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Κυριακή 22 Απριλίου 2018

A comparison of seven different dti-derived estimates of corticospinal tract structural characteristics in chronic stroke survivors

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Publication date: Available online 21 April 2018
Source:Journal of Neuroscience Methods
Author(s): Bokkyu Kim, Beth E. Fisher, Nicolas Schweighofer, Richard M. Leahy, Justin P. Haldar, Soyoung Choi, Dorsa B. Kay, James Gordon, Carolee J. Winstein
BackgroundDifferent diffusion tensor imaging (DTI) has been used to estimate corticospinal tract (CST) structure in the context of stroke rehabilitation research. However, there is no gold standard for the estimate of CST structure in chronic stroke survivors. This study aims to determine the most accurate DTI-derived CST estimate that is associated with a clinical motor outcome measure.MethodsWe obtained imaging and behavioral data from a phase-I stroke rehabilitation clinical trial. We included thirty seven chronic stroke survivors with mild­to­moderate motor impairment. Imaging data were processed using BrainSuite16a software. We calculated mean FA for each of 7 different ROIs/VOIs that include manually drawn 2-D ROIs and 3-D VOIs of CST from individual tractography or standard atlas. We compared ipsi- and contralesional CST FA for each method. Partial correlation was conducted between each CST FA asymmetry index and a time-based motor outcome measure, controlling for age and chronicity.ResultsIpsilesional CST FA was significantly lower than contralesional CST FA for each of the 7 methods Only CST FA asymmetry from the 3-D individual CST tractography showed a significant correlation with the primary motor outcome (r = 0.46, p = .005), while CST FA from the other six methods did not.Comparison with existing methodsCompared to the six other methods, CST FA asymmetry from 3-D individual tractography is the most accurate estimate of CST structure in this cohort of stroke survivors.ConclusionWe recommend this method for future research seeking to understand brain-behavior mechanisms of motor recovery in chronic stroke survivors.



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