Diffusion tensor metrics in regions functionally activated in resting-state fMRI for a test cohort with multiple sclerosis

Motivation: The diagnosis of multiple sclerosis (MS) based on DTI and resting-state fMRI is currently not standardized. Goal(s): Investigation of DTI metrics differences in cerebellum, deep and superficial grey matter in the activation areas obtained from rs-fMRI analysis. Approach: Seed-based connectivity (SBC) analysis was from which activation area masks were obtained. DTI metrics and F-statistics were analyzed in these masks in native DTI space. Results: DTI metrics were significantly different for healthy controls and MS and very weakly correlated with F-statistics from SBC. Systematic error reduction by BSD method yielded large effect size for DTI metrics. Impact: The proposed approach showed potential for the use of DTI metrics in the assessment of the grey matter structure change due to MS specifically in rs-fMRI activation areas and for BSD to improve quantitative parametrization of MS.