Description
Magnetic Resonance Imaging (MRI) is a map of the free protons in tissue. Protons bound to macromolecules are not visible on routine MRI due to their ultra-short T2 values. Magnetization transfer contrast (MTC) enables an indirect evaluation of the macromolecular content by selective saturation of bound protons. The simplest measure of MTC is the Magnetization Transfer Ratio (MTR) which is based on two sequences. Quantitative Magnetization transfer contrast (qMTC) requires acquisition of images at different settings of the bound proton saturation frequency and flip angle. Collagen is the primary macromolecule in muscle tissue, and collagen content in muscle increases with aging, sarcopenia, and in disease states such as muscular dystrophies. There are known gender differences in muscle structure and function including histological studies of differences in collagen content. A non-invasive marker of collagen fraction in muscle tissue has thus the potential to identify gender and aging differences and monitor disease progression or regression. While more accurate than MTR, qMTC is time intensive as the acquisitions sweep a range of MT RF pulse settings leading to a total scan time of 20-30 minutes. A method not been widely used is the Magnetization Transfer Saturation (MTsat) technique which derives an index of Magnetization Transfer. Unlike MTR, MTsat is independent of T1 relaxation times and transmit coil inhomogeneities. Computation of MTsat is relatively simple compared to qMTC. MTsat does not fit to a model, and therefore does not derive tissue parameters such as the macromolecular proton fraction, f. However, MTsat can still be a clinically useful quantity as a surrogate marker of f. Recent developments in compressed sensing based on random undersampling allow for significant reduction in scan times and have not been applied to MTsat. The focus of this thesis is to (i) optimize and establish MTsat mapping of calf muscle in healthy volunteers; (ii) identify and elucidate gender-related differences using MTsat, and (iii) perform simulations on full k-space data to identify the optimum schemes for MTsat using compressed sensing. These optimized schemes will be used in future studies to acquire qMT data with compressed sensing to establish a fast qMT protocol.
