Person:

Hammer, Peter

Heart valves are functionally complex, making surgical repair difficult. Simulation-based surgical planning could facilitate repair, but current finite element studies are prohibitively slow for rapid, clinically-oriented simulations. An anisotropic, nonlinear mass-spring (M-S) model is used to approximate the behavior of valve leaflets and applied to fully image-based mitral valve models to simulate valve closure for fast applications like intraoperative surgical planning. This approach is used to simulate a technique used in valve repair and to assess the role of chordae in determining the closed configuration of the valve. Direct image-based comparison is used for validation. Results of M-S model simulations showed that it is possible to build fully image-based models of the mitral valve and to rapidly simulate closure with sub-millimeter accuracy. Chordae, which are presently difficult to image, are shown to be strong determinants of closed valve shape.

Surgical repair of the mitral valve results in better outcomes than valve replacement, yet diseased valves are often replaced due to the technical difficulty of the repair process. A surgical planning system based on patient-specific medical images that allows surgeons to simulate and compare potential repair strategies could greatly improve surgical outcomes. The system must simulate valve closure quickly and handle the complex boundary conditions imposed by the chords that tether the valve leaflets. We have developed a process for generating a triangulated mesh of the valve surface from volumetric image data of the opened valve. The closed position of the mesh is then computed using a mass-spring model of dynamics. In the mass-spring model, triangle sides are treated as linear springs supporting only tension. Chords are also treated as linear springs, and self-collisions are detected and handled inelastically. The equations of motion are solved using implicit numerical integration. The simulated closed state is compared with an image of the same valve taken in the closed state to assess accuracy of the model. The model exhibits rapid valve closure and is able to predict the closed state of the valve with reasonable accuracy.