Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul 03722, South Korea.
Ocular Epidemiology Research Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore.
J Am Med Inform Assoc. 2023 Dec 22;31(1):130-138. doi: 10.1093/jamia/ocad199.
The potential of using retinal images as a biomarker of cardiovascular disease (CVD) risk has gained significant attention, but regulatory approval of such artificial intelligence (AI) algorithms is lacking. In this regulated pivotal trial, we validated the efficacy of Reti-CVD, an AI-Software as a Medical Device (AI-SaMD), that utilizes retinal images to stratify CVD risk.
In this retrospective study, we used data from the Cardiovascular and Metabolic Diseases Etiology Research Center-High Risk (CMERC-HI) Cohort. Cox proportional hazard model was used to estimate hazard ratio (HR) trend across the 3-tier CVD risk groups (low-, moderate-, and high-risk) according to Reti-CVD in prediction of CVD events. The cardiac computed tomography-measured coronary artery calcium (CAC), carotid intima-media thickness (CIMT), and brachial-ankle pulse wave velocity (baPWV) were compared to Reti-CVD.
A total of 1106 participants were included, with 33 (3.0%) participants experiencing CVD events over 5 years; the Reti-CVD-defined risk groups (low, moderate, and high) were significantly associated with increased CVD risk (HR trend, 2.02; 95% CI, 1.26-3.24). When all variables of Reti-CVD, CAC, CIMT, baPWV, and other traditional risk factors were incorporated into one Cox model, the Reti-CVD risk groups were only significantly associated with increased CVD risk (HR = 2.40 [0.82-7.03] in moderate risk and HR = 3.56 [1.34-9.51] in high risk using low-risk as a reference).
This regulated pivotal study validated an AI-SaMD, retinal image-based, personalized CVD risk scoring system (Reti-CVD).
These results led the Korean regulatory body to authorize Reti-CVD.
视网膜图像作为心血管疾病（CVD）风险生物标志物的潜力引起了广泛关注，但此类人工智能（AI）算法的监管批准尚付诸阙如。在这项受监管的关键性试验中，我们验证了一种 AI-软件即医疗器械（AI-SaMD）——Reti-CVD 的功效，该软件利用视网膜图像对 CVD 风险进行分层。
本回顾性研究使用了心血管和代谢疾病病因研究中心-高危（CMERC-HI）队列的数据。采用 Cox 比例风险模型，根据 Reti-CVD 对 CVD 事件的预测，估计 3 级 CVD 风险组（低危、中危和高危）的风险比（HR）趋势。比较了心脏计算机断层扫描测量的冠状动脉钙（CAC）、颈动脉内膜中层厚度（CIMT）和肱踝脉搏波速度（baPWV）与 Reti-CVD 的差异。
共纳入 1106 名参与者，其中 33 名（3.0%）参与者在 5 年内发生 CVD 事件；Reti-CVD 定义的风险组（低危、中危和高危）与 CVD 风险增加显著相关（HR 趋势为 2.02；95%CI，1.26-3.24）。当将 Reti-CVD 的所有变量、CAC、CIMT、baPWV 和其他传统危险因素纳入一个 Cox 模型时，只有 Reti-CVD 风险组与 CVD 风险增加显著相关（中危风险组的 HR 为 2.40[0.82-7.03]，高危风险组的 HR 为 3.56[1.34-9.51]，以低危风险组为参照）。
这项受监管的关键性研究验证了一种 AI-SaMD，即基于视网膜图像的个性化 CVD 风险评分系统（Reti-CVD）。
这些结果促使韩国监管机构批准了 Reti-CVD。
