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Title: Investigating the effects of high b-value and field strength on diffusion Magnetic Resonance Imaging
Author: Chung, A. W.
ISNI:       0000 0004 5363 1279
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2014
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Diffusion magnetic resonance imaging (MRI) allows the probing of tissue microstructure in the brain non-invasively. The standard method for quantitatively analysing microstructure is diffusion tensor imaging (DTI) with a typical b-value of 1000 s/mm2. However, high b-value imaging (b > 2000 s/mm2) can increase the contrast between tissue types. The disadvantage of high b is the detrimental effect of decreased signal-to-noise-ratio (SNR) on diffusion models. This work begins by investigating the efficacy of exploiting the fitting error of DTI at b = 3000 s/mm2 to provide further information of brain microstructure using bootstrapped principal eigenvectors, µ1. This study revealed binomial distributions of µ1 with potential to be exploited to provide further information of the underlying microstructure. Another factor affecting SNR in diffusion-weighted data is the magnetic field strength of the MRI scanner. Change in DTI measures with SNR by way of increasing b-value and at 1.5 versus 3 T was systematically assessed. Significant differences in DTI measures between field strengths were found suggesting careful comparison of DTI data when acquired at 1.5 and 3 T. The limitations of DTI in modelling the slow diffusion component (fitting between b = 2000 to 3000 s/mm2) were also demonstrated. Other algorithms exist for modelling diffusion profiles without the assumption of diffusion following a Gaussian distribution. One such method is the recently developed multi-compartment model NODDI (Neurite Orientation Dispersion and Density Imaging). The final aim of this work is to further understand how this technique behaves with change in magnetic field strength and its within-subject reproducibility in relation to DTI. This investigation found significant field strength effect on NODDI estimates as well as reasonable white matter diffusion measurements in multi-fibre regions where DTI fails. However, given the complexity of NODDI, greater within- subject variability was found in white matter compared to the simpler tensor model.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available