Assessment of anomalous coronary arteries by imagers and surgeons: Comparison of imaging modalities

Farooqi KM, Nees SN, Smerling J, Senapathi SH, Lorenzoni R, Pavlicova M, Einstein AJ, Bacha EA, Kalfa D, Chai PJ.Ann Thorac Surg. 2020 May 23:S0003-4975(20)30742-6. doi: 10.1016/j.athoracsur.2020.03.124. Online ahead of print.PMID: 32454021

 

Abstract

Background: Anomalous aortic origin of a coronary artery (AAOCA) is associated with sudden cardiac death. High risk characteristics are most commonly assessed using two dimensional (2D) echocardiogram (echo) or cardiac computed tomography (CT). We hypothesize that these characteristics will be more accurately assessed when they are presented in the form of a 3D digital model.

Methods: 14 participants including cardiothoracic surgeons and cardiac imaging specialists assessed image representations including echo, CT images and a 3D digital model, from six patients who had undergone AAOCA repair. Accuracy of assessment was evaluated by comparing responses with operative findings, i.e. the “gold standard”.

Results: The reported type of AAOCA was most accurately assessed on CT (100%) and 3D models (92.31%) as compared to echo (80.77%). The accuracy of the AAOCA course was highest on CT (91.03%), 80.77% on 3D model and lowest on echo (61.54%). The accuracy of intramurality was low across all imaging modalities (17.95% echo, 29.49% CT and 21.79% 3D model). Accurate assessment of a separate AAOCA ostium was highest on 3D models (97.40%). Ostial stenosis was more accurately assessed on 3D models (56.41%). When accuracy was separated by subspecialty, CT and 3D models were more accurately assessed by all participants regardless of training.

Conclusions: Cardiac imagers and congenital cardiothoracic surgeons most accurately assessed AAOCA presence, type and course on cardiac CT and 3D models. 3D models were superior in representation of ostial characteristics. CT and 3D models are overall more accurately assessed by specialists regardless of training.

 

source:https://pubmed.ncbi.nlm.nih.gov/32454021/

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