Machine Learning Identification Framework of Hemodynamics of Blood Flow in Patient-Specific Coronary Arteries with Abnormality.

In this study, we put forth a new deep neural network framework to predict flow behavior in a coronary arterial network with different properties in the presence of any abnormality like stenosis. An artificial neural network (ANN) model is trained using synthetic data so that it can predict the pressure and velocity within the arterial network. The data required to train the neural network were obtained from the CFD analysis of several geometries of arteries with specific features in ABAQUS software. The proposed approach precisely predicts the hemodynamic behavior of the blood flow. The average accuracy of the pressure prediction was 98.7%, and the average velocity magnitude accuracy was 93.2%. Our model can also be used to predict fractional flow reserve (FFR), which is one of the main indices to determine the severity of stenosis, and our model predicts this index successfully based on the artery features.

Computational investigation of stenosis in curvature of coronary artery within both dynamic and static models.

BACKGROUND AND OBJECTIVE: Blood flow variation during cardiac cycle is the main mechanism of atherosclerotic development which is dependent on. METHODS: The present work mainly tends to investigate stenosis effect in dynamic curvature of coronary artery. This paper presents numerical investigations on wall shear stress profiles in three-dimensional pulsatile flow through curved stenotic coronary arteries for both static and dynamic model. In order to do so, three-dimensional models related to the curved arteries with two degrees of stenosis (30% and 50%). RESULTS: Lower amount of wall shear stress is found near the inner wall of artery distal to the plaque region (stenosis) and in both percentages of stenosis the maximum wall shear stress will accrue in the middle of the stenosis; however it is much more in the higher rate of stenosis. CONCLUSIONS: A chaotic wall shear stress region is also observed downstream of stenosis in the severe stenosis case. Finally it concluded that the arterial wall motion affects the wall shear stress and the plaque formation site.