Computational fluid dynamics modeling of coronary artery blood flow using OpenFOAM: Validation with the food and drug administration benchmark nozzle model.
Sajid AliChien-Yi HoChen-Chia YangSzu-Hsien ChouZhen-Ye ChenWei-Chien HuangTzu-Ching ShihPublished in: Journal of X-ray science and technology (2024)
Cardiovascular disease (CVD), a global health concern, particularly coronary artery disease (CAD), poses a significant threat to well-being. Seeking safer and cost-effective diagnostic alternatives to invasive coronary angiography, noninvasive coronary computed tomography angiography (CCTA) gains prominence. This study employed OpenFOAM, an open-source Computational Fluid Dynamics (CFD) software, to analyze hemodynamic parameters in coronary arteries with serial stenoses. Patient-specific three-dimensional (3D) models from CCTA images offer insights into hemodynamic changes. OpenFOAM breaks away from traditional commercial software, validated against the FDA benchmark nozzle model for reliability. Applying this refined methodology to seventeen coronary arteries across nine patients, the study evaluates parameters like fractional flow reserve computed tomography simulation (FFRCTS), fluid velocity, and wall shear stress (WSS) over time. Findings include FFRCTS values exceeding 0.8 for grade 0 stenosis and falling below 0.5 for grade 5 stenosis. Central velocity remains nearly constant for grade 1 stenosis but increases 3.4-fold for grade 5 stenosis. This research innovates by utilizing OpenFOAM, departing from previous reliance on commercial software. Combining qualitative stenosis grading with quantitative FFRCTS and velocity measurements offers a more comprehensive assessment of coronary artery conditions. The study introduces 3D renderings of wall shear stress distribution across stenosis grades, providing an intuitive visualization of hemodynamic changes for valuable insights into coronary stenosis diagnosis.
Keyphrases
- coronary artery
- coronary artery disease
- blood flow
- pulmonary artery
- computed tomography
- cardiovascular disease
- global health
- type diabetes
- end stage renal disease
- percutaneous coronary intervention
- ejection fraction
- magnetic resonance imaging
- chronic kidney disease
- newly diagnosed
- high resolution
- metabolic syndrome
- public health
- aortic stenosis
- deep learning
- pulmonary hypertension
- mass spectrometry
- coronary artery bypass grafting
- peritoneal dialysis
- left ventricular
- convolutional neural network
- drug administration
- pulmonary arterial hypertension