Comparing Region of Interest versus Voxel-Wise Diffusion Tensor Imaging Analytic Methods in Mild and Moderate Traumatic Brain Injury: A Systematic Review and Meta-Analysis

比较感兴趣区域与体素级扩散张量成像分析方法在轻中度创伤性脑损伤中的应用:系统评价和荟萃分析

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Abstract

Diffusion tensor imaging is a magnetic resonance imaging technique that is uniquely capable of detecting microstructural tissue damage in mild and moderate traumatic brain injuries (TBIs). To date, it remains unknown if two common analytic techniques, region of interest (ROI) versus voxel-wise (VW) analyses, detect injury in similar locations. The purpose of this systematic review and meta-analysis was to directly compare the regions of abnormality elucidated by each method. Twenty-seven ROI and 11 VW studies met our inclusion criteria. Our ROI meta-analysis identified 11 regions, including the splenium of the corpus callosum, where fractional anisotropy (FA) was significantly decreased in TBI patients, compared with controls. Likewise, we identified higher mean diffusivity/apparent diffusivity constant in the genu, body, and splenium of the corpus callosum. Alternatively, our VW analysis identified one region of high FA in the right superior longitudinal fasciculus and seven regions of low FA, with the two largest located in the corpus callosum. High mean diffusivity and high radial diffusivity, both in the right inferior longitudinal fasciculus, also was revealed by our VW analysis. Moreover, we have shown that the magnitude of damage in the corpus callosum revealed by ROI analysis (z = -3.15) is greater than that demonstrated by VW analysis (z = -1.41). Overall, this study indicates that both ROI and VW analytic methods are sensitive to low FA in the corpus callosum; however, the ROI method has more power to detect the full extent of tissue abnormality in the corpus callosum. More research utilizing standardized methods and reporting is essential to fully characterize the extent to which ROI and VW analyses can concordantly detect other locations of pathology in mild and moderate TBI patients.

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