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Title: Magnetic susceptibility-based white matter magnetic resonance imaging techniques
Author: Chen, Way Cherng
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2013
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Gradient echo (GRE) imaging, a magnetic resonance imaging (MRI) technique that is sensitive to changes in the magnetic susceptibility property of tissues, has recently revealed significant signal heterogeneity in white matter (WM) at high magnetic field B0 ≥ 3T. Various aspects of the underlying white matter microstructure have been linked to the observed contrast between white matter regions. This thesis investigates the origins of the observed differences in GRE signal behaviour. We proposed an explicit multi-compartmental model of WM that incorporates realistic representation of the geometry and magnetic susceptibility of the underlying microstructure that can be used to study the effects of WM microstructural changes on GRE signal characteristics. In particular, we looked at the apparent transverse relaxation rate (R2*) and the resonance frequency, as well as their respective deviations from mono-exponential decay and linear phase evolution. Next, we investigated the effect of WM fiber orientation on GRE signal using healthy human volunteers at 3T by correlating the GRE signal from different WM regions with WM fiber orientation information. Using literature-based parameters, we demonstrated that the geometric model predicted similar trends. Lastly, we studied the effect of myelin on GRE signal using a cuprizone mouse model at 7T . An ex vivo study was used to correlate GRE signal in fixed mouse brain with normalized myelin stain intensity. Simulated GRE signal from hypothetical scenarios of demyelination were then compared with the experimental results. R2* and resonance frequency were then used in an in vivo longitudinal study to track myelin changes during demyelination and subsequent remyelination.
Supervisor: Miller, Karla Sponsor: Agency for Science, Technology and Research (A*STAR)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Neuroscience ; Biophysics ; Medical Sciences ; white matter ; magnetic susceptibility ; geometric modeling