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    Tractography and the connectome in neurosurgical treatment of gliomas: the premise, the progress, and the potential. Henderson Fraser,Abdullah Kalil G,Verma Ragini,Brem Steven Neurosurgical focus The ability of diffusion tensor MRI to detect the preferential diffusion of water in cerebral white matter tracts enables neurosurgeons to noninvasively visualize the relationship of lesions to functional neural pathways. Although viewed as a research tool in its infancy, diffusion tractography has evolved into a neurosurgical tool with applications in glioma surgery that are enhanced by evolutions in crossing fiber visualization, edema correction, and automated tract identification. In this paper the current literature supporting the use of tractography in brain tumor surgery is summarized, highlighting important clinical studies on the application of diffusion tensor imaging (DTI) for preoperative planning of glioma resection, and risk assessment to analyze postoperative outcomes. The key methods of tractography in current practice and crucial white matter fiber bundles are summarized. After a review of the physical basis of DTI and post-DTI tractography, the authors discuss the methodologies with which to adapt DT image processing for surgical planning, as well as the potential of connectomic imaging to facilitate a network approach to oncofunctional optimization in glioma surgery. 10.3171/2019.11.FOCUS19785
    The role of diffusion tensor imaging and tractography in the surgical management of brainstem gliomas. Xiao Xiong,Kong Lu,Pan Changcun,Zhang Peng,Chen Xin,Sun Tao,Wang Mingran,Qiao Hui,Wu Zhen,Zhang Junting,Zhang Liwei Neurosurgical focus OBJECTIVE:Diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) have the ability to noninvasively visualize changes in white matter tracts, as well as their relationships with lesions and other structures. DTI/DTT has been increasingly used to improve the safety and results of surgical treatment for lesions in eloquent areas, such as brainstem cavernous malformations. This study aimed to investigate the application value of DTI/DTT in brainstem glioma surgery and to validate the spatial accuracy of reconstructed corticospinal tracts (CSTs). METHODS:A retrospective analysis was performed on 54 patients with brainstem gliomas who had undergone surgery from January 2016 to December 2018 at Beijing Tiantan Hospital. All patients underwent preoperative DTI and tumor resection with the assistance of DTT-merged neuronavigation and electrophysiological monitoring. Preoperative conventional MRI and DTI data were collected, and the muscle strength and modified Rankin Scale (mRS) score before and after surgery were measured. The surgical plan was created with the assistance of DTI/DTT findings. The accuracy of DTI/DTT was validated by performing direct subcortical stimulation (DsCS) intraoperatively. Multiple linear regression was used to investigate the relationship between quantitative parameters of DTI/DTT (such as the CST score and tumor-to-CST distance [TCD]) and postoperative muscle strength and mRS scores. RESULTS:Among the 54 patients, 6 had normal bilateral CSTs, 12 patients had unilateral CST impairments, and 36 had bilateral CSTs involved. The most common changes in the CSTs were deformation (n = 29), followed by deviation (n = 28) and interruption (n = 27). The surgical approach was changed in 18 cases (33.3%) after accounting for the DTI/DTT results. Among 55 CSTs on which DsCS was performed, 46 (83.6%) were validated as spatially accurate by DsCS. The CST score and TCD were significantly correlated with postoperative muscle strength (r = -0.395, p < 0.001, and r = 0.275, p = 0.004, respectively) and postoperative mRS score (r = 0.430, p = 0.001, and r = -0.329, p = 0.015, respectively). The CST score was independently linearly associated with postoperative muscle strength (t = -2.461, p = 0.016) and the postoperative mRS score (t = 2.052, p = 0.046). CONCLUSIONS:DTI/DTT is a valuable tool in the surgical management of brainstem gliomas. With good accuracy, it can help optimize surgical planning, guide tumor resection, and predict the postoperative muscle strength and postoperative quality of life of patients. 10.3171/2020.10.FOCUS20166
    Differentiating high-grade glioma recurrence from pseudoprogression: Comparing diffusion kurtosis imaging and diffusion tensor imaging. Wu Xiao-Feng,Liang Xiao,Wang Xiao-Chun,Qin Jiang-Bo,Zhang Lei,Tan Yan,Zhang Hui European journal of radiology PURPOSE:To compare the diagnostic value of DKI and DTI in differentiation of high-grade glioma recurrence and pseudoprogression (PsP). METHOD:Forty patients with high-grade gliomas who exhibited new enhancing lesions (24 high-grade glioma recurrence and 16 PsP) within 6 months after surgery followed by completion of chemoradiation therapy. All patients underwent repeat surgery or biopsy after routine MRI and DKI (including DTI). They were histologically classified into high-grade glioma recurrence and PsP groups. DKI (mean kurtosis [MK], axial kurtosis [Ka], and radial kurtosis [Kr]) and DTI (mean diffusivity [MD] and fractional anisotropy [FA]) parameters in the enhancing lesions and in the perilesional edema were measured. Inter-group differences between high-grade glioma recurrence and PsP were compared using the Mann-Whitney U test The receiver operating characteristic (ROC) curve was used to assess differential diagnostic efficacy of each parameter, and Z-scores were used to compare the value between DKI and DTI. RESULTS:Relative MK (rMK) was significantly higher and relative MD (rMD) was significantly lower in the enhancing lesions of high-grade glioma recurrence compared to PsP (P <  0.001, P = 0.006, respectively). The AUC was 0.914 for rMK and 0.760 for rMD, and this difference was significant (P = 0.030). In the perilesional edema, rMK values were significantly higher and rMD values were significantly lower in high-grade glioma recurrence compared to PsP (P <  0.001, P =  0.005). CONCLUSIONS:DKI had superior performance in differentiating high-grade glioma recurrence from PsP, and rMK appeared to be the best independent predictor. 10.1016/j.ejrad.2020.109445