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Motor network efficiency and disability in multiple sclerosis

Pardini, M., Yaldizli, O., Sethi, V., Muhlert, Nils, Liu, Z., Samson, R. S., Altmann, D. R., Ron, M. A., Wheeler-Kingshott, C. A. M., Miller, D. H. and Chard, D. T. 2015. Motor network efficiency and disability in multiple sclerosis. Neurology 85 (13) , pp. 1115-1122. 10.1212/WNL.0000000000001970

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Objective: To develop a composite MRI-based measure of motor network integrity, and determine if it explains disability better than conventional MRI measures in patients with multiple sclerosis (MS). Methods: Tract density imaging and constrained spherical deconvolution tractography were used to identify motor network connections in 22 controls. Fractional anisotropy (FA), magnetization transfer ratio (MTR), and normalized volume were computed in each tract in 71 people with relapse onset MS. Principal component analysis was used to distill the FA, MTR, and tract volume data into a single metric for each tract, which in turn was used to compute a composite measure of motor network efficiency (composite NE) using graph theory. Associations were investigated between the Expanded Disability Status Scale (EDSS) and the following MRI measures: composite motor NE, NE calculated using FA alone, FA averaged in the combined motor network tracts, brain T2 lesion volume, brain parenchymal fraction, normal-appearing white matter MTR, and cervical cord cross-sectional area. Results: In univariable analysis, composite motor NE explained 58% of the variation in EDSS in the whole MS group, more than twice that of the other MRI measures investigated. In a multivariable regression model, only composite NE and disease duration were independently associated with EDSS. Conclusions: A composite MRI measure of motor NE was able to predict disability substantially better than conventional non-network-based MRI measures.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Cardiff University Brain Research Imaging Centre (CUBRIC)
Subjects: R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Publisher: American Academy of Neurology
ISSN: 0028-3878
Date of First Compliant Deposit: 18 November 2019
Date of Acceptance: 23 April 2015
Last Modified: 18 Nov 2019 14:30

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