Electronic Thesis and Dissertation Repository


Doctor of Philosophy


Medical Biophysics


Drs. Jean Théberge and Rob Nicolson


The transverse relaxation time (T2) is a fundamental parameter of magnetic resonance imaging sensitive to tissue microstructure and water content, thus offering a non-invasive approach to evaluate abnormalities of brain tissue in-vivo. Prevailing hypotheses of two childhood psychiatric disorders were tested using quantitative T2 imaging and automated region of interest (ROI) analyses. In autism, the under-connectivity theory, which proposes aberrant connectivity within white matter (WM) was assessed, finding T2 to be eleveted in the frontal and parietal lobes, while dividing whole brain data into neurodevelopmentally relevant WM ROIs found increased T2 in bridging and radiate WM. In Tourette syndrome, tissue abnormalities of deep gray matter structures implicated in the symptomology of this disorder were evaluated and increased T2 of the caudate was found. Despite the sensitivity of quantitative T2 measurements to underlying pathophysiology, interpretation remain difficult. However, in WM, the compartmentalization of distinct water environments may lead to the detection of multi-exponential T2 decay. The metric of interest is principally the myelin water fraction (MWF), which is the proportion of the MRI signal arising from water trapped within layers of the myelin sheath. As a proof of concept study, the ability to measure the MWF based on T2* decay was evaluated and compared to a MWF measurements obtained from T2 decay. Data were analysed using both non-negative least squares and a two-pool model. Signal losses near sources of magnetic field inhomogeneity, such as the sinuses, rendered T2* components inseparable, invalidating this approach for whole brain MWF measurements. However, this study demonstrated the suitability of a two-pool model to calculate the MWF in WM. A novel approach, based on the multi-component gradient echo sampling of spin echoes (mcGESSE) and a two-pool model of WM, is proposed and its feasibility demonstrated using simulations. The in-vivo implementation of mcGESSE followed, with reproducibility of MWF measurements being assessed and the potential of an accelerated protocol using parallel imaging being investigated. While further work is needed to assess data quality, this approach shows great potential to obtain whole brain MWF data within a clinically relevant scan time.