Identification of amyotrophic lateral sclerosis based on diffusion tensor imaging and support vector machine

White matter (WM) impairments have been well documented in amyotrophic lateral sclerosis (ALS). This study tested the potential of diffusion measurements in WM for identifying ALS based on the support vector machine (SVM). In the optimized SVM model, the FA values from the motor areas (including the bilateral precentral gyrus and the corticospinal tract) and extra-motor areas (including right postcentral gyrus, left superior/inferior longitudinal fasciculus) contributed mostly to classification. Our study suggests the feasibility of ALS diagnosis based on SVM analysis and diffusion measurements of WM. Future study with larger cohort is needed to validate the generality of our results.