Prosthetic aortic valve performance assessment: FSI simulations, spectral analysis and FTLE-based calcification prediction

Calcific aortic valve leaflet degeneration remains a main cause of bioprosthetic aortic valve failure and disturbed blood flow dynamics. This talk presents a computational framework combining high-order fluid-structure interaction (FSI) simulations with dedicated spectral and Lagrangian analyses to characterise post-valvular flow disturbances and identify calcification-prone regions on valve leaflets.
The numerical FSI approach couples a sixth-order finite-difference Navier–Stokes solver with a finite-element elastodynamics formulation through variational L²-projection, ensuring velocity and force continuity at the fluid-solid interface (Nestola et al., J. Comput. Phys., 2019). Simulations capture transitional aortic flows at orifice Reynolds number of 3,800 as well as valve motion. The results have been validated against tomographic particle image velocimetry and 4D Flow MRI measurements.
Three-dimensional kinetic energy spectra are computed via FFT on concentric spherical shells positioned downstream of the valvular orifice (Corso et al., Comput. Biol. Med., 2024). For a severe calcific aortic stenosis, the spectral decay follows Kolmogorov's -5/3 scaling across a broad wavenumber range, indicating canonical turbulent cascade. Bioprosthetic configurations characterised by large leaflet displacements throughout systole deviate from this behaviour, suggesting that leaflet-motion-induced helical flow structures partially suppress nonlinear energy transfer. Novel field quantities, namely modal kinetic energy anisotropy and normalised helicity intensity, are introduced and shown to correlate inversely, with correlation strength varying markedly across valve configurations depending on leaflet kinematics.
For calcification prediction, strain-based finite-time Lyapunov exponents (FTLE) and wall shear stress (WSS) fields are evaluated on leaflet surfaces from FSI results. Unsupervised clustering (k-means) on these features enables objective risk stratification and calcific area prediction across tissue and polymeric valve configurations, with validation against micro-CT maps from explanted clinical specimens (Tsolaki, Corso et al., Acta Biomater., 2023).
The talk concludes with perspectives on integrating these diagnostic metrics into a Bayesian optimisation loop for next-generation polymeric valve design.