In multiple sclerosis, the correlation between clinical scores and classical radiological metrics is poor (“clinico-radiological paradox”). To improve the prediction of future disease course, we suggest to study structural brain disconnectivity resulting from white matter lesions. We proposed an atlas-based approach to quantify structural disconnectomes without diffusion imaging, as it is typically not part of clinical routine MR protocols for multiple sclerosis. The disconnectome was modelled as a graph where brain regions are vertices and affected connections edges. Our method provides a new representation of brain disconnectivity that enables to stratify multiple sclerosis patients in two groups with different prognosis.