan,Yang Fang,Zhang Zhiqiang,Hu Jingze,Xu Qiang,Hu Jianping,Zeng Fanyong,Lu Guangming,Liu Xinfeng
Brain imaging and behavior
An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.
10.1007/s11682-018-9851-y
Parietal operculum and motor cortex activities predict motor recovery in moderate to severe stroke.
Hannanu Firdaus Fabrice,Zeffiro Thomas A,Lamalle Laurent,Heck Olivier,Renard Félix,Thuriot Antoine,Krainik Alexandre,Hommel Marc,Detante Olivier,Jaillard Assia,
NeuroImage. Clinical
While motor recovery following mild stroke has been extensively studied with neuroimaging, mechanisms of recovery after moderate to severe strokes of the types that are often the focus for novel restorative therapies remain obscure. We used fMRI to: 1) characterize reorganization occurring after moderate to severe subacute stroke, 2) identify brain regions associated with motor recovery and 3) to test whether brain activity associated with passive movement measured in the subacute period could predict motor outcome six months later. Because many patients with large strokes involving sensorimotor regions cannot engage in voluntary movement, we used passive flexion-extension of the paretic wrist to compare 21 patients with subacute ischemic stroke to 24 healthy controls one month after stroke. Clinical motor outcome was assessed with Fugl-Meyer motor scores (motor-FMS) six months later. Multiple regression, with predictors including baseline (one-month) motor-FMS and sensorimotor network regional activity (ROI) measures, was used to determine optimal variable selection for motor outcome prediction. Sensorimotor network ROIs were derived from a meta-analysis of arm voluntary movement tasks. Bootstrapping with 1000 replications was used for internal model validation. During passive movement, both control and patient groups exhibited activity increases in multiple bilateral sensorimotor network regions, including the primary motor (MI), premotor and supplementary motor areas (SMA), cerebellar cortex, putamen, thalamus, insula, Brodmann area (BA) 44 and parietal operculum (OP1-OP4). Compared to controls, patients showed: 1) lower task-related activity in ipsilesional MI, SMA and contralesional cerebellum (lobules V-VI) and 2) higher activity in contralesional MI, superior temporal gyrus and OP1-OP4. Using multiple regression, we found that the combination of baseline motor-FMS, activity in ipsilesional MI (BA4a), putamen and ipsilesional OP1 predicted motor outcome measured 6 months later (adjusted-R = 0.85; bootstrap p < 0.001). Baseline motor-FMS alone predicted only 54% of the variance. When baseline motor-FMS was removed, the combination of increased activity in ipsilesional MI-BA4a, ipsilesional thalamus, contralesional mid-cingulum, contralesional OP4 and decreased activity in ipsilesional OP1, predicted better motor outcome (djusted-R = 0.96; bootstrap p < 0.001). In subacute stroke, fMRI brain activity related to passive movement measured in a sensorimotor network defined by activity during voluntary movement predicted motor recovery better than baseline motor-FMS alone. Furthermore, fMRI sensorimotor network activity measures considered alone allowed excellent clinical recovery prediction and may provide reliable biomarkers for assessing new therapies in clinical trial contexts. Our findings suggest that neural reorganization related to motor recovery from moderate to severe stroke results from balanced changes in ipsilesional MI (BA4a) and a set of phylogenetically more archaic sensorimotor regions in the ventral sensorimotor trend, in which OP1 and OP4 processes may complement the ipsilesional dorsal motor cortex in achieving compensatory sensorimotor recovery.
10.1016/j.nicl.2017.01.023
Post-stroke outcomes predicted from multivariate lesion-behaviour and lesion network mapping.
Brain : a journal of neurology
Clinicians and scientists alike have long sought to predict the course and severity of chronic post-stroke cognitive and motor outcomes, as the ability to do so would inform treatment and rehabilitation strategies. However, it remains difficult to make accurate predictions about chronic post-stroke outcomes due, in large part, to high inter-individual variability in recovery and a reliance on clinical heuristics rather than empirical methods. The neuroanatomical location of a stroke is a key variable associated with long-term outcomes, and because lesion location can be derived from routinely collected clinical neuroimaging data there is an opportunity to use this information to make empirically based predictions about post-stroke deficits. For example, lesion location can be compared to statistically weighted multivariate lesion-behaviour maps of neuroanatomical regions that, when damaged, are associated with specific deficits based on aggregated outcome data from large cohorts. Here, our goal was to evaluate whether we can leverage lesion-behaviour maps based on data from two large cohorts of individuals with focal brain lesions to make predictions of 12-month cognitive and motor outcomes in an independent sample of stroke patients. Further, we evaluated whether we could augment these predictions by estimating the structural and functional networks disrupted in association with each lesion-behaviour map through the use of structural and functional lesion network mapping, which use normative structural and functional connectivity data from neurologically healthy individuals to elucidate lesion-associated networks. We derived these brain network maps using the anatomical regions with the strongest association with impairment for each cognitive and motor outcome based on lesion-behaviour map results. These peak regional findings became the 'seeds' to generate networks, an approach that offers potentially greater precision compared to previously used single-lesion approaches. Next, in an independent sample, we quantified the overlap of each lesion location with the lesion-behaviour maps and structural and functional lesion network mapping and evaluated how much variance each could explain in 12-month behavioural outcomes using a latent growth curve statistical model. We found that each lesion-deficit mapping modality was able to predict a statistically significant amount of variance in cognitive and motor outcomes. Both structural and functional lesion network maps were able to predict variance in 12-month outcomes beyond lesion-behaviour mapping. Functional lesion network mapping performed best for the prediction of language deficits, and structural lesion network mapping performed best for the prediction of motor deficits. Altogether, these results support the notion that lesion location and lesion network mapping can be combined to improve the prediction of post-stroke deficits at 12-months.
10.1093/brain/awac010
Predicting Motor Outcomes in Stroke Patients Using Diffusion Spectrum MRI Microstructural Measures.
Hodgson Kyler,Adluru Ganesh,Richards Lorie G,Majersik Jennifer J,Stoddard Greg,Adluru Nagesh,DiBella Edward
Frontiers in neurology
Improved understanding of neuroimaging signal changes and their relation to patient outcomes after ischemic stroke is needed to improve ability to predict motor improvement and make therapy recommendations. The posterior limb of the internal capsule (PLIC) is a hub of afferent and efferent motor signaling and this work proposes new, image-based methods for prognosis based on interhemispheric differences in the PLIC. In this work, nine acute supratentorial ischemic stroke patients with motor impairment received a baseline, 203-direction diffusion brain MRI and a clinical assessment 3-12 days post-stroke and were compared to nine age-matched healthy controls. Asymmetries based on the mean and Kullback-Leibler divergence in the ipsilesional and contralesional PLIC were calculated for diffusion tensor imaging (DTI) and diffusion spectrum imaging (DSI) measures from the baseline MRI. Predictions of upper extremity Fugl-Meyer (FM) scores at 5-weeks follow-up from baseline measures of PLIC asymmetry in diffusion tensor imaging (DTI) and diffusion spectrum imaging (DSI) models were evaluated. For the stroke participants, the baseline asymmetry measures in the PLIC for the orientation dispersion index of the neurite orientation dispersion and density imaging (NODDI) model were highly correlated with upper extremity FM outcomes ( = 0.83). Use of DSI and the NODDI orientation dispersion index parameter shows promise of being more predictive of stroke recovery and to help better understand white matter changes in stroke, beyond DTI measures. The new finding that baseline interhemispheric differences in the PLIC calculated from the orientation dispersion index of the NODDI model are highly correlated with upper extremity functional outcomes may lead to improved image-based motor-outcome prediction after middle cerebral artery ischemic stroke.
10.3389/fneur.2019.00072
Post-stroke deficit prediction from lesion and indirect structural and functional disconnection.
Brain : a journal of neurology
Behavioural deficits in stroke reflect both structural damage at the site of injury, and widespread network dysfunction caused by structural, functional, and metabolic disconnection. Two recent methods allow for the estimation of structural and functional disconnection from clinical structural imaging. This is achieved by embedding a patient's lesion into an atlas of functional and structural connections in healthy subjects, and deriving the ensemble of structural and functional connections that pass through the lesion, thus indirectly estimating its impact on the whole brain connectome. This indirect assessment of network dysfunction is more readily available than direct measures of functional and structural connectivity obtained with functional and diffusion MRI, respectively, and it is in theory applicable to a wide variety of disorders. To validate the clinical relevance of these methods, we quantified the prediction of behavioural deficits in a prospective cohort of 132 first-time stroke patients studied at 2 weeks post-injury (mean age 52.8 years, range 22-77; 63 females; 64 right hemispheres). Specifically, we used multivariate ridge regression to relate deficits in multiple functional domains (left and right visual, left and right motor, language, spatial attention, spatial and verbal memory) with the pattern of lesion and indirect structural or functional disconnection. In a subgroup of patients, we also measured direct alterations of functional connectivity with resting-state functional MRI. Both lesion and indirect structural disconnection maps were predictive of behavioural impairment in all domains (0.16 < R2 < 0.58) except for verbal memory (0.05 < R2 < 0.06). Prediction from indirect functional disconnection was scarce or negligible (0.01 < R2 < 0.18) except for the right visual field deficits (R2 = 0.38), even though multivariate maps were anatomically plausible in all domains. Prediction from direct measures of functional MRI functional connectivity in a subset of patients was clearly superior to indirect functional disconnection. In conclusion, the indirect estimation of structural connectivity damage successfully predicted behavioural deficits post-stroke to a level comparable to lesion information. However, indirect estimation of functional disconnection did not predict behavioural deficits, nor was a substitute for direct functional connectivity measurements, especially for cognitive disorders.
10.1093/brain/awaa156
The structural connectome and motor recovery after stroke: predicting natural recovery.
Brain : a journal of neurology
Stroke patients vary considerably in terms of outcomes: some patients present 'natural' recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify individual recovery potential to make personalized decisions for neuro-rehabilitation, obviating the 'one-size-fits-all' approach. This goal requires (i) the prediction of individual courses of recovery in the acute stage; and (ii) an understanding of underlying neuronal network mechanisms. 'Natural' recovery is especially variable in severely impaired patients, underscoring the special clinical importance of prediction for this subgroup. Fractional anisotropy connectomes based on individual tractography of 92 patients were analysed 2 weeks after stroke (TA) and their changes to 3 months after stroke (TC - TA). Motor impairment was assessed using the Fugl-Meyer Upper Extremity (FMUE) scale. Support vector machine classifiers were trained to separate patients with natural recovery from patients without natural recovery based on their whole-brain structural connectomes and to define their respective underlying network patterns, focusing on severely impaired patients (FMUE < 20). Prediction accuracies were cross-validated internally, in one independent dataset and generalized in two independent datasets. The initial connectome 2 weeks after stroke was capable of segregating fitters from non-fitters, most importantly among severely impaired patients (TA: accuracy = 0.92, precision = 0.93). Secondary analyses studying recovery-relevant network characteristics based on the selected features revealed (i) relevant differences between networks contributing to recovery at 2 weeks and network changes over time (TC - TA); and (ii) network properties specific to severely impaired patients. Important features included the parietofrontal motor network including the intraparietal sulcus, premotor and primary motor cortices and beyond them also attentional, somatosensory or multimodal areas (e.g. the insula), strongly underscoring the importance of whole-brain connectome analyses for better predicting and understanding recovery from stroke. Computational approaches based on structural connectomes allowed the individual prediction of natural recovery 2 weeks after stroke onset, especially in the difficult to predict group of severely impaired patients, and identified the relevant underlying neuronal networks. This information will permit patients to be stratified into different recovery groups in clinical settings and will pave the way towards personalized precision neurorehabilitative treatment.
10.1093/brain/awab082
An overview of fractional anisotropy as a reliable quantitative measurement for the corticospinal tract (CST) integrity in correlation with a Fugl-Meyer assessment in stroke rehabilitation.
Zolkefley Mohd Khairul Izamil,Firwana Younis M S,Hatta Hasnettty Zuria Mohamed,Rowbin Christina,Nassir Che Mohd Nasril Che Mohd,Hanafi Muhammad Hafiz,Abdullah Mohd Shafie,Mustapha Muzaimi
Journal of physical therapy science
[Purpose] Understanding the essential mechanisms in post-stroke recovery not only provides important basic insights into brain function and plasticity but can also guide the development of new therapeutic approaches for stroke patients. This review aims to give an overview of how various variables of Magnetic Resonance-Diffusion Tensor Imaging (MR-DTI) metrics of fractional anisotropy (FA) can be used as a reliable quantitative measurement and indicator of corticospinal tract (CST) changes, particularly in relation to functional motor outcome correlation with a Fugl-Meyer assessment in stroke rehabilitation. [Methods] PubMed electronic database was searched for the relevant literature, using key words of diffusion tensor imaging (dti), corticospinal tract, and stroke. [Results] We reviewed the role of FA in monitoring CST remodeling and its role of predicting motor recovery after stroke. We also discussed the mechanism of CST remodeling and its modulation from the value of FA and FMA-UE. [Conclusion] Heterogeneity of post-stroke brain disorganization and motor impairment is a recognized challenge in the development of accurate indicators of CST integrity. DTI-based FA measurements offer a reliable and evidence-based indicator for CST integrity that would aid in predicting motor recovery within the context of stroke rehabilitation.
10.1589/jpts.33.75
Prediction of motor outcome for hemiparetic stroke patients using diffusion tensor imaging: A review.
Jang Sung Ho
NeuroRehabilitation
We reviewed relevant diffusion tensor imaging (DTI) studies on prediction of motor outcome in hemiparetic stroke patients in order to evaluate the following objectives: characteristics of DTI for prediction of motor outcome in stroke patients, previous DTI studies, and future direction. DTI offers the unique advantage of visualization and estimation of the corticospinal tract, which is the most important neural tract for motor function. Although prediction of motor outcome is a very important topic for clinicians, only about a dozen DTI studies have been reported on this topic. These studies can be classified into two groups: 1) studies for adoption of DTI parameters as a potential marker for prediction of motor outcome in stroke patients, and 2) studies for analysis of the integrity of the corticospinal tract in prediction of motor outcome. In order to increase the predictability of motor outcome, studies according to the somatotopy and studies combined with transcranial magnetic stimulation are necessary. Other additional studies on optimal DTI scanning time for motor prediction will also be required.
10.3233/NRE-2010-0621
Beyond Diffusion Tensor MRI Methods for Improved Characterization of the Brain after Ischemic Stroke: A Review.
AJNR. American journal of neuroradiology
Ischemic stroke is a worldwide problem, with 15 million people experiencing a stroke annually. MR imaging is a valuable tool for understanding and assessing brain changes after stroke and predicting recovery. Of particular interest is the use of diffusion MR imaging in the nonacute stage 1-30 days poststroke. Thousands of articles have been published on the use of diffusion MR imaging in stroke, including several recent articles reviewing the use of DTI for stroke. The goal of this work was to survey and put into context the recent use of diffusion MR imaging methods beyond DTI, including diffusional kurtosis, generalized fractional anisotropy, spherical harmonics methods, and neurite orientation and dispersion models, in patients poststroke. Early studies report that these types of beyond-DTI methods outperform DTI metrics either in being more sensitive to poststroke changes or by better predicting outcome motor scores. More and larger studies are needed to confirm the improved prediction of stroke recovery with the beyond-DTI methods.
10.3174/ajnr.A7414
Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke.
Puig Josep,Blasco Gerard,Schlaug Gottfried,Stinear Cathy M,Daunis-I-Estadella Pepus,Biarnes Carles,Figueras Jaume,Serena Joaquín,Hernández-Pérez Maria,Alberich-Bayarri Angel,Castellanos Mar,Liebeskind David S,Demchuk Andrew M,Menon Bijoy K,Thomalla Götz,Nael Kambiz,Wintermark Max,Pedraza Salvador
Neuroradiology
PURPOSE:Despite improved acute treatment and new tools to facilitate recovery, most patients have motor deficits after stroke, often causing disability. However, motor impairment varies considerably among patients, and recovery in the acute/subacute phase is difficult to predict using clinical measures alone, particularly in severely impaired patients. Accurate early prediction of recovery would help rationalize rehabilitation goals and improve the design of trials testing strategies to facilitate recovery. METHODS:We review the role of diffusion tensor imaging (DTI) in predicting motor recovery after stroke, in monitoring treatment response, and in evaluating white matter remodeling. We critically appraise DTI studies and discuss their limitations, and we explore directions for future study. RESULTS:Growing evidence suggests that combining clinical scores with information about corticospinal tract (CST) integrity can improve predictions about motor outcome. The extent of CST damage on DTI and/or the overlap between the CST and a lesion are key prognostic factor that determines motor performance and outcome. Three main strategies to quantify stroke-related CST damage have been proposed: (i) measuring FA distal to the stroke area, (ii) measuring the number of fibers that go through the stroke with tractography, and (iii) measuring the overlap between the stroke and a CST map derived from healthy age- and gender-matched controls. CONCLUSION:Recovery of motor function probably involves remodeling of the CST proper and/or a greater reliance on alternative motor tracts through spontaneous and treatment-induced plasticity. DTI-metrics represent promising clinical biomarkers to predict motor recovery and to monitor and predict the response to neurorehabilitative interventions.
10.1007/s00234-017-1816-0
Disruption of motor network connectivity post-stroke and its noninvasive neuromodulation.
Grefkes Christian,Fink Gereon R
Current opinion in neurology
PURPOSE OF REVIEW:We review the latest evidence for the neural underpinnings of hand motor function recovery after stroke with particular emphasis on how the latter can be enhanced by noninvasive brain stimulation techniques such as repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS). RECENT FINDINGS:New data from longitudinal studies in which rTMS of the lesioned or contralesional motor cortex was combined with motor training showed ambiguous effects: some patients improved whereas others did not show any rTMS effect (compared with control stimulation). In contrast, novel studies using tDCS point to a more consistent effect on distal upper limb function, especially for inhibitory (cathodal) tDCS applied over contralesional M1. Neuroimaging data reveal that the effects of rTMS/tDCS on the functional architecture of the motor system depend upon lesion location, degree of impairment and number of treatment sessions. Furthermore, analyses of regional brain activity and motor network connectivity allow prediction of the behavioural effects of brain stimulation. SUMMARY:rTMS and tDCS can be used to modulate stroke-induced changes of motor network activity and connectivity thereby improving hand motor function. The interindividual variability in response to brain stimulation calls for the identification of treatment-associated surrogate markers, which may be provided by neuroimaging.
10.1097/WCO.0b013e3283598473
Prediction of motor recovery after stroke: being pragmatic or innovative?
Rosso Charlotte,Lamy Jean-Charles
Current opinion in neurology
PURPOSE OF REVIEW:This review considers both pragmatic and cutting-edge approaches for predicting motor stroke recovery over the period 2017-2019. It focuses on the predictive value of clinical scores and biomarkers including Transcranial Magnetic Stimulation (TMS) and MRI as well as more innovative alternatives. RECENT FINDINGS:Clinical scores combined with corticospinal tract (CST) integrity as assessed by both TMS-induced motor-evoked potential (MEP) and MRI predict motor recovery with an accuracy of about 75%. Therefore, research on novel biomarkers is still needed to improve the accuracy of these models. SUMMARY:Up to date, there is no consensus about which predictive models should be used in clinical routine. Decision trees, such as the PREP2 algorithm are probably the easiest approach to operationalize the translation of predictive models from bench to bedside. However, external validation is still needed to implement current models.
10.1097/WCO.0000000000000843
Motor outcome and motor recovery mechanisms in pontine infarct: a review.
Jang Sung Ho
NeuroRehabilitation
Characteristics of motor recovery mechanisms are known to be linked with motor outcome in stroke. Detailed knowledge of motor outcome and recovery mechanisms in stroke allow for prediction of prognosis and provide the basis for establishment of scientific rehabilitation strategies. Thirteen previous studies with regard to motor outcome (8 studies) and the motor recovery mechanisms (5 studies) in pontine infarct were reviewed. Several motor recovery mechanisms have been reported in pontine infarct: peri-lesional reorganization, and other possible recovery mechanisms (aberrant pyramidal tract, ipsilateral motor pathway, and motor recovery via spared corticospinal tract). Previous studies on motor outcome in pontine infarct have reported generally good outcome. This good motor outcome appears to be related to the characteristics of the motor recovery mechanisms recovered by the lateral corticospinal tract. We think that further studies on motor outcome and recovery mechanisms should be performed for clarification of various motor tracts including non-corticospinal tract, which can affect the motor outcome and recovery mechanisms in pontine infarct. In addition, the effect of rehabilitation on these topics should also be elucidated.
10.3233/NRE-2012-0738
Microstructure and Genetic Polymorphisms: Role in Motor Rehabilitation After Subcortical Stroke.
Liu Jingchun,Wang Caihong
Frontiers in aging neuroscience
Motor deficits are the most common disability after stroke, and early prediction of motor outcomes is critical for guiding the choice of early interventions. Two main factors that may impact the response to rehabilitation are variations in the microstructure of the affected corticospinal tract (CST) and genetic polymorphisms in brain-derived neurotrophic factor (BDNF). The purpose of this article was to review the role of these factors in stroke recovery, which will be useful for constructing a predictive model of rehabilitation outcomes. We review the microstructure of the CST, including its origins in the primary motor area (M1), primary sensory area (S1), premotor cortex (PMC), and supplementary motor area (SMA). Damage to these fibers is disease-causing and can directly affect rehabilitation after subcortical stroke. BDNF polymorphisms are not disease-causing but can indirectly affect neuroplasticity and thus motor recovery. Both factors are known to be correlated with motor recovery. Further work is needed using large longitudinal patient samples and animal experiments to better establish the role of these two factors in stroke rehabilitation. Microstructure and genetic polymorphisms should be considered possible predictors or covariates in studies investigating motor recovery after subcortical stroke. Future predictive models of stroke recovery will likely include a combination of structural and genetic factors to allow precise individualization of stroke rehabilitation strategies.
10.3389/fnagi.2022.813756
MRI Biomarkers for Hand-Motor Outcome Prediction and Therapy Monitoring following Stroke.
Horn U,Grothe M,Lotze M
Neural plasticity
Several biomarkers have been identified which enable a considerable prediction of hand-motor outcome after cerebral damage already in the subacute stage after stroke. We here review the value of MRI biomarkers in the evaluation of corticospinal integrity and functional recruitment of motor resources. Many of the functional imaging parameters are not feasible early after stroke or for patients with high impairment and low compliance. Whereas functional connectivity parameters have demonstrated varying results on their predictive value for hand-motor outcome, corticospinal integrity evaluation using structural imaging showed robust and high predictive power for patients with different levels of impairment. Although this is indicative of an overall higher value of structural imaging for prediction, we suggest that this variation be explained by structure and function relationships. To gain more insight into the recovering brain, not only one biomarker is needed. We rather argue for a combination of different measures in an algorithm to classify fine-graded subgroups of patients. Approaches to determining biomarkers have to take into account the established markers to provide further information on certain subgroups. Assessing the best therapy approaches for individual patients will become more feasible as these subgroups become specified in more detail. This procedure will help to considerably save resources and optimize neurorehabilitative therapy.
10.1155/2016/9265621
Structural Plasticity in Adulthood with Motor Learning and Stroke Rehabilitation.
Sampaio-Baptista Cassandra,Sanders Zeena-Britt,Johansen-Berg Heidi
Annual review of neuroscience
The development of advanced noninvasive techniques to image the human brain has enabled the demonstration of structural plasticity during adulthood in response to motor learning. Understanding the basic mechanisms of structural plasticity in the context of motor learning is essential to improve motor rehabilitation in stroke patients. Here, we review and discuss the emerging evidence for motor-learning-related structural plasticity and the implications for stroke rehabilitation. In the clinical context, a few studies have started to assess the effects of rehabilitation on structural measures to understand recovery poststroke and additionally to predict intervention outcomes. Structural imaging will likely have a role in the future in providing measures that inform patient stratification for optimal outcomes.
10.1146/annurev-neuro-080317-062015
Implementing biomarkers to predict motor recovery after stroke.
Connell Louise A,Smith Marie-Claire,Byblow Winston D,Stinear Cathy M
NeuroRehabilitation
BACKGROUND:There is growing interest in using biomarkers to predict motor recovery and outcomes after stroke. The PREP2 algorithm combines clinical assessment with biomarkers in an algorithm, to predict upper limb functional outcomes for individual patients. To date, PREP2 is the first algorithm to be tested in clinical practice, and other biomarker-based algorithms are likely to follow. PURPOSE:This review considers how algorithms to predict motor recovery and outcomes after stroke might be implemented in clinical practice. FINDINGS:There are two tasks: first the prediction information needs to be obtained, and then it needs to be used. The barriers and facilitators of implementation are likely to differ for these tasks. We identify specific elements of the Consolidated Framework for Implementation Research that are relevant to each of these two tasks, using the PREP2 algorithm as an example. These include the characteristics of the predictors and algorithm, the clinical setting and its staff, and the healthcare environment. CONCLUSIONS:Active, theoretically underpinned implementation strategies are needed to ensure that biomarkers are successfully used in clinical practice for predicting motor outcomes after stroke, and should be considered in parallel with biomarker development.
10.3233/NRE-172395