Evaluation of fundus photography as a Prognostic Tool in age-related macular degeneration
DOI:
https://doi.org/10.5281/zenodo.22812219Keywords:
fundus photography, age-related macular degeneration, fundus autofluorescence, AREDS severity scale, deep learningAbstract
Background: Fundus photography has anchored age-related macular degeneration (AMD) staging since the earliest clinicopathological classification systems, and the Age-Related Eye Disease Study (AREDS) severity scales, derived entirely from stereoscopic color fundus photographs, remain the basis for multi-year risk stratification [5,7].
Objective: This review evaluates the evidence that features visible on fundus photographs, including drusen size, pigmentary abnormality, and fundus autofluorescence (FAF) pattern, carry genuine prognostic value for progression to geographic atrophy and conversion to neovascular AMD.
Methods: We synthesized natural-history cohorts, AREDS and AREDS2 ancillary analyses, FAF pattern studies, and deep-learning re-analyses of legacy fundus photograph archives addressing photographic prediction of AMD progression and vision loss.
Findings: AREDS severity scores predict 5-year progression to advanced AMD ranging from roughly 0.5% to 50% across risk categories [6]; FAF pattern predicts geographic atrophy enlargement rate, with banded and diffuse patterns enlarging fastest [12,11]; and convolutional neural networks trained on archived photographs now match or exceed expert grading, in some cases predicting neovascular conversion months before clinical exudation [25,29].
Conclusions: Fundus photography functions as a genuine prognostic instrument in AMD rather than a purely diagnostic record, and automated grading tools are likely to extend, rather than replace, its role as the most widely accessible entry point into individualized AMD risk assessment [27,26].
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