Simulation of transcatheter aortic valve implantation procedure

K. Yu. Klyshnikov ; V. I. Ganyukov ; A. V. Batranin ; D. V. Nyshtaev ; E. A. Ovcharenko

Matematičeskaâ biologiâ i bioinformatika, Tome 14 (2019) no. 1, pp. 204-219.

Résumé

The study is devoted to numerical modeling of transcatheter aortic valve implantation (TAVI) from the position of prognostic value in comparison with clinical data. The finite element method implemented in the Abaqus/CAE software and the reconstruction of three-dimensional models based on the computer microtomography of the CoreValve bioprosthesis of a size of 29 mm and the patient-specific data of functional studies (multispiral tomography) were used in the work. The study included three variations in the modeling of the aortic valve prosthesis procedure, which determine the level of detalization of the numerical experiment. All stages of the TAVI process were reproduced: the crimp of the prosthesis, the movement of the delivery system, the interaction of the guide – guidewire with the elements of the “prosthesis-root” of the aorta system, implantation itself. In silico experiment demonstrated significant quantitative and qualitative agreement with the data of intraoperative fluorography and computed tomography after the TAVI procedure. It is shown that the inclusion of additional elements – the guidewire and catheter of the delivery system into the “aortic root” has a positive effect on the convergence of the data with the clinical results. The analysis of the stress-strain state of the elements interacting in the experiment demonstrated a significant contribution to the analyzed parameters of the prosthetic motion stage along the guidewire as part of the delivery system catheter. Nevertheless, a comparison with the results of the clinical evaluation of the TAVI procedure revealed a number of differences in the response of the model of the bioprosthesis at the later stages of modeling, which requires further researches of a level of detalization. The approach is extremely promising both for practitioners and for research work of prosthetic designers, it can be applied in further R tasks.

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