Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling
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Aortic valve diseases are among the most common cardiovascular defects. Since a non-functioning valve results in disturbed blood flow conditions, the diagnosis of such defects is based on identification of stenosis via echocardiography. Calculation of disease parameters such as valve orifice area or transvalvular pressure gradient using echocardiography is associated with substantial errors. Computational fluid dynamics (CFD) modeling has emerged as an alternative approach for accurate assessment of aortic valve hemodynamics. Fluid-structure interaction (FSI) modeling is adapted in these models to account for counter-interacting forces of flowing blood and deforming leaflets for most accurate results. However, implementation of this approach is difficult using custom built codes and algorithms. In this paper, we present an FSI modeling methodology for aortic valve hemodynamics using a commercial modeling software, ANSYS. We simulated the problem using fluid flow solver FLUENT and structural solver MECHANICAL APDL under ANSYS and coupled the solutions using System Coupling Module to enable FSI. This approach minimized adaptation problems that would raise if separate solvers were used. As an example case, we investigated influence of leaflet calcification on hemodynamic stresses and flow patterns. Model geometries were generated using b-mode echocardiography images of an aortic valve. A Doppler velocity measurement was used as velocity inlet boundary condition in the models. Simulation results were validated by comparing leaflet movements in the simulations with b-mode echo recordings. Wall shear stress levels, pressure levels and flow patterns agree well with previous studies demonstrating the accuracy of our results. Our modeling methodology can be easily adopted by researchers that are familiar with ANSYS and other similar CFD software to investigate similar biomedical problems.
- Biomedical Research Center Research [196 items ]