Gray matter network reorganization in multiple sclerosis from 7-Tesla and 3-Tesla MRI data

Objective: The objective of this study was to determine the ability of 7T-MRI for characterizing brain tissue integrity in early relapsing-remitting MS patients compared to conventional 3T-MRI and to investigate whether 7T-MRI improves the performance for detecting cortical gray matter neurodegeneration and its associated network reorganization dynamics. Methods: Seven early relapsing-remitting MS patients and seven healthy individuals received MRI at 7T and 3T, whereas 30 and 40 healthy controls underwent separate 3T- and 7T-MRI sessions, respectively. Surface-based cortical thickness (CT) and gray-to-white contrast (GWc) measures were used to model morphometric networks, analyzed with graph theory by means of modularity, clustering coefficient, path length, and small-worldness. Results: 7T-MRI had lower CT and higher GWc compared to 3T-MRI in MS. CT and GWc measures robustly differentiated MS from controls at 3T-MRI. 7T- and 3T-MRI showed high regional correspondence for CT (r = 0.72, P = 2e-78) and GWc (r = 0.83, P = 5.5e-121) in MS patients. MS CT and GWc morphometric networks at 7T-MRI showed higher modularity, clustering coefficient, and small-worldness than 3T, also compared to controls. Interpretation: 7T-MRI allows to more precisely quantify morphometric alterations across the cortical mantle and captures more sensitively MS-related network reorganization. Our findings open new avenues to design more accurate studies quantifying brain tissue loss and test treatment effects on tissue repair.