Impact of Device Type and Orientation on Post-Transcatheter Aortic Valve Replacement Complications in Bicuspid Aortic Valve Patients: A Computational Study

Salwa Anam, Brandon Kovarovic, Puja Parikh, Marvin Slepian, Ashraf Hamdan, Rami Haj-Ali, Danny Bluestein*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Currently, no clinical modality reliably assists clinicians in selecting the optimal transcatheter aortic valve replacement (TAVR) device orientation. This is critical for the growing population of young bicuspid aortic valve (BAV) TAVR candidates, who are at high risk for post-procedural complications. We aim to develop a predictive computational modeling workflow to identify which TAVR device and orientation will minimize the risk of paravalvular leakage (PVL), coronary obstruction, and flow-induced thrombogenicity. We compared the risk of post-TAVR complications across more than 30 device orientation combinations by virtually implanting self-expandable and balloon-expandable TAVR devices in three BAV patients. PVL severity varied significantly with device orientation, reaching up to 22.03 mL/beat with certain self-expandable devices. For self-expandable devices, orientations that ensured the shortest distance between the taller skirt region and PVL regions minimized PVL. A shorter frame height in balloon-expandable devices was insufficient to cover PVL regions in certain patients. Pearson correlation demonstrated a negative relationship between device oversizing and PVL. The risk of flow-induced thrombogenicity was positively correlated with PVL severity. A patient-specific computational modeling workflow can identify the optimal TAVR device and orientation, minimizing life-threatening post-TAVR complications and facilitating future reinterventions for young BAV TAVR candidates.

Original languageEnglish
Article number2459
JournalASAIO Journal
DOIs
StateAccepted/In press - 2025

Funding

FundersFunder number
Abbott Pharmaceuticals
Edwards Lifesciences
NIH-NIBIBU01EB026414

    Keywords

    • bicuspid aortic valve
    • coronary obstruction
    • digital twin
    • paravalvular leakage
    • predictive computational modeling
    • TAVR

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