Affiliation:
1. Department of Computer Science and Engineering, Wright State University, Dayton, Ohio; and
2. Departments of 2Biomedical Engineering,
3. Surgery, and
4. Cellular and Integrative Physiology, Indiana University-Purdue University, Indianapolis, Indiana
Abstract
The morphometry (diameters, length, and angles) of coronary arteries is related to their function. A simple, easy, and accurate image-based method to seamlessly extract the morphometry for coronary arteries is of significant value for understanding the structure-function relation. Here, the morphometry of large (≥1 mm in diameter) coronary arteries was extracted from computed tomography (CT) images using a recently validated segmentation algorithm. The coronary arteries of seven pigs were filled with Microfil, and the cast hearts were imaged with CT. The centerlines of the extracted vessels, the vessel radii, and the vessel lengths were identified for over 700 vessel segments. The extraction algorithm was based on a topological analysis of a vector field generated by normal vectors of the extracted vessel wall. The diameters, lengths, and angles of the right coronary artery, left anterior descending coronary artery, and left circumflex artery of all vessels ≥1 mm in diameter were tabulated for the respective orders. It was found that bifurcations at orders 9–11 are planar (∼90%). The relations between volume and length and area and length were also examined and found to scale as power laws. Furthermore, the bifurcation angles follow the minimum energy hypothesis but with significant scatter. Some of the applications of the semiautomated extraction of morphometric data in applications to coronary physiology and pathophysiology are highlighted.
Publisher
American Physiological Society
Subject
Physiology (medical),Cardiology and Cardiovascular Medicine,Physiology
Cited by
30 articles.
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