Post-processing of coronary and myocardial spatial data
This work addresses the computational infeasibility of simulating haemodynamics across millions of vessels in coronary networks, providing a domain-specific solution for cardiovascular modeling.
The researchers tackled the problem of computationally simulating blood flow in the coronary arterial network by developing a data pipeline to generate computational domains from a partial arterial tree, and a method to map artery perfusion to left-ventricular subregions, validated against the American Heart Association division.
Numerical simulations of real-world phenomena require a computational scheme and a computational domain. In the context of haemodynamics, the computational domain is the blood vessel network through which blood flows. Such networks contain millions of vessels that are joined in series and in parallel. It is computationally unfeasible to explicitly simulate blood flow throughout the network. From a single porcine left coronary arterial tree, we develop a data pipeline to obtain computational domains for haemodynamic simulations in the myocardium from a graph representing a partial coronary arterial tree. In addition, we develop a method to ascertain which subregions of the left-ventricular wall are more likely to be perfused via a given artery, using a comparison with the American Heart Association division of the left ventricle for validation.