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3T magnetic resonance imaging of cortical grey matter lesions in Multiple Sclerosis

Sethi, V; (2014) 3T magnetic resonance imaging of cortical grey matter lesions in Multiple Sclerosis. Doctoral thesis , UCL (University College London). Green open access

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Abstract

Radiological and histopathological studies have established that in addition to the classical white matter (WM) demyelinating lesions, cortical grey matter (CGM) lesions are also a significant part of the pathology in multiple sclerosis (MS), and contribute to the clinical and cognitive deficits seen in MS patients. Double inversion recovery (DIR) has been identified as a good sequence for the radiological detection of cortical grey matter lesions. In this project I investigated the role of phase sensitive inversion recovery (PSIR), a T1-weighted MRI sequence, using a 3T MRI scanner, for the detection of CGM lesions in multiple sclerosis. Detection of CGM lesions on a standard DIR sequence (1x1x3mm resolution) was compared with a higher resolution PSIR sequence (0.5x0.5x2mm), to explore if it can help improve the study of CGM lesions. A representative cohort, including patients with relapsing remitting (RR), primary progressive (PP) and secondary progressive (SP)MS, was recruited in this project, together with controls in order to allow a comparison of findings with those of healthy subjects who do not have MS. I systematically investigated if the use of high resolution PSIR scans can improve CGM lesion detection and classification, when compared to DIR. Using the PSIR sequence, I studied the hypothesis that the distribution of lesions impacts the pattern of cognitive impairment seen in patients. CGM lesion volumes were estimated for frontal, temporal , parietal and occipital lobes and cognitive tests were conducted (Hayling, Stroop, immediate and 4 delayed story and figure recall, PASAT (Paced auditory serial addition test) and SDMT (Symbol digit modality test)). Differences between phenotypes and associations with cognitive measures were explored using a multiple regression model. A follow up study was undertaken to understand how CGM lesions evolve with time and in order to explore potential specificity of PSIRdetected CGM lesions, I compared the findings of CGM lesion detection in MS patients, with patients diagnosed with Fabry’s disease. Compared with DIR, high resolution PSIR was found to detect a significantly greater number of CGM lesions and also improved the classification of CGM lesions. A fronto-temporal dominance of CGM lesions was noted in my study. Different CGM and JC lesion subtypes were found to be associated with cognitive function; the relationship being influenced by the lobar location and the cognitive function being assessed. In the follow-up study I found that people with SPMS have a grater accrual of CGM lesions than RRMS and the process appeared to be independent of WM lesion accrual. CGM lesions were also seen in patients with Fabry’s disease though the frequency was less that in MS. The data presented in my study suggests that PSIR has the potential to improve the quantitative and qualitative study of CGM lesions. CGM lesions were noted across all disease phenotypes, though more common in progressive disease. The distribution, accrual and evolution of CGM lesions provides insights into the pathogenesis of MS and helps understand the contribution of CGM lesions to neurological and cognitive impairment. Detection of CGM lesions has a potential role to help with a diagnosis of MS when it suspected but not confirmed.

Type: Thesis (Doctoral)
Title: 3T magnetic resonance imaging of cortical grey matter lesions in Multiple Sclerosis
Open access status: An open access version is available from UCL Discovery
Language: English
UCL classification: 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 Brain Sciences
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/1458360
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