Combining Diffusion Tensor Imaging and Gray Matter Volumetry to Investigate Motor Functioning in Chronic Stroke

Abstract

<div><p>Motor impairment after stroke is related to the integrity of the corticospinal tract (CST). However, considerable variability in motor impairment remains unexplained. To increase the accuracy in evaluating long-term motor function after ischemic stroke, we tested the hypothesis that combining diffusion tensor imaging (DTI) and gray matter (GM) volumetry can better characterize long-term motor deficit than either method alone in patients with chronic stroke. We recruited 31 patients whose Medical Research Council strength grade was ≤ 3/5 in the extensor muscles of the affected upper extremity in the acute phase. We used the Upper Extremity Fugl-Meyer (UE-FM) assessment to evaluate motor impairment, and as the primary outcome variable. We computed the fractional anisotropy ratio of the entire CST (CST_ratio) and the volume of interest ratio (VOI_ratio), between ipsilesional and contralesional hemispheres, to explain long-term motor impairment. The results showed that CST_ratio, VOI_ratio of motor-related brain regions, and VOI_ratio in the temporal lobe were correlated with UE-FM. A multiple regression model including CST_ratio and VOI_ratio of the caudate nucleus explained 40.7% of the variability in UE-FM. The adjusted R2 of the regression model with CST_ratio as an independent variable was 29.4%, and that of using VOI_ratio of the caudate nucleus as an independent variable was 23.1%. These results suggest that combining DTI and GM volumetry may achieve better explanation of long-term motor deficit in stroke patients, than using either measure individually. This finding may provide guidance in determining optimal neurorehabilitative interventions.</p></div