The Role of AI in Early Detection of Life-Threatening Diseases: A Retinal Imaging Perspective

TL;DR

Retinal imaging offers a non-invasive window into systemic health, enabling earlier detection of life-threatening diseases through high-resolution modalities like OCT/OCTA and adaptive optics, augmented by AI-driven analysis. The paper synthesizes advances across cardiovascular, neurodegenerative, metabolic, hematologic, renal, and hepatobiliary domains, and evaluates diagnostic performance, external validation, and clinical workflow integration. It proposes a roadmap for multicenter standardization, prospective validation, and seamless incorporation of retinal screening into primary and specialty care to enable precision prevention and early intervention. The work highlights the practical impact of retinal oculomics for risk stratification, longitudinal monitoring, and population-scale screening, while calling out data-sharing, ethics, and regulatory considerations as key enablers.

Abstract

Retinal imaging has emerged as a powerful, non-invasive modality for detecting and quantifying biomarkers of systemic diseases-ranging from diabetes and hypertension to Alzheimer's disease and cardiovascular disorders but current insights remain dispersed across platforms and specialties. Recent technological advances in optical coherence tomography (OCT/OCTA) and adaptive optics (AO) now deliver ultra-high-resolution scans (down to 5 μm ) with superior contrast and spatial integration, allowing early identification of microvascular abnormalities and neurodegenerative changes. At the same time, AI-driven and machine learning (ML) algorithms have revolutionized the analysis of large-scale retinal datasets, increasing sensitivity and specificity; for example, deep learning models achieve > 90 \% sensitivity for diabetic retinopathy and AUC = 0.89 for the prediction of cardiovascular risk from fundus photographs. The proliferation of mobile health technologies and telemedicine platforms further extends access, reduces costs, and facilitates community-based screening and longitudinal monitoring. Despite these breakthroughs, translation into routine practice is hindered by heterogeneous imaging protocols, limited external validation of AI models, and integration challenges within clinical workflows. In this review, we systematically synthesize the latest OCT/OCT and AO developments, AI/ML approaches, and mHealth/Tele-ophthalmology initiatives and quantify their diagnostic performance across disease domains. Finally, we propose a roadmap for multicenter protocol standardization, prospective validation trials, and seamless incorporation of retinal screening into primary and specialty care pathways-paving the way for precision prevention, early intervention, and ongoing treatment of life-threatening systemic diseases.

Figures (9)

• Figure 1: Bird's-eye view of diseases and parameter prediction from retinal imaging.
• Figure 2: Heatmap of retinal imaging modalities (fundus, OCT, OCTA, AO) versus systemic disease categories (AD, PD, MS, DR, hypertension, CVD, CKD, hepatobiliary disease, anemia). Colors indicate relative biomarker strength from none (0) to strong (3).
• Figure 3: Representative retinal changes observed in hypertensive retinopathy. Key features include retinal hemorrhages, neovascularization, arteriolar narrowing and bundling, micro-aneurysms, hard exudates, cotton-wool spots, and optic disc swelling. These vascular abnormalities reflect the impact of systemic hypertension on the retinal microvasculature and are critical indicators for the diagnosis and monitoring of hypertensive damage.
• Figure 4: Representative retinal images showing Branch Retinal Vein Occlusion (BRVO). Key pathological features include hemorrhage and edema within the retinal layers, resulting from obstruction of the retinal venous outflow. These changes can lead to vision impairment and are critical indicators in the diagnosis and management of BRVO.
• Figure 5: Comparison of a normal eye and an eye affected by glaucoma, highlighting structural differences in the optic nerve region. In the glaucomatous eye, the optic cup appears enlarged relative to the optic disc, indicating optic nerve head cupping Ṫhis structural change is a hallmark of glaucoma, often resulting from increased intraocular pressure and associated with progressive retinal ganglion cell loss.