Coronary artery disease is the second leading cause of death in the United States. Models of coronary arteries have been widely used to understand the hemodynamic drivers of the disease. Fluid‐Structure Interaction (FSI) modeling of the coronary arteries provides information on both the forces that are created by the blood and the forces distributed into the artery wall. A better understanding of the artery health and markers of disease progression may be discernable by performing a spatiotemporal analysis of the coronary artery hemodynamics and solid mechanics. The goals of this investigation were: 1) to create a three‐dimensional (3D) FSI model of the left anterior descending coronary artery and 2) to evaluate disease progression using multiple mechanical descriptors in both space and time domains using COMSOL Multiphysics. The 3D geometry reconstruction was based on a patient's computer tomography angiography (CTA) data. The fluid domain representing the blood volume and solid domain representing the artery wall were fully coupled. The artery wall was modeled using a 5‐parameter hyperelastic Mooney‐Rivlin material model. We assessed time averaged wall shear stress, wall shear stress gradient, and oscillatory shear index (OSI) along the fluid‐structure interface. Artery wall strain (along the three principal directions) and Von‐Mises stress were assessed within regions of the solid (i.e., the vascular wall). A virtual calculation of the Fractional Flow Reserve (vFFR), which is used for clinical diagnosis of cardiac ischemia, was performed. These analyses were collected from three different regions along the artery, proximal to, at, and distal to an area of narrowing in the artery throughout the cardiac cycle. Clear differences were observed between the regions. The distal region to the narrowing had variable OSI and high time averaged wall shear stress, but the lowest average Von‐Mises stress. The vFFR was 0.96 which is comparable to the average FFR in the left anterior descending artery. This type of model reconstruction and analysis can be used to evaluate plaque vulnerabilities. It may also have clinical implications when assessing the patient's specific coronary artery mechanical environment that may lead to plaque development and instability.
In cases of severe cardiac stenosis, the selection of treatment options including angioplasty, stent insertion, and bypass surgery are based on cardiac diagnosis provided by electrocardiograms, stress tests, and angiograms. Although these diagnostic tools are all vital, it is still difficult to determine the true extent to which normal blood flow has been compromised. To date, a clear guideline for aggressive intervention does not exist, as stenosis characteristics can vary greatly between patients. Plaque composition, compressibility, and shape are all factors that can modify a patient's risk of incurring a life‐threatening cardiac event in the near future. Our work aims to establish a streamlined computational model that can provide accurate estimation of dynamic shear stress and tensile strain on a plaque based on a patient's specific geometry. Together with flow information provided by 4D cardiac MRI, information from the computational model will allow a cardiologist to make better informed decisions regarding therapeutic options for patient cardiac health.The goal of this undergraduate research project was to determine the most effective method for 3D reconstruction and segmentation of the heart and coronary arteries from patient‐specific CTA (computed tomography angiography) data. The resulting 3D geometry will be imported into COMSOL, a computational fluid dynamics software, for hemodynamics and stress‐strain analysis.Patients' CTA data was provided by the Cardiac Imaging Department of the St. Francis Hospital (with IRB approval). A set of 2097 images were imported into a 3D reconstruction software, 3D Slicer (http://www.slicer.org), and visualized in sagittal, axial, and coronal views. By scanning through images in each plane, major components of the heart (i.e., atria, ventricles, aorta, coronary arteries) were identified manually. 3D reconstruction and segmentation were accomplished using a seeding procedure in which each part of the heart was carefully selected and identified as an individual component. 3D Slicer then generated a 3D‐reconstructed geometry of the heart from seeds. Proper seeding allowed different components of the heart to be visualized individually in the 3D viewer, enabling isolation of the coronary arteries from the whole heart model.Preliminary results showed a 3D model of the whole heart from CTA data with the left main coronary isolated. Manual segmentation was found to be challenging because coronary artery branches are embedded within the cardiac muscle. It was demonstrated to be efficient to refine seeds for coronary artery identification and segmentation by carefully examining the 3D model and performing several iterations of correction. The coronary artery geometry generated in 3D Slicer is then processed by a Vascular Modeling Tool Kit (VMTK, an open source software) to generate the proper geometries (in .stl format) needed for COMSOL, for hemodynamics modeling and analysis.As methods for reconstruction and segmentation are further refined, computational modeling will be used as a high throughput tool to generate useful information on stress/strain conditions within the coronary arteries, moving toward our goal of streamlined personalized cardiac treatment.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
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