Working towards the future of transcatheter aortic valve replacement: integrating computational modeling with patient-specific clinical care

INTRODUCTION: Transcatheter aortic valve implantation (TAVR) is rapidly evolving to become the standard of care for all types of aortic stenosis (AS) patients, as opposed to open-heart surgery. The emergence of new commercial TAVR devices, as well as technological advancements in AS diagnosis and procedural planning, combat post-TAVR complications while also posing new challenges with patient selection and optimal timing of valve replacement. Computational modeling is a powerful tool that may help streamline solutions for heart teams when faced with these complexities. AREAS COVERED: This narrative review outlines the evolving landscape of TAVR patients - with a primary focus on AS - and examines the paradigm shift toward computational modeling in diagnostics, procedural planning, and intraoperative guidance. Highlighted mechanistic and AI-accelerated modeling studies were identified via PubMed search with publication dates ranging from January 2016-April 2026. The remaining sources were also identified via PubMed without a publication date constraint. EXPERT OPINION: TAVR indications and available devices will continue to increase. The development of TAVR devices with improved durability is underway, which is increasingly necessary as the mean age of TAVR patients decreases and the general life expectancy increases. Emerging computational techniques such as radiomics, as well as AI/ML tools to enhance standard imaging modalities, hold promise in identifying who and when to treat for AS or AR. Digital twins may facilitate TAVR planning to ensure the optimal treatment pathway for individual patients, navigating through these compounded complexities.