Vibrational characteristics of brain magnetic resonance elastography

This thesis aims to investigate vibrational characteristics of magnetic resonance elastography (MRE) of the brain. MRE is a promising, non-invasive methodology for the mapping of shear stiffness of the brain. A mechanical actuator shakes the brain and generates shear waves, which are then imaged with a special MRI sequence sensitive to sub-millimeter displacements. This research focuses on exploring the profile of vibrations utilized in brain elastography from the standpoint of ultimately investigating nonlinear behavior of the tissue. The first objective seeks to demonstrate the effects of encoding off-frequency vibrations using standard MRE methodologies. Vibrations of this nature can arise from nonlinearities in the system and contaminate the results of the measurement. The second objective is to probe nonlinearity in the dynamic brain system using MRE. A non-parametric decomposition technique, novel to the MRE field, is introduced and investigated.

Using a voxel-based krogh cylinder array to simulate microvascular contrast enhancement

The goal of this study is to better simulate microscopic and voxel-based dynamic contrast enhancement in magnetic resonance imaging. Specifically, errors imposed by the traditional two-compartment model are reduced by introducing a novel Krogh cylinder network. The two-compartment model was developed for macroscopic pharmacokinetic analysis of dynamic contrast enhancement and generalizing it to voxel dimensions, due to the significant decrease in scale, imposes physiologically unrealistic assumptions. In the project, a system of microscopic exchange between plasma and extravascular-extracellular space is built while numerically simulating the local contrast agent flow between and inside image elements. To do this, tissue parameter maps were created, contrast agent was introduced to the tissue via a flow lattice, and various data sets were simulated. The effects of sources, tissue heterogeneity, and the contribution of individual tissue parameters to an image are modeled. Further, the study attempts to demonstrate the effects of a priori flow maps on image contrast, indicating that flow data is as important as permeability data when analyzing tumor contrast enhancement. In addition, the simulations indicate that it may be possible to obtain tumor-type diagnostic information by acquiring both flow and permeability data.