Imaging biomarkers including drusen characteristics, reticular pseudodrusen, hyperreflective foci, and choroidal thickness have shown associations with AMD progression risk. However, predicting which individual patients will progress rapidly enough to justify earlier intervention remains imperfect.
Why biomarkers matter in AMD
Age-related macular degeneration progresses unpredictably. Some patients remain stable for years; others lose vision rapidly. Identifying high-risk individuals could enable closer monitoring, earlier treatment, and better clinical trial design. Imaging features visible on OCT, fundus autofluorescence, and OCTA offer potential prognostic information.
Drusen characteristics
Larger drusen, particularly those exceeding 125 micrometers, and high drusen volume correlate with higher progression risk. Drusen with specific internal reflectivity patterns on OCT may indicate different risk levels. However, many eyes with large drusen never progress, and some eyes with small drusen do—drusen alone have limited positive predictive value.
Reticular pseudodrusen
Also called subretinal drusenoid deposits, these appear as distinct lesions on multimodal imaging, located above the RPE rather than below. Their presence associates with faster progression to advanced AMD and particularly geographic atrophy. Detection sensitivity varies by imaging modality—near-infrared reflectance and OCT are most sensitive.
Hyperreflective foci
These small, bright spots on OCT represent RPE disruption, migrated RPE cells, or inflammatory cells. Increasing number and volume of hyperreflective foci correlate with progression in some studies. Automated quantification is challenging, and clinical utility for individual patient predictions is not established.
Choroidal thickness and vascularity
Reduced choroidal thickness and decreased choriocapillaris density on OCTA have been associated with AMD presence and progression. However, choroidal thinning also occurs with normal aging and myopia, limiting specificity. Whether choroidal measurements add predictive value beyond other biomarkers is debated.
Geographic atrophy growth rate
Measuring existing GA area and growth rate helps predict future vision loss and serves as an endpoint in clinical trials. But identifying biomarkers that predict imminent GA development in intermediate AMD—before it appears—has been more elusive. Combinations of biomarkers may perform better than single features.
From association to prediction
Many imaging features associate with AMD progression in population studies. Turning these into clinically useful prediction tools for individual patients requires high positive predictive value, which most single biomarkers lack. Machine learning models combining multiple features show promise but need prospective validation.
Clinical application questions
Even with accurate prediction, clinical decisions depend on actionable interventions. AREDS2 supplementation reduces progression risk modestly. Anti-VEGF treatment is used after neovascularization develops. Would earlier intervention in high-risk eyes improve outcomes? This question remains largely unanswered, limiting the clinical value of prognostic biomarkers until preventive treatments improve.
Evidence should be inspectable.
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