Work

A Simplified Classification for Age-Related Macular Degeneration Based on Optical Coherence Tomography

Year: 2026

Type: article

Abstract: Background and Objective As optical coherence tomography (OCT) has enabled the identification of an expanding set of age-related macular degeneration (AMD) risk biomarkers and become central to routine clinical practice, there remains a need for a simplified grading scheme that allows physicians to communicate and synchronize AMD grading directly from standard OCT imaging rather than relying on traditional color fundus imaging. This study aims to establish a standardized OCT-based AMD classification that balances diagnostic accuracy with practicality for use across clinical and research settings. Patients and Methods Spectral-domain optical coherence tomography scans were independently graded by two retinal specialists following the newly proposed Stanford OCT-Based AMD Classification (SOAC). Discrepancies were adjudicated by a third independent retinal specialist. Intergrader agreement was assessed using weighted kappa coefficients. Results Among the 109 eyes from 108 patients (mean age 79.61□±□7.57 years; 41.7% male, 58.3% female), AMD staging based on SOAC was distributed as follows: normal aging in 9 patients (8.3%), early AMD in 16 (14.7%), intermediate AMD in 32 (29.4%), neovascular AMD (nAMD) in 18 (16.5%), geographic atrophy (GA) in 20 (18.3%), and combined nAMD and GA in 14 (12.8%). The overall intergrader agreement demonstrated robust consistency, with a weighted kappa value of 0.95 (95% CI: 0.92–0.98), signifying excellent intergrader reliability and reinforcing the validity of SOAC. Conclusion SOAC provides a standardized, OCT-based framework for AMD grading that demonstrates high intergrader agreement. By enabling consistent classification from commonly acquired OCT scans, SOAC supports reliable disease staging and facilitates integration across clinical studies and translational research. As imaging and molecular data continue to expand, SOAC can serve as a common OCT-based reference for phenotype refinement and longitudinal AMD studies. Key questions What is already known on this topic? Existing classifications of age-related macular degeneration (AMD) rely heavily on color fundus photography and inconsistently incorporate optical coherence tomography (OCT) biomarkers, despite OCT’s superior resolution for detecting subclinical structural changes. What this study adds? This study introduces an OCT-based classification framework that consolidates key biomarkers with proven prognostic relevance into a simplified, tiered staging protocol. By prioritizing a curated set of evidence-supported, high-risk OCT biomarkers, the Stanford OCT-Based AMD Classification (SOAC) provides a common framework and shared language for OCT-based AMD staging, facilitates longitudinal monitoring, and reduces intergrader variability through standardized reporting guidelines. The framework deliberately balances clinical practicality with scientific rigor, excluding less significant or potentially confusing features to ensure scalability across diverse clinical and research settings. How this study might affect research, practice or policy? SOAC provides an OCT-based framework for AMD staging with high inter-physician agreement. This is particularly important in real-world clinical and translational research settings, where color fundus photography is not always available. By offering a common OCT-based reference, SOAC reduces diagnostic variability and supports more consistent AMD staging across clinicians and studies. The classification incorporates up-to-date, evidence-based, high-risk OCT features associated with disease progression and is designed to be scalable, allowing integration with emerging multimodal data, including AI-driven imaging analysis and molecular profiling. By bridging advances in retinal imaging with practical clinical application, SOAC lays the groundwork for improved risk stratification, longitudinal outcome studies, and more standardized reporting in AMD.

Source: Ophthalmic surgery, lasers & imaging retina

DOI: 10.3928/23258160-20260409-02