Reduced Order Modeling for Real-Time Stent Deformation Simulations of Transcatheter Aortic Valve Prostheses.

Area of Science:

• Biomedical Engineering
• Computational Mechanics
• Medical Device Simulation

Background:

• Transcatheter aortic valve replacement (TAVR) requires accurate deployment prediction.
• Traditional finite element (FE) modeling of TAVR is computationally intensive due to complex multiphysics and partial differential equations (PDEs).

Purpose of the Study:

• To develop a PDEs-based reduced order modeling (ROM) framework for rapid simulation of TAVR deployment.
• To accelerate the prediction of structural deformation for the Medtronic Evolut R valve stent frame.

Main Methods:

• Implemented a proper orthogonal decomposition-Galerkin (POD-Galerkin) approach with Discrete Empirical Interpolation Method for nonlinearities.
• Generated a snapshot library from 105 FE simulations in the offline phase.
• Validated ROM against full order model (FOM) solutions for linear elastic and hyperelastic models.

Main Results:

• Achieved strong agreement between ROM and FOM solutions for Evolut stent frame deformation.
• Demonstrated a computational speed-up of at least 92% in CPU time compared to FOM.
• Successfully simulated steady and unsteady regimes, including hyperelastic constitutive models.

Conclusions:

• The developed ROM framework enables rapid and accurate simulation of TAVR deployment.
• This represents a significant step towards real-time predictive modeling for TAVR procedures.
• The method holds potential for improving pre-procedural planning and device selection in aortic stenosis treatment.