Fluid-structure interaction analysis of bioinspired polymeric heart valves with experimental validation

BACKGROUND AND OBJECTIVES: Valvular heart disease, when not addressed adequately, can result in heart failure, serious heart-related health problems, and in some cases, death. Polymeric heart valves (PHVs) are promising valve replacement technologies that may offer improved durability and better biological performance. Notably, PHVs have the potential to accommodate highly innovative valve designs. Given this feature of PHVs, it is important to shortlist the best performing valve designs prior to committing to extensive in vitro hemodynamic validation prototypes. METHODS: This study presents a computational fluid-structure interaction (FSI) workflow, which integrates computational fluid dynamics (CFD) and finite element analysis (FEA), to simulate the hemodynamic performance of PHVs with two different valve designs under physiological conditions. RESULTS: The model accurately predicts cardiac output (CO), effective orifice area (EOA) and regurgitant fraction (RF) and these predictions have been successfully validated using experimental data. Consistent with experimental findings, increasing valve thickness results in a decrease in EOA, with RF trends varying between different valve designs. The fully opened and unfolded valve exhibited the lowest WSS on the leaflet surfaces. Both valve design and thickness significantly influence stress distribution along the leaflets with the thinnest valves showing lower von Mises stresses during opening and higher stresses during closing. Detailed analysis of flow patterns, wall shear stress (WSS), valve opening and closing behaviors, and mechanical stress distribution are presented. CONCLUSIONS: This work demonstrates the potential of FSI simulations in predicting the hydrodynamic and mechanical behavior of PHVs, offering valuable insights into valve durability and design optimization for improved patient outcomes. This approach can significantly accelerate valve development by reducing reliance on extensive in vitro and in vivo testing.