UCLA

Current clinical magnetic resonance (MR) acquisitions primarily rely on qualitative or ‘weighted’ images and diagnosis is made by subjective assessment of regional signal intensity (hyperintense or hypointense). However, MR signal for the same material can vary due to different scanners and different protocols, which hinders objective evaluation of disease severity. In contrast, quantitative MRI provides objective information for tissue characterization, offering enhanced inter-session and inter-site reproducibility. It enables improved pathology detection and disease monitoring and has better sensitivity to mild or diffuse tissue alterations compared to qualitative imaging. The combination of multiple biomarkers provides more comprehensive information and shows great promise for risk assessment and early detection.Despite these advantages, the clinical application of multiparametric MRI has been limited due to the prolonged scan times for acquiring different biomarkers, motion artifacts, and misregistration between parametric maps. MR Multitasking presents a promising approach for motion-resolved, multi-parametric mapping. However, it has yet to exploit the multi-echo information (magnitude and phase) for T2*, susceptibility, and fat fraction mapping, which necessitates further technical development. This includes flow compensation for more accurate susceptibility mapping, achieving adequate temporal resolution for motion tracking, and improving imaging efficiency for multi-echo readouts. In addition, MR Multitasking demands further improvement in quantitative performance (precision and repeatability) and scan time for practical applications. The dissertation will be focused on technical developments of MR Multitasking to enable comprehensive tissue characterization and to improve quantitative performance. The first objective is to develop a technique for three-dimensional, whole-brain simultaneous T1, T2, T2*, and susceptibility mapping. The proposed method is evaluated on phantoms and human subjects. The second objective involves further technical development to achieve free-breathing, non-ECG, simultaneous myocardial T1, T2, T2*, and FF mapping in a 2.5-min scan. Lastly, a novel reconstruction approach is introduced to improve precision and repeatability and shorten scan time. The approach is evaluated with numerical simulations and healthy subjects. The dissertation represents a step toward motion-resolved, comprehensive tissue characterization within a clinically feasible scan time and without the need for extra physiological monitoring. It lays the groundwork for future clinical use of quantitative multiparametric MRI.