Mapping structural disconnection and morphometric similarity in Multiple Sclerosis: a longitudinal study

Abstract

Motivation: Multiple sclerosis can be modelled as a network disorder. Progressive demyelination and neurodegeneration lead to structural disconnection and disruption of the morphometric similarity between gray matter regions. Goal(s): To obtain measures of structural disconnection and morphometric similarity networks from conventional MRI sequences and test whether they are sensitive to disease status and clinical disability. Approach: 461 patients were imaged. Using publicly available software, we computed structural disconnection using white matter lesions masks and normative tractography atlases. Likewise, morphometric similarity was computed from standard FreeSurfer outputs. Results: Structural disconnection and morphometric similarity networks are sensitive to disease status and explain clinical disability. Impact: Measures of structural disconnection and morphometric similarity networks obtained from conventional MRI sequences are sensitive to multiple sclerosis and its related physical and cognitive disability. Our approach could represent a way to overcome the limitations of the standard network analyses.