Fluid‐structure interaction analysis of transcatheter aortic valve implantation

Author:

Fumagalli Ivan1ORCID,Polidori Rebecca2,Renzi Francesca2,Fusini Laura34,Quarteroni Alfio15,Pontone Gianluca3,Vergara Christian2ORCID

Affiliation:

1. MOX, Dipartimento di Matematica Politecnico di Milano Milan Italy

2. LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica Politecnico di Milano Milan Italy

3. Department of Perioperative Cardiology and Cardiovascular Imaging Centro Cardiologico Monzino IRCSS Milan Italy

4. Department of Electronics, Information and Biomedical Engineering Politecnico di Milano Milan Italy

5. Institute of Mathematics École Polytechnique Fédérale de Lausanne Lausanne Switzerland

Abstract

AbstractTranscatheter aortic valve implantation (TAVI) is a minimally invasive intervention for the treatment of severe aortic valve stenosis. The main cause of failure is the structural deterioration of the implanted prosthetic leaflets, possibly inducing a valvular re‐stenosis 5–10 years after the implantation. Based solely on pre‐implantation data, the aim of this work is to identify fluid‐dynamics and structural indices that may predict the possible valvular deterioration, in order to assist the clinicians in the decision‐making phase and in the intervention design. Patient‐specific, pre‐implantation geometries of the aortic root, the ascending aorta, and the native valvular calcifications were reconstructed from computed tomography images. The stent of the prosthesis was modeled as a hollow cylinder and virtually implanted in the reconstructed domain. The fluid‐structure interaction between the blood flow, the stent, and the residual native tissue surrounding the prosthesis was simulated by a computational solver with suitable boundary conditions. Hemodynamical and structural indicators were analyzed for five different patients that underwent TAVI – three with prosthetic valve degeneration and two without degeneration – and the comparison of the results showed a correlation between the leaflets' structural degeneration and the wall shear stress distribution on the proximal aortic wall. This investigation represents a first step towards computational predictive analysis of TAVI degeneration, based on pre‐implantation data and without requiring additional peri‐operative or follow‐up information. Indeed, being able to identify patients more likely to experience degeneration after TAVI may help to schedule a patient‐specific timing of follow‐up.

Funder

H2020 European Research Council

Publisher

Wiley

Subject

Applied Mathematics,Computational Theory and Mathematics,Molecular Biology,Modeling and Simulation,Biomedical Engineering,Software

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