Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls.

Introduction: This study investigates whether a multi-shell diffusion tensor imaging (DTI) protocol and its subsets can reliably distinguish healthy controls (HC) from patients with multiple sclerosis (MS) presenting with low Expanded Disability Status Scale (EDSS) scores and mild MRI findings. Methods: To enhance accuracy, spatial systematic errors in diffusion measurements were corrected using the B-matrix Spatial Distribution method (BSD-DTI). We examined the discriminative potential of fractional anisotropy (FA) and mean diffusivity (MD) across three broad brain regions: whole brain (WB), white matter (WM), and gray matter (GM), using both the full protocol and its subsets. Additionally, we employed a more detailed classification strategy based on segmentation into 95 regions of interest (ROIs), analyzing FA, MD, axial diffusivity (AD), and radial diffusivity (RD) under a stringent statistical criterion. Results: While the protocol and each subset showed a comparable ability to differentiate between HC and MS groups, substantial variability in metric values across protocols highlights the limited utility of directly comparing DTI metrics between acquisition schemes. Discussion: The results emphasize the importance of accounting for spatial systematic errors when selecting optimal protocols for clinical and research applications.