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

Carmen Tur, Francesco Grussu, Ferran Prados, Thalis Charalambous, Sara Collorone, Baris Kanber, Niamh Cawley, Daniel R. Altmann, S. bastien Ourselin, Frederik Barkhof, Jonathan D. Clayden, Ahmed T. Toosy, Claudia A. M. Gandini Wheeler-Kingshott, Olga Ciccarelli

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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.
Original languageEnglish
JournalMultiple Sclerosis Journal
DOIs
Publication statusPublished - 2019

Cite this

Tur, C., Grussu, F., Prados, F., Charalambous, T., Collorone, S., Kanber, B., ... Ciccarelli, O. (2019). A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis. Multiple Sclerosis Journal. https://doi.org/10.1177/1352458519845105
Tur, Carmen ; Grussu, Francesco ; Prados, Ferran ; Charalambous, Thalis ; Collorone, Sara ; Kanber, Baris ; Cawley, Niamh ; Altmann, Daniel R. ; Ourselin, S. bastien ; Barkhof, Frederik ; Clayden, Jonathan D. ; Toosy, Ahmed T. ; Wheeler-Kingshott, Claudia A. M. Gandini ; Ciccarelli, Olga. / A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis. In: Multiple Sclerosis Journal. 2019.
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title = "A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis",
abstract = "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.",
author = "Carmen Tur and Francesco Grussu and Ferran Prados and Thalis Charalambous and Sara Collorone and Baris Kanber and Niamh Cawley and Altmann, {Daniel R.} and Ourselin, {S. bastien} and Frederik Barkhof and Clayden, {Jonathan D.} and Toosy, {Ahmed T.} and Wheeler-Kingshott, {Claudia A. M. Gandini} and Olga Ciccarelli",
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language = "English",
journal = "Multiple Sclerosis",
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Tur, C, Grussu, F, Prados, F, Charalambous, T, Collorone, S, Kanber, B, Cawley, N, Altmann, DR, Ourselin, SB, Barkhof, F, Clayden, JD, Toosy, AT, Wheeler-Kingshott, CAMG & Ciccarelli, O 2019, 'A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis' Multiple Sclerosis Journal. https://doi.org/10.1177/1352458519845105

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, S. bastien; Barkhof, Frederik; Clayden, Jonathan D.; Toosy, Ahmed T.; Wheeler-Kingshott, Claudia A. M. Gandini; Ciccarelli, Olga.

In: Multiple Sclerosis Journal, 2019.

Research output: Contribution to journalArticleAcademicpeer-review

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 - 2019

Y1 - 2019

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.

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UR - https://www.ncbi.nlm.nih.gov/pubmed/31074686

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