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Title: Clinical applications of perfusion-weighted magnetic resonance imaging in neurological disorders
Author: Falah, Yasser
ISNI:       0000 0004 7971 4320
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2019
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The research presented in this thesis represents my passion for developing magnetic resonance imaging (MRI) techniques in neurological disorders. Arterial spin labeling (ASL), a non-contrast MRI method, is used as a tool to characterise different patients groups with the view to develop understanding of disease processes, confirm diagnosis, and monitor progression. In chapter two, 7 tesla (T) ASL MRI is used to measure cortical lesions perfusion in Multiple Sclerosis (MS) and compare that to local and global normal appearing grey matter. To our knowledge, this is the first study to date addressing this issue using 7T ASL. To assess the reproducibility of ASL and its reliability compared to the gold standard perfusion weighted MRI method, dynamic susceptibility contrast (DSC), the study detailed in chapter three was performed. This is the first longitudinal 7T ASL study to date in MS. Reversible cerebral vasoconstriction syndrome (RCVS) is a poorly understood condition; perfusion MRI can be a useful tool complementing anatomical and vascular scans. The study described in chapter four assessed a cohort of patients who presented with recurrent thunderclap headache suggestive of RCVS using 3T ASL to validate its clinical use. Chapter five summarises the projects I performed and highlights the aspects which need addressing before ASL can be used in clinical practice such as standardised protocols and automated imaging analysis. While 7T ASL offers invaluable opportunity to study cerebral perfusion in various neurological disorders, there are certain requirements and implications which researchers should be aware when planning studies. A multi-centre collaboration to develop ASL protocols and test their application in clinical setting is a great prospect for future work.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: WN Radiology. Diagnostic imaging