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Investigating structural network disruption in multiple sclerosis

Charalambous, Thalis; (2018) Investigating structural network disruption in multiple sclerosis. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

Multiple sclerosis (MS) is an inflammatory, demyelinating and neurodegenerative disease of the central nervous system (CNS). Conventional whole brain magnetic resonance imaging (MRI) measures do not sufficiently explain disability in MS. Network science provides a powerful approach to study brain organizational principles and in combination with graph theory has revealed fundamental connectivity patterns in neurological conditions including MS. The overarching aim of this thesis is to investigate structural network disruption in MS evaluating the potential of brain networks analyses as novel biomarkers in MS pathology. The results of this thesis add to the current scientific knowledge. In particular, by applying an optimised structural network reconstruction pipeline we demonstrated that network metrics explain disability better in MS over and above conventional non- network metrics. In addition, in the absence of any longitudinal network studies, we developed a longitudinal network pipeline which we then applied to our longitudinal data. These findings demonstrated for the first time that baseline structural network metrics are predictors of future deep grey matter atrophy and increased lesion load. Finally, we applied a data-driven network decomposition approach detecting progressive weakening of connections that is linked to the severity of MS subtypes suggesting that these techniques are sensitive to pathology. The results presented here highlight the potential of network-based approaches as complementary methods for disease biomarkers to better predict disease course and monitor treatment effects. We believe that these findings may provide a framework for future studies with the aim to bridge the gap between imaging and symptomatology.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Investigating structural network disruption in multiple sclerosis
Event: UCL
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2018. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
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 Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
URI: https://discovery.ucl.ac.uk/id/eprint/10064039
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