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Fully automated detection of corticospinal tract damage in chronic stroke patients.

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE(2014)

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Abstract
Structural integrity of the corticospinal tract (CST) after stroke is closely linked to the degree of motor impairment. However, current methods for measurement of fractional atrophy (FA) of CST based on region of interest (ROI) are time-consuming and open to bias. Here, we used tract-based spatial statistics (TBSS) together with a CST template with healthy volunteers to quantify structural integrity of CST automatically. Two groups of patients after ischemic stroke were enrolled, group 1 (10 patients, 7 men, and Fugl-Meyer assessment (FMA) scores <= 50) and group 2 (12 patients, 12 men, and FMA scores = 100). CST of FA(ipsi), FA(contra), and FA(ratio) was compared between the two groups. Relative to group 2, FA was decreased in group 1 in the ipsilesional CST (P < 0.01), as well as the FA(ratio) (P < 0.01). There was no significant difference between the two subgroups in the contralesional CST (P = 0.23). Compared with contralesional CST, FA of ipsilesional CST decreased in group 1 (P < 0.01). These results suggest that the automated method used in our study could detect a surrogate biomarker to quantify the CST after stroke, which would facilitate implementation of clinical practice.
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Key words
magnetic resonance imaging,stroke,motor skills,diffusion tensor imaging,automation
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