Fisniku, L.K.;
(2011)
Magnetic resonance imaging markers of long term disability in relapse-onset multiple sclerosis patients.
Doctoral thesis , UCL (University College London).
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Abstract
The aim of this thesis is to assess the ever challenging role of MRI in predicting disability in relapse-onset Multiple Sclerosis (MS) patients. It consists of four parts. In part one a brief overview of MS is given, looking at the most up-to-date knowledge on aetiology, pathogenesis, most common clinical presentations and the evolution in diagnostic process, prognosis and ever increasing treatment options for MS patients. Then, a brief review of the basic physics concepts and the techniques used to assess disability in MS is given using both conventional and non-conventional MRI. In part two, the relationship of T2 white matter lesion volume (T2WMLV) with long-term disability is assessed in a unique cohort of MS patients seen from the disease onset with a clinically isolated syndrome and followed up with clinical and MRI data every 5 years up to 20 years. In part three, using cross-sectional data from the same cohort of patients, the role of tissue specific i.e. grey matter and white matter changes in predicting disability at 20 years is assessed, using both atrophy measurements and magnetisation transfer ratio. Comparisons between sub-group of MS patients and controls are also assessed. Furthermore, the relationship of longitudinal T2WMLV changes with atrophy measurements at 20 years is also explored. In the fourth and final part of this thesis, a summary of the main findings of this work is given and there is discussion on what the future holds for the role of imaging in predicting disability in MS.
Type: | Thesis (Doctoral) |
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Title: | Magnetic resonance imaging markers of long term disability in relapse-onset multiple sclerosis patients |
Open access status: | An open access version is available from UCL Discovery |
Language: | English |
UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
URI: | https://discovery.ucl.ac.uk/id/eprint/1335724 |
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