Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.729217
Title: Magnetic resonance imaging of cerebrovascular anatomy and physiology at 7 Tesla
Author: Viessmann, Olivia
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2017
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Abstract:
Magnetic Resonance Imaging (MRI) can study the cerebrovasculature non-invasively in humans. It can image the vascular anatomy, as well as functional attributes such as flow and perfusion. This multi-modal capability renders MRI one of the most favourable imaging techniques to study the cerebrovasculature in research and in clinical settings. The advent of human 7 Tesla (7T) MRI offers further benefits to existing methods. Most evidently, the higher signal-to-noise ratio (SNR) can be used to improve resolution. However concomitant changes in contrast mechanisms, an increase in the specific absorption rate (SAR) and transmit B1-field inhomogeneity need to be addressed when transitioning to higher field. Vessel wall imaging (VWI) is an exemplar application that benefits from higher resolution but is based on SAR intense methods. In the first part of this thesis the implementation of a VWI method, DANTE-SPACE, is described. The readout scheme was specifically optimised for high resolution wall depiction and enhanced suppression of cerebrospinal fluid to produce vessel wall contrast in the major intracranial arteries at 7T. Besides refining spatial scales, recent technical developments have accelerated information content in the temporal domain. In-slice acceleration and simultaneous excitation of multiple slices substantially reduced acquisition times for many applications. In particular, multiband techniques have pushed sampling speeds in functional MRI (fMRI) to sub-second regimes. Traditionally, fMRI is used to study low frequency neuro-vascular signals below 0.1Hz. Aliases of cardio-respiratory-induced signals have been regarded as "physiological noise". Sufficiently fast sampling resolves the spectrum beyond the cardiac frequency, thus transforming noise into valuable signal. In the second part of this thesis strategies to map and quantify signal fluctuations at the cardiac frequency are described using echo-planar imaging (EPI). Potential age-related difference in the cardiac EPI signal power were studied. Also, an investigation was made into the underlying MR-mechanisms that form these fluctuations by decomposing the EPI-signal over the cardiac cycle into S0 and T2* waveforms. Ultimately this research aims to foster the understanding of the vascular origins of cardiac-induced EPI signals. This will hopefully serve future research into how EPI data can be exploited to study cerebrovascular properties in healthy and diseased states.
Supervisor: Jezzard, Peter Sponsor: Marie Curie Actions of the European Commission
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.729217  DOI: Not available
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