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Updated: May 7, 2026

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A Workflow to Quantitatively Determine Age-Related Macular Degeneration Lesion-Specific Variations in Fundus Autofluorescence
Published on: May 26, 2023
Microperimetry, fundus autofluorescence, and retinal layer changes in progressing geographic atrophy
Elisabetta Pilotto1, Elisa Benetti, Enrica Convento
1Department of Ophthalmology, University of Padova, Padova.
Summary
Functional and structural changes in geographic atrophy (GA) correlate. Fundus autofluorescence (FAF) patterns predict GA progression, highlighting the need for combined imaging techniques for comprehensive patient assessment.
Area of Science:
- Ophthalmology
- Medical Imaging
- Retinal Diseases
Background:
- Geographic atrophy (GA) is a progressive form of age-related macular degeneration (AMD).
- Understanding the correlation between functional and structural retinal changes is crucial for predicting GA progression.
Purpose of the Study:
- To analyze the correlation among microperimetry, inner and outer retinal layers, and fundus autofluorescence (FAF) changes in eyes with progressing GA.
- To evaluate the predictive value of FAF patterns for GA evolution.
Main Methods:
- Microperimetry, spectral-domain optical coherence tomography (SD-OCT), standard short-wavelength FAF (SW-FAF), and near-infrared-wavelength FAF (NIR-FAF) were performed.
- Analysis included FAF patterns, photoreceptor inner segment/outer segment (IS/OS) junction integrity, and retinal layer thickness changes.
Main Results:
- Retinal sensitivity decreased significantly, while dense scotomas increased.
- Outer retinal layers (ORL) thickness decreased, inversely correlated with inner retinal layers (IRL) thickness increase.
- FAF patterns correlated with retinal thickness and predicted the risk of developing dense scotomas.
Conclusions:
- Retinal sensitivity changes correlate with IRL and ORL thickness and photoreceptor IS/OS junction integrity.
- FAF patterns are relevant for predicting GA evolution.
- Combining microperimetry, FAF, and SD-OCT provides comprehensive morphologic and functional information for GA management.

