Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2026
Motor tract integrity in gait pattern clusters of patients with chronic Stroke: A diffusion tensor imaging and motion capture study.
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Kim Jinuk, Kim Eunmi, Lee Su-Hyun, Lee Jungsoo, Kim Yun-Hee
Аннотация
OBJECTIVE: This study aimed to identify distinct gait pattern clusters among patients with chronic stroke and investigate motor tract integrity differences across these clusters.
METHODS: Sixty-nine chronic stroke patients with hemiparesis who could walk independently underwent gait analysis using a motion capture system and diffusion tensor imaging. K-means clustering was performed using 26 gait parameters on the affected side. Fractional anisotropy (FA) values were extracted for corticospinal tract subregions and motor subtracts. Kruskal-Wallis tests assessed FA differences between clusters, and multinomial logistic regression identified key motor tract predictors.
RESULTS: K-means clustering identified four gait clusters with significant differences in gait speed. FA analysis revealed reduced ipsilesional posterior limb of the internal capsule, cerebral peduncle, and pyramidal integrity in the most impaired clusters. Notable FA differences were observed in ipsilesional leg motor cortex (M1) and somatosensory cortex (S1) and contralesional premotor cortex (PMV, PMD) tracts. Bilateral leg M1, contralesional PMV, S1, and supplementary motor area (SMA) FA were key predictors of cluster differentiation.
CONCLUSIONS: Distinct gait clusters corresponded to motor tract integrity differences, underscoring the potential for targeted rehabilitation strategies based on motor tract profiles.
SIGNIFICANCE: This study highlights the neural mechanisms of gait dysfunction in chronic stroke, emphasizing the role of contralesional pathways in compensation.
METHODS: Sixty-nine chronic stroke patients with hemiparesis who could walk independently underwent gait analysis using a motion capture system and diffusion tensor imaging. K-means clustering was performed using 26 gait parameters on the affected side. Fractional anisotropy (FA) values were extracted for corticospinal tract subregions and motor subtracts. Kruskal-Wallis tests assessed FA differences between clusters, and multinomial logistic regression identified key motor tract predictors.
RESULTS: K-means clustering identified four gait clusters with significant differences in gait speed. FA analysis revealed reduced ipsilesional posterior limb of the internal capsule, cerebral peduncle, and pyramidal integrity in the most impaired clusters. Notable FA differences were observed in ipsilesional leg motor cortex (M1) and somatosensory cortex (S1) and contralesional premotor cortex (PMV, PMD) tracts. Bilateral leg M1, contralesional PMV, S1, and supplementary motor area (SMA) FA were key predictors of cluster differentiation.
CONCLUSIONS: Distinct gait clusters corresponded to motor tract integrity differences, underscoring the potential for targeted rehabilitation strategies based on motor tract profiles.
SIGNIFICANCE: This study highlights the neural mechanisms of gait dysfunction in chronic stroke, emphasizing the role of contralesional pathways in compensation.