Language
English
Publication Date
1-1-2025
Journal
Frontiers in Cardiovascular Medicine
DOI
10.3389/fcvm.2025.1721523
PMID
41704290
PMCID
PMC12907430
PubMedCentral® Posted Date
2-2-2026
PubMedCentral® Full Text Version
Author MSS
Abstract
Introduction: Anomalous aortic origin of a coronary artery (AAOCA) is associated with sudden cardiac death. The intramural (IM) length is considered high-risk, yet radiologic measurements by computed tomography angiography (CTA) show variable agreement with measurements at surgery. We aimed to develop a semi-automatic computational method to estimate IM length in a retrospective cohort of surgical AAOCA patients.
Methods: In 58 patients [49 right(R), 9 left(L)], CTA images were used to generate 3D segmentations of the aorta and a centerline of the anomalous coronary. The distance from the centerline to the aortic segmentation was calculated. The IM length was estimated from a transition point in the derivative of the distance curve and compared to radiologic and surgical measurements.
Results: Our method demonstrated an overall root-mean-square error (RMSE) of 3.4 mm, comparable to radiologic estimates (3.2 mm). For L-AAOCA subjects, our method showed lower root-mean-square error compared to radiologic estimates (our method: 3.6 mm, radiologic: 4.7 mm). For R-AAOCA subjects, the RMSE was higher in our method compared to radiologic estimates (our method: 3.4 mm, radiologic: 2.8 mm).
Conclusion: This is a pilot study of a computational approach to measure intramural length that is shown to be accurate relative to surgical measurements. Computational methods that represent and quantify morphology, including acute take-off angle, ostial characteristics, minimal luminal area, and intramural length, may be helpful for risk stratification and surgical planning in AAOCA.
Keywords
anomalous aortic origin of a coronary artery, computed tomography angiography, intramural length, risk stratification, sudden cardiac arrest
Published Open-Access
yes
Recommended Citation
Shah, Vikram; Ferrino, Lauren; Reaves-O'Neal, Dana; et al., "A Computational Approach for Intramural Length Estimation in Anomalous Aortic Origin of a Coronary Artery" (2025). Faculty, Staff and Students Publications. 7502.
https://digitalcommons.library.tmc.edu/baylor_docs/7502