Quantitative Magnetic Resonance Relaxometry and Diffusometry

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Magnetic resonance imaging (MRI) is well known as a flexible and powerful non-invasive diagnostic imaging technique available to clinical medicine. MRI as a largely qualitative tool is well established, principally used to visualize the internal structure of biological systems through mapping the spatial position of hydrogen. The magnetic resonance signal lifetimes (relaxation times) and molecular diffusion usually manifest qualitatively in the MR image contrast. Quantitative analysis of these parameters will reveal molecular scale information, since magnetic resonance is sensitive to a range of physical/chemical characteristics including molecular structure, motion, size and interactions, through the measurements of relaxation times (relaxometry) and molecular diffusion (diffusometry). The potential for quantitative MR has been recognized. However, significant methodological developments are still required for this potential to be fully realized. Our goal is to quantitatively map the relaxation and diffusion correlations with conventional MRI instruments, achieving a spatial resolution beyond the limits set by traditional methods, as well as quantitative analysis of tissue structure with spot measurements utilizing a low cost handheld MR scanner. We will exploit artificial neural network (deep learning) based data processing in both scenarios to overcome the challenges inherent in these measurements and to enable efficient recovery of underlying tissue quantity and property. Quantitative and robust relaxometry and diffusometry will empower magnetic resonance and bring it to a new level as an analytical methodology and significantly enlarge its capacity in disease detection and quantification. Because of the inter-disciplinary nature of the work, involving biology and computer science as well as physics, the research shows promise of significant relevance to practical problems in these and other fields. Collaboration with colleagues at the University of Windsor and elsewhere will enable these avenues to be explored.