Symmetry differences of structural connectivity in multiple sclerosis and healthy state

Abstract

Focal and diffuse cerebral damages occur in Multiple Sclerosis (MS) that promotes profound shifts in local and global structural connectivity parameters, mainly derived from diffusion tensor imaging. Most of the reconstruction analyses have applied conventional tracking algorithms largely based on the controversial streamline count. For a more credible explanation of the diffusion MRI signal, we used convex optimization modeling for the microstructure-informed tractography2 (COMMIT2) framework. All multi-shell diffusion data from 40 healthy controls (HCs) and 40 relapsing-remitting MS (RRMS) patients were transformed into COMMIT2-weighted matrices based on the Schefer-200 parcels atlas (7 networks) and 14 bilateral subcortical regions. The success of the classification process between MS and healthy state was efficiently predicted by the left DMN-related structures and visual network-associated pathways. Additionally, the lesion volume and age of onset were remarkably correlated with the components of the left DMN. Using complementary approaches such as global metrics revealed differences in WM microstructural integrity between MS and HCs (efficiency, strength). Our findings demonstrated that the cutting-edge diffusion MRI biomarkers could hold the potential for interpreting brain abnormalities in a more distinctive way.