Noninvasive measurement of oxygenation using quantitative susceptibility mapping (supplement)

PROJECT SUMMARY/ABSTRACT The goal of this research is to develop and validate cardiac quantitative susceptibility mapping (QSM) for the assessment of mitral annular calcification severity, towards the long-term objective of improving prediction of therapeutic response, therapeutic decision-making and clinical outcomes for patients with mitral valve prolapse

(MVP). MVP occurs in over 7 million individuals in the United States and over 170 million worldwide. It is a leading cause of degenerative mitral regurgitation (DMR) which represents the most frequent form of mitral regurgitation (MR) requiring surgery. Percutaneous (mitral valve clip placement) or surgical (mitral valve repair)

treatment can reduce MR, thus avoiding harmful untreated regurgitation or mitral valve replacement (MVR). However, MR recurs in 10-30% of patients, which impacts prognosis and increases risk for congestive heart failure and death. It is therefore critical to have early predictors of therapeutic success to optimize treatments

and improve outcomes for patients with MVP. Mitral annular calcium (MAC) is one such key predictor of response to surgical and percutaneous repair in patients with MVP. MAC is known to decrease surgical treatment success and to increase morbidity and mortality. MAC is currently diagnosed using ultrasound (echo), which lacks

quantitation, or CT, which exposes the patient to ionizing radiation and is not capable of measuring other predictors such as fibrosis or directly assessing MR itself. Cardiac MRI (CMRI) can measures these predictors but is currently incapable of quantifying MAC – thus limiting the utility of this powerful modality for assessment

of physiologic determinants of MR and its response to therapy. Nevertheless, calcification has a strong effect on the MR signal due to its strong diamagnetic susceptibility, which significantly modifies the magnetic at and round the MAC. While severe MAC can be qualitatively detected using the resulting low magnitude signal, it is less

sensitive at mild or moderate MAC levels and is not quantitative. QSM – an MRI technique pioneered by our group – is able to directly measure susceptibility and thus calcium content. We have obtained encouraging preliminary data showing the feasibility of using cardiac QSM to detect MAC and have shown preliminary

validation of this method against cardiac CT reference. In this proposal, we propose to develop cardiac QSM acquisition and processing methods and perform its validation among a cohort of MVP patients through the following Specific Aims. (1) We will compare conventional to accelerated QSM for quantification of MAC among

patients with MVP undergoing percutaneous or surgical repair. (2) We will develop and validate a fully automated machine learning algorithm to quantify MAC. (3) We will test whether QSM independently predicts therapeutic response to mitral valve repair. The expected outcome of this research is a non-invasive MRI based method to

measure mitral annulus calcification severity, which is a key predictor of success of percutaneous or surgical treatment for mitral valve prolapse. Cardiac QSM holds broad significance towards the goal of therapeutic optimization for valvular disease.