Evaluation of an artificial intelligence model for opportunistic calculation of Agatston score on non-gated computed tomography of the chest

ImportanceThe Agatston score is a measure of cardiovascular disease traditionally calculated on cardiac gated computed tomography (CT) of the chest. Cardiac gated CT is resource-intensive, can be hard to access, and involves extra radiation exposure. Artificial intelligence (AI) can be used to opportunistically calculate Agatston score on non-gated CTs performed for other indications. ObjectiveThis study compared the accuracy of an AI model (Riverain Technologies ClearRead CT CAC) at calculating Agatston scores on non-gated CTs to both consensus radiologist interpretations on the same CTs and Agatston scores from paired cardiac gated CTs. DesignA retrospective standalone performance assessment was conducted on a dataset of non-contrast CT chest cases acquired between January 2022 and December 2023. SettingThe study was conducted at five hospitals in the United States. ParticipantsThe cohort included non-gated CTs from 491 patients. It was enriched to ensure a representation of disease severity by selecting approximately two-thirds of patients using the originally reported Agatston score on a paired cardiac gated CT within the study timeframe. Main Outcome(s) and Measure(s)The study compared the agreement of Agatston categories (0, 1-99, 100-399 and [≥]400) between the AI model and ground truth radiologists or original radiology reports using the quadratic weighted Kappa coefficient. Exposure(s)Each non-gated CT case was interpreted independently by three radiologists to establish consensus interpretations. Each CT was then interpreted by the AI model. The Agatston scores for paired cardiac gated CTs were obtained from original radiology reports. ResultsThe agreement between the AI model and ground truth radiologists was 0.959 (95% CI: 0.943-0.975). This result was broadly consistent across sex, age group, race, ethnicity and CT scanner manufacturer subgroups. The agreement between the AI model and paired cardiac gated CT was 0.906 (95% CI: 0.882-0.927). Conclusions and RelevanceThe assessed AI model accurately calculated Agatston scores on non-gated CTs and produced similar scores to paired cardiac gated CTs. Its use could broaden screening for atherosclerotic cardiovascular disease, enabling opportunistic screening on CTs captured for other indications.