AI has already transformed TAVR care—and the best is yet to come
Artificial intelligence (AI) is starting to play a much bigger role during transcatheter aortic valve replacement (TAVR) procedures, helping cardiologists plan ahead, make critical decisions and even predict the risk of certain complications.
The team behind a new analysis in Life explored this trend at length, focusing on 51 different studies published from 2014 to 2025.[1]
“AI algorithms could revolutionize the heart team decision-making process, being not only a tool for patient evaluation, but an active member of the team with applications to analyze and optimize all stages of the TAVR procedure, guide decision making and predict outcomes, and, with the contribution and evaluation of information from all human members of the team, enhance even more the patient-mediated medicine/interventions,” wrote first author Flora Tsakirian, MD, MSc, an interventional cardiology researcher with National and Kapodistrian University of Athens in Greece, and colleagues.
Tsakirian et al. separated the many uses of AI during TAVR into four distinctive categories:
1. Medical imaging and pre-procedural planning
It’s no secret that radiology is the one specialty getting more out of advanced AI than cardiology. AI is now commonly used to review imaging results and perform a variety of tasks, including CT segmentation, plaque evaluation and even post-TAVR patient assessments. The authors specifically called out the impact AI-powered 4D imaging can make on patient care.
“AI-driven 4D-CT tools quantify dynamic prosthesis behavior—volume, cross-sectional area and displacement across the cardiac cycle, facilitating standardized post-TAVR surveillance and durability research,” the authors added. “These dynamic markers may help uncover device–tissue interactions that static imaging misses.”
2. Image quality optimization
AI models have been developed to help care teams with CT reconstruction, dose reduction and pre-TAVR coronary evaluations. As coronary CT angiography (CCTA) continues to gain momentum as the go-to imaging modality for evaluating many heart patients, AI offerings designed to evaluate CCTA images are only going to become more and more important to TAVR operators.
3. Assisting clinicians with predicting outcomes and making decisions
AI can help care teams anticipate when patients may face an increased risk of severe complications, or even death, following TAVR. It may turn out that some patients should undergo a different treatment option—surgical or robotic aortic valve replacement, for instance—due to the risks uncovered by AI.
AI-enabled risk scores are already starting to outperform traditional risk scores for the identification of various issues. However, certain barriers—data privacy, the need for “clearer reporting”—remain in place.
4. Emerging fields that are still works in progress
This includes virtual reality, augmented reality, digital twins and a wide variety of other advanced technologies. The authors appeared to be especially impressed by the significant potential of intra-procedural AI.
“Narrative syntheses suggest real-time AI for landmarking, complication detection, and deployment optimization across interventional cardiology, including structural heart procedures," the group wrote. “Translation will depend on fast, reliable processing, user-centric UI, and prospective evaluation demonstrating safety and benefit.”
Limitations to consider
The group did point out that AI implementation during TAVR still faces certain challenges. It requires a certain level of “specialized expertise,” for example, that may not be available in all parts of the world. In addition, physician skepticism over these algorithms and the high costs associated with AI are limitations that have not yet been fully solved or addressed.
Click here to read the full analysis.
Michael has more than 19 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.