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Towards Biomechanical Analyses for Predictive Planning of Transcatheter Aortic Valve Implantation
Michael Gessat, PhD1, Christoph Russ2, Raoul Hopf2, Simon H. Sündermann, MD1, Sven Hirsch, PhD2, Edoardo Mazza, PhD2, Gábor Székely, PhD2, Volkmar Falk, MD, PhD1.
1University Hospital Zürich, Zürich, Switzerland, 2Swiss Federal Institue of Technology (ETH) Zürich, Zürich, Switzerland.

OBJECTIVE: Transcatheter aortic valve implantation (TAVI) is an effective treatment for severe aortic stenosis in high-risk patients but causes complications, such as AV-blocks, paravalvular leaks, vascular complications, and annular rupture. Valve selection, sizing, and positioning are critical for reducing the risk for these complications. Geometric parameters, such as annular diameter or cross-sectional area and distance to the coronary ostia are currently considered during implantation planning. Biomechanical analyses may add a new perspective to preoperative TAVI planning. We present the current state of developments aiming at providing tools for patient-specific prediction of the biomechanical situation in the aortic root after TAVI.
METHODS: Stent geometry was extracted from micro-CT. Mechanical models of TAVI stents were created using microCT imaging and literature values for the material parameters of Nitinol. The reliability of these models was evaluated experimentally.
Patient-specific anatomical models were created from CT images of six patients. The mechanical characteristics of the tissues were added based on biomechanical models and parameters from literature. Verification of these models was performed using tissue samples from patients undergoing surgery at the aortic root or ascending aorta.
In-silico prediction of the displacement of tissues and the contact forces induced by valvuloplasty and stent implantation was performed with the Finite Element Method. Stent models extracted from post-operative CT images were used for validation.

RESULTS: The reliability of the predictions is influenced by the choice of tissue models and parameters. With a reasonably accurate and yet not overly complex non-linear model, the prediction of radial strain after stent implantation, characterized by the change in circumference of the aortic annulus and ascending aorta, is accurate within an error margin of 10%. Since calcifications were not sufficiently taken into account, errors were larger in cases with severe calcifications.
CONCLUSIONS: Patient-specific modeling of the aortic root for predicting the biomechanical situation during and after TAVI is feasible. Yet, there remain unanswered questions regarding the trade-off between model complexity and accuracy and the representation of calcium.

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