Studying the Effect of Ischemic Stroke on Corticospinal Tract in Adults Using Serial Tractography

Abstract Background: Cerebrovascular ischemia results from in-sufficient blood flow due to the obstruction of blood vessels in the brain which leads to rapid cellular necrosis [1]. Depend-ing on the affected populations of neurons, serious deficits can manifest. Aim of Study: To investigate the associationof diffusion tensor imaging (DTI) metrics of the corticospinal tract (CST) and clinical assessment on motor recovery at 3 months in ischemic stroke patients. Material and Methods: 23 ischemic stroke patients were included in this observational longitudinal study. The patients underwent DTI scanning in the acute and subacute stages of stroke (Within 2 weeks from the time of the initial impairment and after 3 months respectively). Fractional anisotropy ratio (rFA) and mean diffusivity ratio (rMD)between the ipsilesional and contralesional sides were used as DTI metrics. Standard upper extremity Fugl-Meyer assessment (UE-FM) was used to estimate the functional motor outcome at the same time points of the DTI acquisition. Multipleline arregression analysis was used to develop a prediction model in order toassociate the motor outcome (UE-FM at 3 months) to DTI and initial motor assessment variables. Results: 23 stroke patients (mean age 65.70±8.86, 26.1% females) completed the study. rFA was found to show signif-icant positive correlation with the motor score (UE-FM) in the acute stage (r=0.486, p=.02) and in the subacute stage (r=0.681, p=.002). No significant correlations were found between the rMD and the motor score at either of the two time points. The multivariate regression model statistically significantly predicted the motor score at 3 months with an adjusted R2 of .420, p=.004. However, only rFA at the subacute stage was independently associated with the motor score in this multivariate framework, p=.012. Conclusion: We found that rFA values along the CST in the acute and subacute stages of ischemic stroke could help predict the outcome of motor impairment in stroke patients. These results will be useful in furthering our understanding of the motor recovery mechanisms in stroke and will facilitate the clinical decision making.