Post-processing of coronary and myocardial spatial data

TL;DR

This paper presents a data pipeline and a method to generate computational domains for blood flow simulations in the heart, using coronary artery data and validating perfusion regions against established anatomical divisions.

Contribution

It introduces a novel pipeline for creating haemodynamic simulation domains from coronary artery graphs and a method to identify perfused myocardial subregions based on arterial supply.

Findings

Validated perfusion region identification against AHA divisions

Developed a scalable pipeline for coronary data processing

Enhanced accuracy of myocardial perfusion modeling

Abstract

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.