A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis

Autor: Niamh Cawley, Ferran Prados, Olga Ciccarelli, Jonathan D. Clayden, Carmen Tur, Daniel R. Altmann, Francesco Grussu, Frederik Barkhof, Thalis Charalambous, Baris Kanber, Sebastien Ourselin, Sara Collorone, Ahmed T. Toosy, Claudia Am Gandini Wheeler-Kingshott
Přispěvatelé: Radiology and nuclear medicine, Amsterdam Neuroscience - Neuroinfection & -inflammation
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Mult Scler
Tur, C, Grussu, F, Prados, F, Charalambous, T, Collorone, S, Kanber, B, Cawley, N, Altmann, D R, Ourselin, S B, Barkhof, F, Clayden, J D, Toosy, A T, Wheeler-Kingshott, C A M G & Ciccarelli, O 2020, ' A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis ', Multiple Sclerosis Journal, vol. 26, no. 7, pp. 774-785 . https://doi.org/10.1177/1352458519845105
Multiple Sclerosis Journal, 26(7), 774-785. SAGE Publications Ltd
Multiple Sclerosis Journal
ISSN: 1352-4585
Popis: Background: 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. Objective: 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. Methods: 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. Results: Patients had lower mean nodal strength ( p = 0.003) and greater network modularity than controls ( p = 0.045). Greater modularity was associated with worse cognitive performance in patients, even after accounting for lesion load ( p = 0.002). Multi-shell-derived metrics outperformed single-shell-derived ones. Conclusion: 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.
Databáze: OpenAIRE