Multicenter External Validation of an AI-Based Funduscopic Carotid Atherosclerosis Score and Assessment of Its Association With Coronary Artery Calcification: External Validation Study.

Background: Screening for atherosclerosis is essential for early intervention, but conventional screening methods are often invasive and resource-intensive. As a result, there is growing interest in leveraging AI with noninvasive tools such as retinal fundus imaging to enable opportunistic cardiovascular risk assessment. The deep-learning funduscopic atherosclerosis score (DL-FAS) is an AI-derived biomarker, generated by a deep learning model, that was developed in a previous study to reflect the likelihood of carotid artery atherosclerosis from retinal fundus images. Objective: This study aimed to externally validate DL-FAS in a multicenter health checkup population and investigate its association with coronary artery calcification to gain deeper insights into its ability to reflect the broader systemic atherosclerotic burden. Methods: We used data from 108,982 participants in a Korean health checkup population who underwent retinal fundus imaging and at least one of either carotid artery sonography or coronary artery calcium scoring across 5 health-promotion centers operated by the Korea Association of Health Promotion between 2018 and 2021. Carotid atherosclerosis was defined by increased intima-media thickness (≥ 0.9 mm), atheroma, or stenosis. A coronary artery calcium score >0 indicated the presence of coronary artery calcification. DL-FAS (range 0-1) was generated for each fundus image, and the average score from both eyes was used as the final DL-FAS when available. The discriminative performance of DL-FAS for carotid atherosclerosis was assessed using the area under the receiver operating characteristic curve. We performed multivariable logistic regression, adjusted for the Pooled Cohort Equations (PCE) 10-year cardiovascular risk score, to quantify the associations between DL-FAS and both outcomes. Results: The area under the receiver operating characteristic curve for detecting carotid atherosclerosis was 0.700 (95% CI 0.697-0.703), confirming the generalizability of DL-FAS across multiple centers. In multivariable logistic regression adjusted for the PCE score, a 10% absolute increase in DL-FAS was associated with both carotid atherosclerosis (odds ratio 1.29, 95% CI 1.28-1.31) and coronary artery calcification (odds ratio 1.29, 95% CI 1.24-1.33). These associations remained significant among participants aged <60 years, as well as within the PCE-defined low- and moderate-risk subgroups, highlighting the potential utility of DL-FAS in populations that may benefit most from early detection and intervention. Conclusions: DL-FAS was externally validated in a large, multicenter health checkup dataset and was significantly associated with both carotid atherosclerosis and coronary artery calcification. These findings highlight its potential as a noninvasive biomarker associated with systemic atherosclerotic burden and cardiovascular risk stratification, particularly in the context of opportunistic screening.