ArticleOphthalmology science2026
A Novel Pixel-Based Spatial Modeling Framework for Mapping At-Risk Retina in Geographic Atrophy Progression.
Article in Ophthalmology science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: To develop a Pixel-based At-risk Retina Mapping (PARM) framework quantifying local geographic atrophy (GA) progression in nonexudative age-related macular degeneration and evaluate its predictive performance and statistical efficiency relative to conventional area-based measures. Design: Secondary analysis of a multicenter randomized controlled trial. Participants: Eyes with GA from the Age-Related Eye Disease Study. Methods: Annual color fundus photographs were manually segmented, registered, and converted into 10-μm pixel grids. The perilesional "at-risk" zone was empirically defined as pixels with ≥5% 1-year GA conversion probability. Within this zone, 1-year GA pixel involvement was modeled using a generalized additive model with random effects for eye and participant. Predictors included pixel-level measures (distances to GA border and foveal center) and 9 eye-level factors. Prediction accuracy was evaluated using the area under the receiver operating characteristic curve (AUC). Simulation-based power analyses compared sample size requirements between the PARM framework and conventional area-based measures for detecting a 30% treatment effect (odds ratio 0.70 for pixel conversion) at 80% power (2-sided α = 0.05). Main Outcome Measures: One-year GA pixel involvement. Results: We included 239 eyes from 161 participants. Pixels within 500 μm of the GA border had ≥5% 1-year conversion risk, defining the "at-risk" region. Shorter distance to the GA border and greater distance from the foveal center were independently associated with a higher 1-year risk of GA pixel involvement ( Conclusions: Pixel-based spatial modeling of GA progression within a 500-μm perilesional at-risk zone showed stronger predictive performance than conventional eye-level modeling and improved statistical efficiency relative to area-based measures in internal simulations by leveraging pixel-level distances to the GA border and foveal center. These findings support further evaluation of PARM framework for studying GA progression, with external validation required before clinical-trial implementation. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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