TY - JOUR
T1 - A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis
AU - Tur, Carmen
AU - Grussu, Francesco
AU - Prados, Ferran
AU - Charalambous, Thalis
AU - Collorone, Sara
AU - Kanber, Baris
AU - Cawley, Niamh
AU - Altmann, Daniel R.
AU - Ourselin, S. bastien
AU - Barkhof, Frederik
AU - Clayden, Jonathan D.
AU - Toosy, Ahmed T.
AU - Wheeler-Kingshott, Claudia A. M. Gandini
AU - Ciccarelli, Olga
PY - 2020/6/1
Y1 - 2020/6/1
N2 - 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.
AB - 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.
KW - Diffusion-weighted imaging
KW - clinically isolated syndrome
KW - multi-shell acquisitions
KW - multi-shell multi-tissue constrained spherical deconvolution
KW - multiple sclerosis
KW - tractography
UR - http://www.scopus.com/inward/record.url?scp=85066834917&partnerID=8YFLogxK
U2 - https://doi.org/10.1177/1352458519845105
DO - https://doi.org/10.1177/1352458519845105
M3 - Article
C2 - 31074686
SN - 1352-4585
VL - 26
SP - 774
EP - 785
JO - MULTIPLE SCLEROSIS JOURNAL
JF - MULTIPLE SCLEROSIS JOURNAL
IS - 7
ER -