Why the study?
AI has the potential to revolutionize CCTA workflow, but evaluating the effectiveness and feasibility of AI algorithms before clinical deployment is crucial.
This expert consensus provides a framework for evaluating and implementing artificial intelligence algorithms across the entire coronary computed tomography angiography workflow.
Guides AI integration into CCTA workflows now; extends imaging standards by defining three core research design elements.
Coronary computed tomography angiography (CCTA) enables noninvasively assessment of the luminal stenosis and atherosclerotic plaque components, which has become the first-line technique for evaluating coronary artery disease. Artificial intelligence (AI) has the potential to revolutionize the entire CCTA workflow. However, it is crucial to evaluate the effectiveness and feasibility of AI algorithms before their deployment in practice. This expert consensus proposes three fundamental elements of research designs of AI in the CCTA field and offers corresponding recommendations. The consensus also reviews the existing evidence on AI applications in CCTA and provides recommendations on the current clinical applications of AI, including image acquisition and reconstruction, post-processing, diagnosis, prognostic prediction, guiding prevention and treatment, and cardiovascular disease prevention.
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Zhang et al. (2025) studied this question.
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