Understanding the Effects of Diffusion and Relaxation in Magnetic Resonance Imaging using Computational Modeling

Abstract

The work described in this dissertation was motivated by a desire to better understand the cellular pathology of ischemic stroke. Two of the three bodies of research presented herein address and issue directly related to the investigation of ischemic stroke through the use of diffusion weighted magnetic resonance imaging (DWMRI) methods. The first topic concerns the development of a computationally efficient finite difference method, designed to evaluate the impact of microscopic tissue properties on the formation of DWMRI signal. For the second body of work, the effect of changing the intrinsic diffusion coefficient of a restricted sample on clinical DWMRI experiments is explored. The final body of work, while motivated by the desire to understand stroke, addresses the issue of acquiring large amounts of MRI data well suited for quantitative analysis in reduced scan time. In theory, the method could be used to generate quantitative parametric maps, including those depicting information gleaned through the use of DWMRI methods. Chapter 1 provides an introduction to several topics. A description of the use of DWMRI methods in the study of ischemic stroke is covered. An introduction to the fundamental physical principles at work in MRI is also provided. In this section the means by which magnetization is created in MRI experiments, how MRI signal is induced, as well as the influence of spin-spin and spin-lattice relaxation are discussed. Attention is also given to describing how MRI measurements can be sensitized to diffusion through the use of qualitative and quantitative descriptions of the process. Finally, the reader is given a brief introduction to the use of numerical methods for solving partial differential equations. In Chapters 2, 3 and 4, three related bodies of research are presented in terms of research papers. In Chapter 2, a novel computational method is described. The method reduces the computation resources required to simulate DWMRI experiments. In Chapter 3, a detailed study on how changes in the intrinsic intracellular diffusion coefficient may influence clinical DWMRI experiments is described. In Chapter 4, a novel, non-steady state quantitative MRI method is described.