Utilisation of novel magnetic resonance imaging features in the diagnosis and understanding of multiple sclerosis

There is no single test clinically available that is independently diagnostic for multiple sclerosis (MS). Currently MS is diagnosed using a combination of clinical evaluation and investigations including magnetic resonance imaging (MRI), interpreted in accordance with diagnostic criteria, to demonstrate the requisite dissemination of lesions in (anatomical) space and time. Lesions comprising inflammatory demyelination in the central nervous system are a core pathological feature of MS. Ultra-high field (e.g. 7 Tesla or 7T) T2*-weighted MRI can demonstrate in vivo a central vein in most of these lesions. This is a histopathologically specific feature which could be exploited to improve diagnostic workup in cases of suspected inflammatory demyelination. Central nervous system white matter not involved in demyelinating lesions is nevertheless affected in MS. The mechanisms inflicting injury to this normal appearing white matter (NAWM) and how they relate to focal lesions are unclear. Damage to NAWM seems important, because it correlates well with disability. Any association between cortical lesions, focal white matter lesions (WML) and diffuse damage to NAWM is difficult to investigate in vivo in MS, principally because MRI is relatively insensitive to cortical lesions. Investigation of such associations may also be confounded by the presence of small focal lesions within the “NAWM” that may remain undetected when using conventional MRI to define NAWM. Advantages inherent to ultra-high field MRI might help mitigate both of these problems.

Name dc:type.qualificationname

Doctor of Medicine (MD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2016

Author dc:creator

• Mistry, Niraj

Advisor dc:contributor.advisor

• Evangelou, Nikos

• Multiple Sclerosis
• Magnetic Resonance Imaging
• Diagnosis
• Sensitivity and Specificity

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/093aebe2-2874-4c5f-b73b-d48a0fcfefde/download
• https://www.rioxx.net/licenses/all-rights-reserved/
• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/f5ce25fb-62eb-419a-97e3-2859ffa35da6/download

Language dc:language

en

DOI dc:identifier.doi

https://doi.org/10.17863/CAM.6132

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/263001