Blog

Delve into the pivotal research presented in “Beyond Static Planning: Computational Predictive Modeling to Avoid Coronary Artery Occlusion in TAVR,” a study published on June 18, 2024, in The Annals of Thoracic Surgery. This insightful paper explores the integration of computational predictive modeling into the preoperative planning phase of transcatheter aortic valve replacement (TAVR) to significantly reduce the risk of coronary artery occlusion (CO)—a severe complication associated with TAVR procedures.

Dr. Lakshmi Prasad Dasi, a noted contributor, alongside a team of esteemed researchers, including Kimberly Holst, MD, Taylor Becker, MS, J. Trent Magruder, MD, Venkateshwar Polsani, MD, and Vinod H. Thourani, MD, utilized DASI Simulations’ advanced modeling tools to assess CO risk in patients undergoing TAVR. Their study covered a patient cohort from January 2020 to December 2022, identifying high-risk individuals based on traditional and computational methods and implementing targeted procedural modifications to mitigate risk.

The findings reveal that computational modeling accurately predicted an increased risk of CO in a significant portion of the patient group, guiding the implementation of successful procedural strategies such as bioprosthetic or native aortic scallop intentional laceration and chimney coronary stents. Remarkably, there were no episodes of coronary artery compromise post-TAVR in the predicted high-risk group following these modifications, nor in those assessed as low risk undergoing standard TAVR.

This research underscores the transformative potential of integrating computational predictive modeling in surgical planning, enhancing safety and outcomes in TAVR procedures. For a comprehensive understanding of the study’s methodology, results, and clinical implications, read the full publication.