Objective: To evaluate the association between outcomes, including affected extremity functions and activities of daily living (ADL), and fractional anisotropy (FA) derived from automated tractography incorporating age among patients after stroke. Methods: This study enrolled stroke patients, and diffusion-tensor imaging was conducted during the second week. Standardized automated tractography was utilized to compute FA values in the corticospinal tract (CST), the inferior fronto-occipital fasciculus (IFOF), and the superior longitudinal fasciculus (SLF). Outcome evaluations were performed at discharge from our affiliated rehabilitation facility. Extremity functions were assessed using the total scores of the motor component of the Stroke Impairment Assessment Set (SIAS-motor). Independence levels in ADL were appraised through the motor and cognition components of the Functional Independence Measure (FIM). For each outcome measure, multivariate regression analysis incorporated the FA values of the CST, the IFOF, and the SLF, along with age. Results: Forty-two patients were enrolled in the final analytical database. Among the four explanatory variables, the CST emerged as the most influential factor for SIAS-motor scores. Conversely, age proved to be the primary determinant for both the motor and cognition components of FIM, surpassing the impact of FA metrics, including the CST and the IFOF. Conclusion The key influencing factors exhibited significant variations based on the targeted outcome assessments. Clinicians should be aware of these differences when utilizing neuroimaging techniques to predict stroke outcomes.

Objective: To evaluate the association between outcomes, including affected extremity functions and activities of daily living (ADL), and fractional anisotropy (FA) derived from automated tractography incorporating age among patients after stroke. Methods: This study enrolled stroke patients, and diffusion-tensor imaging was conducted during the second week. Standardized automated tractography was utilized to compute FA values in the corticospinal tract (CST), the inferior fronto-occipital fasciculus (IFOF), and the superior longitudinal fasciculus (SLF). Outcome evaluations were performed at discharge from our affiliated rehabilitation facility. Extremity functions were assessed using the total scores of the motor component of the Stroke Impairment Assessment Set (SIAS-motor). Independence levels in ADL were appraised through the motor and cognition components of the Functional Independence Measure (FIM). For each outcome measure, multivariate regression analysis incorporated the FA values of the CST, the IFOF, and the SLF, along with age. Results: Forty-two patients were enrolled in the final analytical database. Among the four explanatory variables, the CST emerged as the most influential factor for SIAS-motor scores. Conversely, age proved to be the primary determinant for both the motor and cognition components of FIM, surpassing the impact of FA metrics, including the CST and the IFOF. Conclusion The key influencing factors exhibited significant variations based on the targeted outcome assessments. Clinicians should be aware of these differences when utilizing neuroimaging techniques to predict stroke outcomes.

Objective: To evaluate the association between outcomes, including affected extremity functions and activities of daily living (ADL), and fractional anisotropy (FA) derived from automated tractography incorporating age among patients after stroke. Methods: This study enrolled stroke patients, and diffusion-tensor imaging was conducted during the second week. Standardized automated tractography was utilized to compute FA values in the corticospinal tract (CST), the inferior fronto-occipital fasciculus (IFOF), and the superior longitudinal fasciculus (SLF). Outcome evaluations were performed at discharge from our affiliated rehabilitation facility. Extremity functions were assessed using the total scores of the motor component of the Stroke Impairment Assessment Set (SIAS-motor). Independence levels in ADL were appraised through the motor and cognition components of the Functional Independence Measure (FIM). For each outcome measure, multivariate regression analysis incorporated the FA values of the CST, the IFOF, and the SLF, along with age. Results: Forty-two patients were enrolled in the final analytical database. Among the four explanatory variables, the CST emerged as the most influential factor for SIAS-motor scores. Conversely, age proved to be the primary determinant for both the motor and cognition components of FIM, surpassing the impact of FA metrics, including the CST and the IFOF. Conclusion The key influencing factors exhibited significant variations based on the targeted outcome assessments. Clinicians should be aware of these differences when utilizing neuroimaging techniques to predict stroke outcomes.