Past Event: Oden Institute Seminar

A novel method to utilize murine animal models in pulmonary heart valve research

XinZeng Feng, Postdoc Fellow, Willerson Center for Cardiovascular Modeling and Simulation, UT Austin

Abstract

The development of replacement heart valve usually requires expensive and time-consuming large animal models. While murine models have many advantages in both speed and quantities, also allowing for the use of genetic knockout techniques, the very small size of the heart valve (~1mm) greatly limits their use and research. Particularly, it is still not clear about the unloaded shape of murine heart valves and their mechanical properties. In this talk, I will present an integrated imaging/computational method for studying murine heart valves. In the first part, I'll show our up-to-date analysis on high-resolution micro-CT images of a collection of nine murine heart valves. While different valves are fixed under different pressure level from 0 to 30mmHg, remarkably, we found a scaling law that the length of free edge changes with pressure in proportion to the circumference of the entire valve. In the second part, I'll discuss a computational pipeline to analyze the imaging data. The approach is based on isogeometric analysis and treats the valve as a 2D shell with leaflet-leaflet contact formulated by a volumetric potential. Using the scaling law as a geometric constraint, we systematically studied how unloaded valve geometry and material properties affect valve shape under uniform pressure. Therefore, by optimizing against the micro-CT images, we estimate, for the first time, unloaded murine pulmonary heart valve shape and mechanical properties. Collectively, I aim to demonstrate the capability of our integrated imaging/computational method and the potential of using murine animal models in pulmonary heart valve research and regenerative approaches for replacement heart valves. Bio Dr. Feng is a postdoc fellow at Willerson Center for Cardiovascular Modeling and Simulation at the University of Texas at Austin. He earned his PhD in Mechanical Engineering from Cornell University (2016) in the area of solid mechanics. Dr. Feng's research interests are focused on computational biomechanics in cardiovascular system, computational oncology, computational cell mechanics and cell traction microscopy.