Article ; Online: Imaging geographic atrophy: integrating structure and function to better understand the effects of new treatments.
The British journal of ophthalmology
2024
Abstract: Geographic atrophy (GA) is an advanced and irreversible form of age-related macular degeneration (AMD). Chronic low grade inflammation is thought to act as an initiator of this degenerative process, resulting in loss of photoreceptors (PRs), retinal ... ...
Abstract | Geographic atrophy (GA) is an advanced and irreversible form of age-related macular degeneration (AMD). Chronic low grade inflammation is thought to act as an initiator of this degenerative process, resulting in loss of photoreceptors (PRs), retinal pigment epithelium (RPE) and the underlying choriocapillaris. This review examined the challenges of clinical trials to date which have sought to treat GA, with particular reference to the successful outcome of C3 complement inhibition. Currently, optical coherence tomography (OCT) seems to be the most suitable method to detect GA and monitor the effect of treatment. In addition, the merits of using novel anatomical endpoints in detecting GA expansion are discussed. Although best-corrected visual acuity is commonly used to monitor disease in GA, other tests to determine visual function are explored. Although not widely available, microperimetry enables quantification of retinal sensitivity (RS) and macular fixation behaviour related to fundus characteristics. There is a spatial correlation between OCT/fundus autofluorescence evaluation of PR damage outside the area of RPE loss and RS on microperimetry, showing important associations with visual function. Standardisation of testing by microperimetry is necessary to enable this modality to detect AMD progression. Artificial intelligence (AI) analysis has shown PR layers integrity precedes and exceeds GA loss. Loss of the ellipsoid zone has been recognised as a primary outcome parameter in therapeutic trials for GA. The integrity of the PR layers imaged by OCT at baseline has been shown to be an important prognostic indicator. AI has the potential to be invaluable in personalising care and justifying treatment intervention. |
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Language | English |
Publishing date | 2024-01-30 |
Publishing country | England |
Document type | Journal Article ; Review |
ZDB-ID | 80078-8 |
ISSN | 1468-2079 ; 0007-1161 |
ISSN (online) | 1468-2079 |
ISSN | 0007-1161 |
DOI | 10.1136/bjo-2023-324246 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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