In silico approaches for transcatheter aortic valve replacement inspection

ABSTRACT

Introduction: Increasing applications of transcatheter aortic valve replacement (TAVR) to treat high- or medium-risk patients with aortic diseases have been proposed in recent years. Despite its increasing use, many influential factors are still to be understood. Furthermore, innovative applications of TAVR such as in bicuspid aortic valves or in low-risk patients are emerging in clinical use.

Numerical analyses are increasingly used to reproduce clinical treatments. The future trends in this area are foreseen for in silico trials and personalized medicine.

Areas covered: This review paper analyzes the recent years (Jan 2018 – Aug 2020) of in silico studies simulating the behavior of transcatheter aortic valves with emphasis on the addressed clinical question and the used modeling strategies.

The manuscripts are firstly classified based on their clinical hypothesis. A second classification is based on the adopted modeling approach in terms of patient domain, device modeling, and inclusion or exclusion of the fluid domain.

Expert opinion: The TAVR can be virtually performed in numerous vessel geometries and with different devices. This versatility allows a rapid evaluation of the feasibility of different implantation approaches for specific patients, and patient populations, resulting in faster and safer introduction or optimization of new treatments or devices.

KEYWORDS:

• Transcatheter aortic valve implantation
• modeling
• simulations
• FSI
• in-silico medicine

Article Highlights bullets

• TAVR in silico models are an additional useful tool for choosing the valve typology and size in patient-specific implantation.

• From imaging to interventional procedures, pre-procedural planning to post-procedural care simulations can be of help.

• Simulations with their predictive modeling could reduce animal and clinical trials.

• Simulations are still interconnected with experiments: experimental results help in validating and improving the simulations and the simulations help in acquiring new knowledge.

• For accurate simulated results, simulations are required to be close to reality as much as possible.

• When used for real-time prediction, simulations are required to be fast. Hence, reduced/surrogate models are required.

• The regulatory process for biomedical devices started receiving and accepting in silico evidence from modeling and numerical simulations.

• From a modeling viewpoint, the Fluid-Structure Interaction (FSI) methodology represents the best numerical approach capable of reproducing the loading on the valve leaflets due to the fluid coupling.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.