JMIR Publications

ABSTRACT

Background:

Detecting subclinical 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 artificial intelligence (AI) with non-invasive tools like retinal fundus imaging to enable opportunistic cardiovascular risk assessment. The deep-learning funduscopic atherosclerosis score (DL-FAS) is an artificial intelligence-derived biomarker developed in a previous study to detect 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 132,722 health checkup visits that included retinal fundus imaging and at least one of either carotid artery sonography or coronary artery calcium (CAC) scoring, conducted across five 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 CAC score >0 indicated the presence of coronary artery calcification. DL-FAS (range 0–1) was generated for each fundus image, and the higher score from both eyes was selected. Model discrimination for carotid atherosclerosis was assessed with area under the receiver operating characteristic curve (AUROC). 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 AUROC for detecting carotid atherosclerosis was 0.70 (95% confidence interval [CI]: 0.70–0.70), confirming the generalizability of DL-FAS across multiple centers. Multivariable logistic regression, adjusted for the PCE score, demonstrated significant associations between a 10% absolute increase in DL-FAS and both carotid atherosclerosis (odds ratio [OR] = 1.29, 95% CI: 1.28–1.31) and coronary artery calcification (OR = 1.28, 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 non-invasive biomarker for systemic atherosclerotic burden and cardiovascular risk stratification, particularly in the context of opportunistic screening.