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Title: Arterial spin labelling magnetic resonance imaging of the brain : techniques and development
Author: Wells, J. A.
ISNI:       0000 0004 2727 7974
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2010
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This thesis centres on the development of arterial spin labelling (ASL) MRI, a non-invasive technique to image cerebral perfusion. In the first chapter I explain the principles of cerebral blood flow (CBF) quantification using ASL beginning with the original implementation through to the most recent advances. I proceed to describe the established theory behind the key additional MRI contrast mechanisms and techniques that underpin the novel experiments described in this thesis (T2 and T1 relaxation, diffusion imaging and half-Fourier acquisition and reconstruction). In Chapter 2 I describe work undertaken to sample the transverse relaxation of the ASL perfusion-weighted and control images acquired with and without vascular crusher gradients at a range of post-labelling delay times and tagging durations, to estimate the intra-vascular, intra-cellular and extra-cellular distribution of labelled water in the rat cortex. The results provide evidence for rapid exchange of labelled water into the intra-cellular space relative to the transit-time through the vascular bed, and provide a more solid foundation for CBF quantification using ASL techniques. In Chapter 3 the performance of image de-noising techniques for reducing errors in ASL CBF and arterial transit time estimates is investigated. I show that noise reduction methods can suppress random and systematic errors, improving both the precision and accuracy of CBF measurements and the precision of transit time maps. In Chapter 4 I present the first in-vivo demonstration of Hadamard-encoded continuous ASL (H-CASL); an efficient method of imaging small volumes of labelled blood water in the brain at multiple post labelling delay times. I present evidence that H-CASL is viable for in-vivo application and can improve the precision of δa estimation in 2/3 of the imaging time required for standard multi post labelling delay continuous ASL.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available