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Optimisation of magnetic resonance techniques for imaging the human brain at 4.7 Tesla

High magnetic field strengths (4.7 Tesla) promise improved MRI quality but also pose technical challenges. The research described here aims to optimise imaging techniques to generate artifact-free human brain images. Radio frequency (RF) B1 magnetic field homogeneity is worse at high field. Progress towards reducing the effect of the inhomogeneity at 4.7 T has been made in a novel spin-echo sequence using Hyperbolic Secant (HS) RF pulses. The properties of HS pulses when used for excitation and refocusing are investigated and exploited using simulations and experiments to yield a pulse sequence in which the HS pulse refocusing is B1-insensitive. This sequence has one less RF pulse than a similar commonly used technique and produces an improved slice profile compared with a previous sequence. High resolution diffusion-weighted imaging in reasonable scan times and without severe distortion proves challenging at high magnetic field strength. A volume-selective Stimulated Echo Acquisition Mode Echo-Planar Imaging sequence developed here shows potential for overcoming these challenges. The technique is shown to give similar diffusion coefficients to standard sequences in phantoms. It is designed for application in brain regions in which the higher resolution could allow nerve fibre tracts to be followed in greater detail. The construction of an anthropomorphic head phantom as a tool for comparing susceptibility artifact reduction techniques is described. The aim is for the phantom to accurately reproduce the magnetic environment of the brain and allow quantification of susceptibility-induced distortion and drop-out, which are worse at high field strength. The phantom is based on a water-filled plastic skull with realistic air spaces and wax to mimic soft tissues and has been used to evaluate a new technique that recovers signal in areas of drop-out in gradient-echo images. Magnetic field maps show that the field pattern in the phantom is similar to that in real brains.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:417112
Date January 2005
CreatorsShmueli, Karin
PublisherUniversity College London (University of London)
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://discovery.ucl.ac.uk/1446687/

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