Background: To investigate the effectiveness of an artificial intelligence (AI)-based computer-aided detection (CAD) system in identifying incidental lung cancer on cardiac computed tomography (CT) scans and to compare its performance with that of radiologists.Methods: In this retrospective, multicenter study, 652 cardiac CT scans from 581 patients subsequently diagnosed with lung cancer were analyzed.A commercial AI-CAD system was employed to detect pulmonary lesions on cardiac CT.The detection rate of AI-CAD was compared to that of the radiologist, based on the radiology report, as well as to the detection rate when combining AI-CAD and the radiologist.The characteristics of the lesions detected and missed by the radiologist and AI-CAD were compared.Results: Radiologists and AI-CAD demonstrated similar detection rates for lung cancer (76.2% vs. 77.4%,P = 0.551).However, combining radiologists and AI-CAD significantly improved the detection rate to 90.4% (P 100 days, with 78.2% leading to stage progression.AI-CAD identified 58.5% of these diagnostic delays.Conclusion: AI-CAD demonstrated the potential to improve the detection rate of incidental lung cancer by identifying a subset of lesions that were initially overlooked by radiologists on cardiac CT.It exhibited particular strength in identifying early-stage cancers and small, subsolid lesions.
Son et al. (Thu,) studied this question.