BIOMEDICAL MODELING OF THE CIRCULATION TO IMPROVE THE EFFICIENCY OF CARDIOVASCULAR IMPLANTS

Abstract

Cardiovascular implants (hereinafter referred to as CVIs) play an important role in the treatment of various cardiovascular diseases; however, their effectiveness often depends on hemodynamic conditions, which may vary according to patient-specific anatomy and the characteristics of the implant itself. Biomedical blood flow modeling (hereinafter referred to as BBFM) enables a detailed investigation of hemodynamic conditions, thereby contributing to improved reliability and functionality of implants. The application of modern computational fluid dynamics methods provides analysis and optimization of CVIs, which determines the relevance of this study. The aim of the article is to substantiate the use of biomedical blood flow modeling to enhance the efficiency and reliability of cardiovascular implants. The study employs methods of analysis, synthesis, abstraction, induction, and deduction to evaluate hemodynamic parameters, mathematical models of blood circulation, and recommendations for their application. Key hemodynamic parameters determining the effectiveness of CVIs are investigated. In particular, blood flow velocity is analyzed as a parameter characterizing the intensity of blood movement within vessels and enabling the identification of acceleration and stagnation zones. Blood pressure reflects the mechanical load on the vascular wall and is essential for assessing implant-induced effects. Blood viscosity determines flow resistance and affects the accuracy of modeling interactions with the implant surface. Wall shear stress (WSS) is identified as a criterion for thrombus formation risk, while blood flow pulsatility allows the analysis of hemodynamic stability throughout the cardiac cycle. Contemporary mathematical models of blood circulation and approaches to their application are analyzed, including the Navier–Stokes equations, pulsatile flow models, and fluid–structure interaction (FSI) models. Computational methods such as computational fluid dynamics (CFD), the finite element method, and the finite volume method are considered. Software tools used for modeling are identified, including ANSYS Fluent, COMSOL Multiphysics, and OpenFOAM. Recommendations for the application of BBFM to improve the functional characteristics and reliability of CVIs are developed. The use of three-dimensional patient-specific vascular models with high spatial resolution is proposed, along with the application of pulsatile boundary conditions to reproduce the real cardiac cycle and non-Newtonian blood models in regions with low shear rates. Additionally, it is recommended to account for vascular wall and implant deformation using FSI models and to validate CFD results through comparison with experimental data. The obtained results confirm the feasibility of using biomedical blood flow modeling for the optimization of cardiovascular implants. This approach not only enhances their effectiveness but also reduces the risks of complications associated with thrombosis and other hemodynamic disturbances.