Jenkins, T., Alix, J. orcid.org/0000-0001-8391-9749, David, C. et al. (10 more authors) (2018) Imaging muscle as a potential biomarker of denervation in motor neuron disease. Journal of Neurology, Neurosurgery and Psychiatry, 89. pp. 248-255. ISSN 0022-3050
Abstract
Objective To assess clinical, electrophysiological and whole-body muscle MRI measurements of progression in patients with motor neuron disease (MND), as tools for future clinical trials, and to probe pathophysiological mechanisms in vivo. Methods A prospective longitudinal observational clinico-electrophysiological and radiological cohort study was performed. Twenty-nine MND patients and 22 age and gender-matched healthy controls were assessed with clinical measures, electrophysiological motor unit number index (MUNIX) and T2-weighted whole-body muscle MRI, at first clinic presentation and four months later. Between-group differences and associations were assessed using age and gender-adjusted multivariable regression models. Within-subject longitudinal changes were assessed using paired t-tests. Patterns of disease spread were modelled using mixed-effects multivariable regression, assessing associations between muscle relative T2 signal and anatomical adjacency to site of clinical onset. Results MND patients had 30% higher relative T2 muscle signal than controls at baseline (all-regions mean, 95%CI 15%, 45%, p<0.001). Higher T2 signal was associated with greater overall disability (coefficient -0.009, 95%CI -0.017, -0.001, p=0.023), and with clinical weakness and lower MUNIX in multiple individual muscles. Relative T2 signal in bilateral tibialis anterior increased over four months in MND patients (right: 10.2%, 95%CI 2.0%, 18.4%, p=0.017; left: 14.1%, 95%CI 3.4%, 24.9%, p=0.013). Anatomically contiguous disease spread on MRI was not apparent in this model. Conclusions Whole-body muscle MRI offers a new approach to objective assessment of denervation over short timescales in MND, and enables investigation of patterns of disease spread in vivo. Muscles inaccessible to conventional clinical and electrophysiological assessment may be investigated using this methodology.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Infection, Immunity and Cardiovascular Disease The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Neuroscience (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield) The University of Sheffield > Sheffield Teaching Hospitals |
Funding Information: | Funder Grant number NATIONAL INSTITUTE FOR HEALTH RESEARCH IS-BRC-1215-20017 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Oct 2017 13:15 |
Last Modified: | 30 Oct 2018 11:27 |
Published Version: | https://doi.org/10.1136/jnnp-2017-316744 |
Status: | Published |
Publisher: | BMJ Publishing Group |
Refereed: | Yes |
Identification Number: | 10.1136/jnnp-2017-316744 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:122499 |