학술논문

Finite Element Analysis of Patient-Specific Heart Model with Simulated Aortic Stenosis
Document Type
Conference
Source
2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE) BIBE Bioinformatics and Bioengineering (BIBE), 2023 IEEE 23rd International Conference on. :315-319 Dec, 2023
Subject
Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Heart
Analytical models
Three-dimensional displays
Computational modeling
Biological system modeling
Numerical models
Stress
patient-specific heart model
aortic stenosis
computational analysis
finite element method
Language
ISSN
2471-7819
Abstract
The main aim of this study was to evaluate the impact of simulated aortic stenosis on velocity and shear stress distribution within the patient-specific heart model by using computational Finite Element (FE) method. The three-dimensional (3D) patient-specific model of heart, including surrounding arterial and vein structures, was reconstructed based on Computed Tomography (CT) scan images in order to obtain the 3D FE mesh. Computational Fluid Dynamics (CFD) analysis was performed, with applied equivalent material characteristics and boundary conditions. Using one patient-specific heart model with clinically confirmed hypertrophic cardiomyopathy, three different cases were simulated: (i) without aortic stenosis, (ii) with 30% of aortic stenosis (mild aortic stenosis), and (iii) with 70% of aortic stenosis (severe aortic stenosis). The initial results of the study (velocity and shear stress distribution) were quantified concerning anatomical patient's structures and simulating different degrees of aortic stenosis to analyse the blood flow patterns, as well as the correlation between shear stress and aortic and left ventricular remodelling. It was found that gradient of shear stress distribution increases with stenosis degree, especially in the ascending aorta which can lead to different aortopathies and endothelial diseases. Due to the difficulties in obtaining such characteristics in vitro or in vivo, the performed computational analysis gave better insight into the biomechanics of the heart and aortic stenosis that is needed to achieve improvements in surgical repair techniques and presurgical planning.