AI-based detection and classification of anomalous aortic origin of coronary arteries using coronary CT angiography images.

ABSTRACT: Anomalous aortic origin of the coronary artery (AAOCA) is a rare cardiac condition that can lead to ischemia or sudden cardiac death, yet it is often overlooked or falsely classified in routine coronary CT angiography (CCTA). Here, we developed, validated, externally tested, and clinically evaluated a fully automated artificial intelligence (AI)-based tool for detecting and classifying AAOCA in 3D-CCTA images. The discriminatory performance of the different models achieved an AUC ≥ 0.99, with sensitivity and specificity ranging 0.95-0.99 across all internal and external testing datasets. Here, we present an AI-based model that enables fully automated and accurate detection and classification of AAOCA, with the potential for seamless integration into clinical workflows. The tool can deliver

SUBMITTER: Shiri I 

PROVIDER: S-EPMC11961624 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature