Abstract

Computational hemodynamic (CH) characteristics play a central role in the onset and expansion of atherosclerotic plaques in the coronary main arteries. This study has explored the effects of hemodynamic properties especially coronary arterial wall tangential stresses on various healthy and diseased patient-based coronary artery models based on coronary computed tomography angiography (CCTA) imaging. The key components of the work are the CCTA image acquisition, accurate three-dimensional (3 D) model segmentation, reconstruction, appropriate grid generation, CH simulations, and analysis of the results by using open-source techniques. The CH simulation results have produced hemodynamic variables, including velocity magnitude (VM), mean arterial pressure difference, wall shear stress (WSS), time-averaged WSS (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and finally, computational fractional flow reserve (cFFR), that allow the pathophysiological conditions in patient-based coronary models. The VM, mean pressure difference, and WSS indices have yielded consistent simulation results for predicting the severity conditions of coronary diseases. We have compared our cFFR results with the published results and observed that the WSS indices were a good alternative approach for measuring the severity of coronary lesions. The CH results allow a medical expert to estimate the severity of a lumen area and stenosis physiological blood flow conditions in a non-invasive way.

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