Quantification of Multi-Compartment T1 Relaxation and Magnetization Transfer in Biological Tissue: From Biophysics to Biomarkers for Multiple Sclerosis - Project Summary The overarching goal of this project is to improve the reproducibility of quantitative MRI (qMRI). Secondary goals are to enhance its sensitivity and specificity, and to enable its utilization in clinical routine imaging by reducing the scan time. Successful completion of this project will help towards the fulfillment of qMRI's promise to objectify the radiologists' analysis and to improve the comparability of different scans, which is much needed in the age of large multi-center studies, artificial intelligence, and precision medicine. It is well-known that estimates of spin relaxation times for biological tissue vary substantially throughout the literature, in particular if different pulse sequences are used for their measurement. Our central hypothesis is that this variability is a result of model oversimplifications, as un-modeled effects bias the parameter estimates and this bias depends on the sequence. Simple models are commonly chosen for in vivo qMRI to keep the scan time clinically feasible. This project aims to overcome this variability by removing the most severe model oversimplifications, and we will enable an efficient encoding of the more complex model with the hybrid state, a spin-ensemble state whose discovery we recently reported in Nature Communications Physics. Our preliminary data suggests that the hybrid state allows us to disentangle different T1-relaxation paths, on a voxel-by-voxel basis and within a clinically feasible scan time, and we find that magnetization transfer plays a dominant role in T1-relaxation in brain white matter. The three specific aims concern the physics, bio-medical, and the engineering aspects of the project and will jointly establish the proposed model and hybrid-state pulse sequence for robust and fast quantitative MRI. We aim to provide an improved understanding of multi-component T1-relaxation in biological tissue and the clinical implications thereof, as well as to develop tools for quantifying the developed biomarkers in a clinical imaging setting. While this work is relevant to the entire field of biomedical MR, the project focuses on neuroimaging, where the relevant biophysics in best understood; and we will use multiple sclerosis as a test-vehicle for our model and pulse sequence, as the bio-medical interpretation of the physical parameters is well understood.
