Abstract 72: A Novel VLSM-CST Lesion Load Model is a Superior Predictor of Motor Outcomes of Acute Stroke Patients

• DOI: 10.1161/str.47.suppl_1.72
• Publication Date: 2021-07-03T12:32:07Z
• Authors: Jasmine Wang; Wayne Feng; Pratik Y Chhatbar; Gottfried Schlaug
• Keywords: Corticospinal tract; Stroke Recovery; Stroke; Akaike information criterion

Introduction: Lesion load of the Corticospinal Tract (CST-LL) can predict 64% variance in 3-months outcome acute stroke patients. Voxel-based lesion symptom mapping (VLSM) studies have revealed brain voxels associated with motor impairment. A combined VLSM- CST-LL approach may give particular weight to that are both part an impairment map and descending tracts. Hypothesis: VLSM-wCST-LL model better than weighted alone. Methods: We derived VLSM from a group 50 chronic patients variable deficits relating patients’ lesions Upper Extremity Fugl-Meyer (UE-FM) scores. correction for multiple comparisons was applied at FDR<0.05. Resulting T-maps were multiplied using our probabilistic CST maps, then summed form canonical VLSM-weighted tract. Individual maps 76 overlaid onto calculate load. Patients assessed baseline 3 months. Linear regressions fit UE-FM, wCST-LL, Days-of-Therapy (DoT) determine predictions outcome. multivariate regression run VSLM-weighted CST-LL, controlling UE-FM DoT. Age not significant regressor. Akaike Information Criterion select best model. Results: The analysis determined precentral gyrus, premotor regions, corona radiata region, within tracts significantly related VLSM-CST-LL predicted 85% months AIC results confirmed 99% certainty is Conclusions: superior compared predicting