Computer-assisted carotid plaque characterisation. el-Barghouty N,Geroulakos G,Nicolaides A,Androulakis A,Bahal V European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery OBJECTIVE:To determine the relationship between plaque echogenicity as measured by computer and the incidence of cerebral brain infarction. PATIENTS AND METHODS:Eighty-seven patients with 148 plaques producing more than 50% internal carotid artery stenosis were studied. Sixty-nine plaques were in asymptomatic patients, 35 were associated with amaurosis fugax, 19 with transient ischaemic attacks and 25 with stroke. All patients had a CT brain scan and the presence of ipsilateral cerebral infarction was noted. Images of the plaques obtained with an ATL Ultramark-4 Duplex scanner (7.5 MHz high resolution probe) were transferred to a computer. Using an image analysis program a histogram for each plaque was obtained with the number of pixels plotted against the grey scale (0-225). The median of the grey scale was used as a measure of echogenicity. RESULTS:Fifty-three (36%) of the 148 plaques were associated with ipsilateral CT brain infarction. Plaques with a grey scale median more than 32 (echogenic) were associated with an incidence of 11% (7/64) CT infarction. In contrast, plaques with grey scale median below or equal to 32 (echolucent) were associated with 55% (46/84) incidence of CT infarction (chi 2 = 30.35, p < 0.001, relative risk = 22, 95% confidence interval from 4.7 to 108). CONCLUSION:This study indicates that computer analysis of carotid plaque can identify high-risk carotid plaques. The potential of such analysis in the identification of asymptomatic high-risk patients should be explored in further studies.

Texture analysis of ultrasonic images of symptomatic carotid plaques can identify those plaques associated with ipsilateral embolic brain infarction. Kakkos S K,Stevens J M,Nicolaides A N,Kyriacou E,Pattichis C S,Geroulakos G,Thomas D European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery OBJECTIVES:The aim of our study was to determine the association between objective, computerised texture analysis of carotid plaque ultrasonic images and embolic CT-brain infarction in patients presenting with hemispheric neurological symptoms. DESIGN:Cross-sectional study in patients with 50%-99% (ECST) carotid stenosis. PATIENTS AND METHODS:Carotid plaque ultrasonic images (n=54, 26 with TIAs and 28 with stroke) obtained during carotid ultrasound were normalised and standardised for resolution and subsequently assessed visually for the presence of discrete echogenic or juxtaluminal echolucent components and overall echogenicity (plaque type). Using computer software, 51 histogram/textural features of the plaque outlines were calculated. Factor analysis was subsequently applied to eliminate redundant variables. Small cortical, large cortical and discrete subcortical infarcts on CT-brain scan were considered as being embolic. RESULTS:Twenty-five cases (46%) had embolic infarcts. On logistic regression, grey-scale median (GSM), a measure of echolucency, spatial grey level dependence matrices (SGLDM) correlation and SGLDM information measure of correlation-1, measures of homogeneity were significant (p<0.05), but not grey level runlength statistics (RUNL) Run Percentage (RP), stenosis severity, type of symptoms or echolucent juxtaluminal components. Using ROC curves methodology, SGLDM information measure of correlation-1 improved the value of GSM in distinguishing embolic from non-embolic CT-brain infarction. CONCLUSION:Computerised texture analysis of ultrasonic images of symptomatic carotid plaques can identify those that are associated with brain infarction, improving the results achieved by GSM alone. This methodology could be applied to prospective natural history studies of symptomatic patients not operated on or randomised trials of patients undergoing carotid angioplasty and stenting in order to identify high-risk subgroups for cerebral infarction. 10.1016/j.ejvs.2006.10.018

Quantitative Histogram Analysis on Intracranial Atherosclerotic Plaques: A High-Resolution Magnetic Resonance Imaging Study. Shi Zhang,Li Jing,Zhao Ming,Peng Wenjia,Meddings Zakaria,Jiang Tao,Liu Qi,Teng Zhongzhao,Lu Jianping Stroke BACKGROUND AND PURPOSE:Intracranial atherosclerosis is one of the main causes of stroke, and high-resolution magnetic resonance imaging provides useful imaging biomarkers related to the risk of ischemic events. This study aims to evaluate differences in histogram features between culprit and nonculprit intracranial atherosclerosis using high-resolution magnetic resonance imaging. METHODS:Two hundred forty-seven patients with intracranial atherosclerosis who underwent high-resolution magnetic resonance imaging sequentially between January 2015 and December 2016 were recruited. Quantitative features, including stenosis, plaque burden, minimum luminal area, intraplaque hemorrhage, enhancement ratio, and dispersion of signal intensity (coefficient of variation), were analyzed based on T2-, T1-, and contrast-enhanced T1-weighted images. Step-wise regression analysis was used to identify key determinates differentiating culprit and nonculprit plaques and to calculate the odds ratios (ORs) with 95% CIs. RESULTS:In total, 190 plaques were identified, of which 88 plaques (37 culprit and 51 nonculprit) were located in the middle cerebral artery and 102 (57 culprit and 45 nonculprit) in the basilar artery. Nearly 90% of culprit lesions had a degree of luminal stenosis of <70%. Multiple logistic regression analyses showed that intraplaque hemorrhage (OR, 16.294 [95% CI, 1.043-254.632]; =0.047), minimum luminal area (OR, 1.468 [95% CI, 1.032-2.087]; =0.033), and coefficient of variation (OR, 13.425 [95% CI, 3.987-45.204]; <0.001) were 3 significant features in defining culprit plaques in middle cerebral artery. The enhancement ratio (OR, 9.476 [95% CI, 1.256-71.464]; =0.029), intraplaque hemorrhage (OR, 2.847 [95% CI, 0.971-10.203]; =0.046), and coefficient of variation (OR, 10.068 [95% CI, 2.820-21.343]; <0.001) were significantly associated with plaque type in basilar artery. Coefficient of variation was a strong independent predictor in defining plaque type for both middle cerebral artery and basilar artery with sensitivity, specificity, and accuracy being 0.79, 0.80, and 0.80, respectively. CONCLUSIONS:Features characterized by high-resolution magnetic resonance imaging provided complementary values over luminal stenosis in defined lesion type for intracranial atherosclerosis; the dispersion of signal intensity in histogram analysis was a particularly effective predictive parameter. 10.1161/STROKEAHA.120.029062