A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis - Tur, Carmen; Grussu, Francesco; Prados, Ferran; Charalambous, Thalis; Collorone, Sara; Kanber, Baris; Cawley, Niamh; Altmann, Daniel R; Ourselin, Sébastien; Barkhof, Frederik; Clayden, Jonathan D; Toosy, Ahmed T; et al. (Multiple sclerosis, 2020)
The potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple sclerosis (MS) has scarcely been investigated. To test, in patients with a clinically isolated syndrome (CIS), whether multi-shell imaging-derived connectivity metrics can differentiate patients from controls, correlate with clinical measures, and perform better than metrics obtained with conventional single-shell protocols. Nineteen patients within 3 months from the CIS and 12 healthy controls underwent anatomical and 53-direction multi-shell diffusion-weighted 3T images. Patients were cognitively assessed. Voxel-wise fibre orientation distribution functions were estimated and used to obtain network metrics. These were also calculated using a conventional single-shell diffusion protocol. Through linear regression, we obtained effect sizes and standardised regression coefficients. Patients had lower mean nodal strength ( = 0.003) and greater network modularity than controls ( = 0.045). Greater modularity was associated with worse cognitive performance in patients, even after accounting for lesion load ( = 0.002). Multi-shell-derived metrics outperformed single-shell-derived ones. Connectivity-based nodal strength and network modularity are abnormal in the CIS. Furthermore, the increased network modularity observed in patients, indicating microstructural damage, is clinically relevant. Connectivity analyses based on multi-shell imaging can detect potentially relevant network changes in early MS.