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Bioinformatics, Computational and Systems Biology

Three-Dimensional Mapping of Coronary Vasculature Geometries

(A-12) Three-Dimensional Mapping of Coronary Vasculature Geometries

Thursday, October 12, 2023

9:30 AM – 10:30 AM PDT

Location: Exhibit Hall - Row A - Poster # 12

Presenting Author(s)

AA

Aksel E. Anderson (he/him/his)

Undergraduate Researcher
University of Utah
Salt Lake City, Utah, United States

Co-Author(s)

LR

Lindsay Rupp

Graduate Research Assistant
University of Utah, United States
AB

Anna Busatto

Graduate Research Assistant
University of Utah, United States

Primary Investigator(s)

RM

Rob Macleod

Professor of Biomedical Engineering
Scientific Computing and Imaging Institute, United States

Introduction:: Cardiovascular disease is the leading cause of death globally, and one of the most impactful subsets is coronary artery disease. This condition occurs when an obstruction(s) in the coronary arteries fails to supply the heart with sufficient flow and nutrients. Understanding the geometric structure of the heart’s vascular network can provide insight into the development of coronary artery disease and its consequences to the heart. However, these vasculature geometries are often limited to the primary branches of the coronaries. Capturing deeper vasculature would improve understanding of the negative consequences of reduced blood flow, especially to myocardial electrophysiology and contractility. Our study developed a method to efficiently obtain subject-specific, high-resolution vasculature geometries.

Materials and Methods:: We obtained five explanted porcine hearts and administered the contrast agent BriteVu, which highlights the coronaries in CT images. We created three-dimensional vasculature segmentation of the CT images using the open-source software Seg3D. Furthermore, we developed a Python program to remove discontinuities in the resulting segmentations. Once the final geometries were obtained, we computed two metrics to determine the extent of the captured vasculature: (1) the number of vessel segments and (2) the smallest vessel radius.

Results, Conclusions, and Discussions:: The extent of vasculature captured via our methodology varied across subjects, as shown in Figure 1. Specifically, the total number of vessels obtained ranged between 74 - 228, with an average vessel count of approximately 169 +/- 63 vessels. The smallest vessel radius ranged between 0.30 - 0.64 mm, with an average of approximately 0.44 +/- 0.15 mm. According to previous research, the average radius of a porcine left coronary artery is approximately 3.5 mm. We were able to successfully capture vessels over 85% smaller than that of the left coronary artery. However, the number of calculated branches and smallest radius varied between experiments showing a potential inconsistency in the level of vasculature captured in this methodology (Figure 1). Such variability could be attributed to difficulty with the BrtieVu injections. Our next goal is to extend these vasculature geometries into the microvasculature level using a rule-based approach to map perfusion beds in the myocardium. This scale of subject-specific models of vasculature will permit novel predictive models of myocardial ischemia and its consequences. Overall, our developed methodology provides the ability to study coronary artery disease beyond just the primary branches. Our methodology is still limited in identifying the microvasculature, but the obtained geometries in this study are a drastic improvement. Furthermore, due to the diversity of cardiac vasculature between individuals, a patient-specific procedure can allow for more detailed research of coronary artery disease.

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