Huber, E;
Patel, R;
Hupp, M;
Weiskopf, N;
Chakravarty, MM;
Freund, P;
(2020)
Extrapyramidal plasticity predicts recovery after spinal cord injury.
Scientific Reports
, 10
(1)
, Article 14102. 10.1038/s41598-020-70805-5.
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Abstract
Spinal cord injury (SCI) leads to wide-spread neurodegeneration across the neuroaxis. We explored trajectories of surface morphology, demyelination and iron concentration within the basal ganglia-thalamic circuit over 2 years post-SCI. This allowed us to explore the predictive value of neuroimaging biomarkers and determine their suitability as surrogate markers for interventional trials. Changes in markers of surface morphology, myelin and iron concentration of the basal ganglia and thalamus were estimated from 182 MRI datasets acquired in 17 SCI patients and 21 healthy controls at baseline (1-month post injury for patients), after 3, 6, 12, and 24 months. Using regression models, we investigated group difference in linear and non-linear trajectories of these markers. Baseline quantitative MRI parameters were used to predict 24-month clinical outcome. Surface area contracted in the motor (i.e. lower extremity) and pulvinar thalamus, and striatum; and expanded in the motor thalamus and striatum in patients compared to controls over 2-years. In parallel, myelin-sensitive markers decreased in the thalamus, striatum, and globus pallidus, while iron-sensitive markers decreased within the left caudate. Baseline surface area expansions within the striatum (i.e. motor caudate) predicted better lower extremity motor score at 2-years. Extensive extrapyramidal neurodegenerative and reorganizational changes across the basal ganglia-thalamic circuitry occur early after SCI and progress over time; their magnitude being predictive of functional recovery. These results demonstrate a potential role of extrapyramidal plasticity during functional recovery after SCI.
| Type: | Article |
|---|---|
| Title: | Extrapyramidal plasticity predicts recovery after spinal cord injury |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41598-020-70805-5 |
| Publisher version: | https://doi.org/10.1038/s41598-020-70805-5 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Biophysical models, Spinal cord diseases |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10124130 |
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