Keywords: DWI/DTI/DKI, 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.
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