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Mind the gap: avoiding paravalvular leak using computer simulation in bicuspid transcatheter aortic valve
James Dargan1, Rumneek Hampal2, Faisal Khan2
1Cardiovascular Clinical Academic Group, St George's University of London and St George's University Hospitals NHS Foundation Trust, Cranmer Terrace, London SW17 0RE, UK.
European Heart Journal. Case Reports
|October 14, 2022
Summary
Patient-specific computer simulation aids transcatheter aortic valve replacement (TAVR) sizing in complex bicuspid aortic valve (BAV) cases. This technology helps select the correct valve size and deployment, improving outcomes in challenging anatomies.
Area of Science:
- Cardiovascular Medicine
- Medical Imaging
- Computational Biology
Background:
- Transcatheter aortic valve replacement (TAVR) is increasingly common, expanding to diverse patient groups.
- Bicuspid aortic valve (BAV) presents unique anatomical challenges for TAVR, particularly in valve sizing.
- Current TAVR sizing relies on CT-derived measurements and algorithms, which can be ambiguous in borderline cases.
Observation:
- A case involving an 86-year-old female with severe, calcific BAV aortic stenosis treated with TAVR.
- The patient presented with anatomical difficulties and borderline valve sizing, necessitating advanced pre-procedural planning.
- Patient-specific computer simulation using finite-element modeling was employed with the Medtronic Evolut PRO+ platform.
Findings:
- Computer simulation enabled precise selection of the TAVR valve size and optimal deployment height.
- The simulation accurately predicted the procedural outcome in a complex, calcified BAV case.
- This approach facilitated a tailored discussion and decision-making process within the heart team.
Implications:
- Patient-specific computer simulation offers a valuable tool for optimizing TAVR in complex BAV anatomies.
- This technology can enhance procedural safety and efficacy by improving valve selection and deployment.
- It supports personalized treatment strategies and facilitates collaborative decision-making in interventional cardiology.
