Arterial Spin Labeling (ASL) is a Magnetic Resonance Imaging (MRI) technique that is able to non-invasively quantify the rate of delivery of arterial blood to tissue, known as perfusion. In this thesis a method that uses Velocity Selective (VS) preparations to generate contrast between blood and tissue spins is investigated. The systematic errors associated with performing a VSASL experiment on imperfect hardware is first investigated. It is shown through simulations and experiments that some VS preparations will underestimate perfusion due to static and transmit magnetic field errors, and that eddy currents caused by switching of magnetic gradients lead to an overestimation of perfusion with VSASL by up to a factor 2. A novel VS preparation, BIR-8, is presented which is shown to be the most robust to these imperfections. The BIR-8 VSASL technique is then applied in brain tumours where it is found that significant VSASL signal can be detected in less than 5 minutes. However, in a comparison with a spatially selective ASL technique it is found that VSASL overestimates perfusion in these tumours, despite agreeing in Grey Matter. The systematic errors due to physiology are then modelled, and it is shown that both diffusion and bulk motion will systematically bias the VSASL measurement. A diffusion insensitive VSASL technique, VS-TILT, is then developed and it is found that a significant proportion of the VSASL signal originates from diffusion effects. Theoretical models for the shape of the bolus in vascular networks are also derived, and it is shown that an isotropic network of laminar vessels produces the most efficient saturation, but saturation is also achieved with plug flow. The diffusion insensitive VS preparation is then applied in an attempt to isolate the venous compartment in order to measure Oxygen Extraction Fraction. A kinetic model is derived in order to optimise the acquisition. However, it is found that accurate measurements of OEF would not be produced by this sequence in a clinically realistic time.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:627823 |
Date | January 2014 |
Creators | Meakin, James A. |
Contributors | Jezzard, Peter |
Publisher | University of Oxford |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://ora.ox.ac.uk/objects/uuid:a4247c64-d113-42e6-beee-5795e78a4cdc |
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