An In Vitro Study of PVP Bioprosthetic Valve Dynamics Using Optical and Ultrasound Imaging

Structural valve degeneration caused by mechanical stress is considered one of the primary hemodynamic factors limiting the long-term durability of bioprosthetic transcatheter aortic valve replacements (TAVR). A novel pulmonary visceral pleura (PVP) tissue—characterized by a higher elastin-to-collagen ratio than the bovine or porcine pericardium used in current commercial devices—shows great potential for improving resilience, biocompatibility, and durability in future TAVR designs. To optimize PVP-based TAVR and validate fluid-structure interaction (FSI) simulations, a detailed experimental understanding of valve FSI behavior is essential. In this study, a benchtop platform was developed using a combined optical and acoustic imaging approach to quantitatively investigate the interaction between pulsatile flow and leaflet kinematics in a prototype valve model. The valve was mounted into a transparent aortic root phantom. In vitro experiments employed both optical and ultrasound B-mode imaging velocimetry to study flow and leaflet motion under steady and pulsatile conditions. Pulsatile flow was driven by a programmable pump, with waveform parameters mimicking physiological aortic flow to ensure clinical relevance. The leaflet opening geometry, effective orifice area, and associated flow field characteristics were analyzed and compared to previous results obtained using a silicone-based valve model. The flow patterns and leaflet dynamics observed in the PVP valve demonstrated improved compliance and reduced flow resistance under pulsatile conditions. Results show good agreement between the two measurement modalities. While optical measurements provided high-resolution flow field data, the ultrasound system effectively tracked leaflet motion and captured velocity data in regions inaccessible to optical measurements. This integrated optical-acoustic framework offers a robust tool for studying valve biomechanics and provides a valuable dataset for validating computational FSI models and informing future TAVR design improvements.