April 5, 2019 — ICES Professor Michael Sacks’ research team has developed a new noninvasive technique for simulating repairs to the heart’s mitral valve with levels of accuracy reliable enough for use in a clinical setting.

Mitral valve (MV) disease is one of the most common valve-related heart conditions, newly diagnosed in five million Americans each year. Left unchecked, MV disease can lead to heart failure and/or stroke. This advance in computational modeling technology allows surgeons to provide patient-specific treatments, a development that will improve the long-term efficacy of current medical approaches.

Sacks, a professor of Biomedical Engineering at UT Austin, and his team outlined their computational modeling technique for imaging MV leaflets — flaps located on the base of the valve that open and close to regulate blood flow from the left atrium to left ventricle of the heart — in recent issues of the International Journal for Numerical Methods in Biomedical Engineering and the Annals of Biomedical Engineering.

The MV plays a crucial role in maintaining healthy blood flow in the heart, but normal function can be compromised in a number of ways. For instance, heart attacks may disrupt the MV leaflets’ capacity to close properly, resulting in blood leaking back into the heart’s left atrium. The importance of healthy MV function is thus widely understood within the medical community, but there is not a consensus on how best to treat common MV disorders such as regurgitation, prolapse and mitral valve stenosis.

Until now, there has been a lack of accurate modeling approaches available to surgeons for predicting the best surgical methods to restore MV function.

“Heart valves are very difficult to study. They are complex structures that move incredibly fast and are located inside the heart, making them extremely difficult to image,” said Sacks, who also serves as director of the James T. Willerson Center for Cardiovascular Modeling and Simulation in the university’s Oden Institute for Computational Engineering and Sciences. “Our new computational model provides surgeons with a tool for the prediction of post-surgical outcomes from clinically obtained pre-surgical data alone.”

Sacks has spent most of his academic career analyzing and modeling heart valve function. Recent advances in computational and 3D imaging technologies have made it possible for Sacks and his team to noninvasively and accurately acquire the in vivo (or living) geometry of the MV leaflets in patients from real-time 3D echocardiography — a clinical technique that uses sound waves to monitor heart function.

The UT team’s computational model was developed in collaboration with researchers from Penn Medicine and Georgia Tech.