Post-processing of coronary and myocardial spatial data

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.

Authors

Institutions

Publication Details

Journal
Computers in Biology and Medicine
Published
2025-08-11
DOI
https://doi.org/10.1016/j.compbiomed.2025.110868
Primary Topic
Cardiovascular Health and Disease Prevention
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Post-processing of coronary and myocardial spatial data

Megan Miller, Justin MacKenzie, Mette S. Olufsen, N. A. Hill
Computers in Biology and Medicine
Cardiovascular Health and Disease Prevention
article

Post-processing of coronary and myocardial spatial data

Megan Miller, Justin MacKenzie, Mette S. Olufsen, N. A. Hill
article en

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.

Computers in Biology and MedicineVol. 196(Pt C)
North Carolina State University (US), Virginia Military Institute (US), University of Glasgow (GB)
National Science Foundation, Engineering and Physical Sciences Research Council
Good health and well-being
Openalex Percentile: Top 68%
Cardiovascular Health and Disease Prevention
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.