Volume 18, Issue 4 (2026)

Optimization of the Nitinol Framework of an Aortic Valve Bioprosthesis Using Numerical Simulation
Optimization of the Nitinol Framework of an Aortic Valve Bioprosthesis Using Numerical Simulation

Key words: aortic heart valve prosthesis; numerical simulation; finite element method; hydrodynamic study.

2026, Volume 18, Issue 4, page 14
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The application of numerical analysis methods when developing novel heart valve bioprostheses is an integral stage of their design; it enables to optimize the bioprosthetic construction and accelerate their development process.

The aim of the study was to conduct hydrodynamic tests of a prototype of a self-expandable transcatheter aortic valve bioprosthesis and, based on the findings, using numerical simulation, improve the geometry of the bioprosthetic nitinol frame.

Materials and Methods. The study investigated an aortic valve bioprosthesis with a self-expanding nitinol frame and the leaflet apparatus of three biological leaflets fixed to the frame through the holes in the commissural posts. The bioprosthesis was tested on a test bench to evaluate the hydrodynamic characteristics of heart valve prostheses. A computer model of the valve frame was created for a finite element analysis in the COMSOL Multiphysics software environment, and validated based on the observed deformations of the bioprosthesis in a full-scale experiment. The obtained model was used for parametric optimization of the commissural post geometry to reduce their deformities.

Results. Bench hydrodynamic tests revealed significant deformities of the bioprosthetic commissural posts (bending up to 5 mm) in leaflet closure under diastolic pressure. The numerical simulation using the finite element method enabled to precise the load on the posts (1.3 N instead of 1.52 N according to preliminary calculations). Based on the results obtained, an optimized frame design was developed with increased width and thickness of the beams in the area of commissural posts (from 0.3 to 0.5 mm and from 0.4 to 0.5 mm, respectively). Finite element analysis showed the suggested modification to significantly increase the structural stiffness, reducing the deformation value to 0.7 mm under the load of 1.3 N.

Conclusion. The suggested approach to the application of numerical simulation demonstrated its effectiveness for optimizing the design of the nitinol frame of a transcatheter aortic valve bioprosthesis. The suggested modification of the commissural post geometry significantly reduced their deformity under the hydrodynamic load on the valve, which contributed to the preservation of the leaflet coaptation, reduced the risk of paravalvular regurgitation and prosthesis dislocation. The findings demonstrate the promise of using numerical simulation methods at a bioprosthetic design stage enabling to reduce the number of necessary physical prototypes and accelerate the development process.


1.         Ovcharenko E.A., Onishchenko P.S., Kostyunin A.E., Glushkova T.V., Akentуeva T.N., Borisova N.N., Fokeeva M.P., Klyshnikov K.Yu. Automatic optimization of heart valve prosthesis — a genetic algorithm-based approach. Siberian Journal of Clinical and Experimental Medicine 2025; 40(2): 191–200, https://doi.org/10.29001/2073-8552-2025-40-2-191-200.

2.         Zakerzadeh R., Hsu M.C., Sacks M.S. Computational methods for the aortic heart valve and its replacements. Expert Rev Med Devices 2017; 14(11): 849–866, https://doi.org/10.1080/17434440.2017.1389274.

3.         Abbas S.S., Nasif M.S., Al-Waked R. State-of-the-art numerical fluid–structure interaction methods for aortic and mitral heart valves simulations: a review. SIMULATION 2022; 98(1): 3–34, https://doi.org/10.1177/00375497211023573.

4.         Zakerzadeh R., Hsu M.C., Sacks M.S. Computational methods for the aortic heart valve and its replacements. Expert Rev Med Devices 2017; 14(11): 849–866, https://doi.org/10.1080/17434440.2017.1389274.

5.         Astorino M., Gerbeau J.-F., Pantz O., Traoré K.-F. Fluid–structure interaction and multi-body contact: application to aortic valves. Computer Methods in Applied Mechanics and Engineering 2009; 198(45–46): 3603–3612, https://doi.org/10.1016/j.cma.2008.09.012.

6.         Bellhouse B.J., Talbot L. The fluid mechanics of the aortic valve. Journal of Fluid Mechanics 1969; 35(4): 721–735, https://doi.org/10.1017/s0022112069001406.

7.         Mohammadi H., Mequanint K. Prosthetic aortic heart valves: modeling and design. Med Eng Phys 2011; 33(2): 131–147, https://doi.org/10.1016/j.medengphy.2010.09.017.

8.         Klyshnikov K.Yu., Onishchenko P.S., Glushkova T.V., Akentyeva T.N., Kostyunin A.E., Rezvova M.A., Ovcharenko E.A. On the setting up of numerical modeling of heart valve prostheses. Sibirskij nauchnyj medicinskij zhurnal 2024; 44(5): 119–128, https://doi.org/10.18699/ssmj20240514.

9.         Klyshnikov K.Y., Onischenko P.S., Ovcharenko Е.А. Study of biomechanics of the heart valve leaflet apparatus using numerical simulation method. Sovremennye tehnologii v medicine 2022; 14(2): 6–14, https://doi.org/10.17691/stm2022.14.2.01.

10.        Zhuravleva I.Y., Bogachev-Prokofev A.V., Timchenko T.P., Sharifulin R.M., Prikhodko Y.M. Bioprosthetic aortic valve (variants) for open non-suture and transcatheter implantation. Patent RU 2749118C1. 2021.

11.        Mummert J., Sirois E., Sun W. Quantification of biomechanical interaction of transcatheter aortic valve stent deployed in porcine and ovine hearts. Ann Biomed Eng 2013; 41(3): 577–586, https://doi.org/10.1007/s10439-012-0694-1.

12.        Dwyer H.A., Matthews P.B., Azadani A., Ge L., Guy T.S., Tseng E.E. Migration forces of transcatheter aortic valves in patients with noncalcific aortic insufficiency. J Thorac Cardiovasc Surg 2009; 138(5): 1227–1233, https://doi.org/10.1016/j.jtcvs.2009.02.057.

13.        Auricchio F., Taylor R.L., Lubliner J. Shape-memory alloys: macromodelling and numerical simulations of the superelastic behavior. Computer Methods in Applied Mechanics and Engineering 1997; 146(3–4): 281–312, https://doi.org/10.1016/s0045-7825(96)01232-7.

14.        Auricchio F. A robust integration-algorithm for a finite-strain shape-memory-alloy superelastic model. International Journal of Plasticity 2001; 17(7): 971–990, https://doi.org/10.1016/s0749-6419(00)00050-4.

15.        Souza A.C., Mamiya E.N., Zouain N. Three-dimensional model for solids undergoing stress-induced phase transformations. European Journal of Mechanics — A/Solids 1998; 17(5): 789–806, https://doi.org/10.1016/s0997-7538(98)80005-3.

16.        Auricchio F., Reali A., Stefanelli U. A three-dimensional model describing stress-induced solid phase transformation with permanent inelasticity. International Journal of Plasticity 2007; 23(2): 207–226, https://doi.org/10.1016/j.ijplas.2006.02.012.

17.        Auricchio F., Coda A., Reali A., Urbano M. SMA numerical modeling versus experimental results: parameter identification and model prediction capabilities. Journal of Materials Engineering and Performance 2009; 18(5–6): 649–654, https://doi.org/10.1007/s11665-009-9409-7.

Vladimirov S.V., Prikhodko Yu.M., Khakhalkin V.V., Borodin V.P., Mochalova A.B., Bogachev-Prokofiev A.V. Optimization of the nitinol framework of an aortic valve bioprosthesis using numerical simulation. Sovremennye tehnologii v medicine 2026; 18(4): 14, https://doi.org/10.17691/stm2026.18.4.02