Hemodynamics in artery stenosis models based on computational fluid dynamics simulations

Referencia Apresentador Autores
(Instituição)
Resumo
01-019
Janaina Andrea Dernowsek Rezende, R.A.(Renato Archer Center for Information Technology); Silva, J.V.(Renato Archer Center for Information Technology); Dernowsek, J.A.(Renato Archer Center for Information Technology); Mironov, V.(Renato Archer Center for Information Technology); Vilalba, F.d.(Renato Archer Center for Information Technology); Lara, V.F.(Renato Archer Center for Information Technology); Nogueira, J.A.(Renato Archer Center for Information Technology); Recently, numerical analysis and computational fluid dynamics (CFD) have been applied for cardiovascular medicine and for quantifying aortic valve hemodynamic. The simulation of blood flows in compliant large vessels is a very active research topic. In the development of new types of prostheses or even to the improvement of existing ones is important to perform in silico, in vitro and in vivo studies. By facilitating aspects as quickness, economical, low-risk prototyping, CFD modelling has already revolutionized research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterization of complex physiological pressure and flow fields and computational measurements which cannot be directly taken as, for example, wall shear stress (WSS). Thus, the purpose of this study was to explore the effect of hemodynamics factors in vascular segments from morphologically realistic three-dimensional (3D), and to compare the velocity, pressure and wall shear stress with two different models of vascular stenosis. By varying geometry parameters, various sections in the vascular segment can be evaluated using computational fluid dynamics (CFD). This model started by the segmentation of a clinical image of a vascular branch located near to the hearth. This ramification came from a Computed Tomography (CF) scan. Medical Imaging Software InVesalius, originally created in the Renato Archer Center for Information Technology (CTI) is able to import CT images (and also Magnetic Resonance Image - MRI) and generate a 3D digital model. Therefore, CT from a human heart was imported into InVesalius and processed to obtain a 3D model of a vascular branch. In order to be possible to simulate the mesh, it was needed to modulate the surfaces to finally get a 3D model. With the vascular tree mesh available, CFD simulations were initiated. Numerical algorithms structure CFD codes are governed by the Navier–Stokes equations. There have been selected 10 cross-sections, the inlet and outlets to the analyses. These studies show the impact of the blood flow in different vascular branches and sections. We compared the velocity, pressure and WSS patterns in the vascular branches of a healthy subject and in the arteries stenosis (regular and irregular) that were modeled at Rhinoceros. The 3D computational domains were initially discretized into elements in the range of 219,000 and 450,000. Flow velocity and pressure profiles of each branch and models show a uniform velocity distribution in a normal vascular branch, but a different behavior happens with the two stenoses models. In the sections 4 and 5, the models were modified to mimic the strangulation of the stenosis diseases (concentric and irregular stenoses) and its velocities profiles present peaks, mainly the regular stenosis model. It is visible an elevation in the velocity of the section 5 from regular stenosis model, showing a greater narrowing when we compare with irregular stenosis model. The pressure distribution on the wall of all models shows generally low pressure downstream of the stenosis and the lowest pressure at the distal end of stenosis and the WSS magnitude was computed. In the irregular stenosis was found an increase of the WSS. The results show that CFD simulations provide relevant information about the blood flow behavior in vascular segments and it can futurely help to predict behavior of stents or any replacing device to the cardiovascular field. --------- Our thanks to CNPq and FAPESP.
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