Date of Award
Campus Access Thesis
Jennifer M C Vendemia
Voxel-based Lesion Symptom Mapping (VLSM) analysis was utilized to predict degree of motor impairment based on lesion location. Magnetic Resonance Imaging (MRI) was used to collect T1 weighted structural images of lesions in 11 participants who suffered primarily left hemisphere damage due to stroke. Assessments from the Lower Extremity Fugl-Meyer, Berg Balance Scale, Timed Up and Go, and walking speed were used as behavioral measures in the analysis. Behavioral measures were significantly correlated with lesion location, with lesions in the left superior temporal gyrus, post-central gyrus, and central fissure significantly predicting deficits in the motor scores in the Berg Balance Scale and Timed Up and Go measures. The Fugl-Meyer and walking speed assessment tests were not significantly correlated with injury. The behavioral measure values were in accordance with motor deficits expected after damage to motor systems, and areas of lesion overlap were consistent with systems involved in motor ability. In the future, VLSM may serve as a tool to medical physicians and researchers to provide a more accurate prognosis of motor recovery from stroke.
Reynolds, A. M.(2012). Voxel-Based Lesion Symptom Mapping as a Predictor of Motor Impairment after Stroke. (Master's thesis). Retrieved from https://scholarcommons.sc.edu/etd/1145