Identifying geographic atrophy

Leanne Clevenger, Aleksandra Rachitskaya

Research output: Contribution to journalReview articlepeer-review

5 Scopus citations

Abstract

Purpose of reviewAge-related macular degeneration (AMD) is one of the leading causes of blindness and can progress to geographic atrophy (GA) in late stages of disease. This review article highlights recent literature which assists in the accurate and timely identification of GA, and monitoring of GA progression.Recent findingsTechnology for diagnosing and monitoring GA has made significant advances in recent years, particularly regarding the use of optical coherence tomography (OCT). Identification of imaging features which may herald the development of GA or its progression is critical. Deep learning applications for OCT in AMD have shown promising growth over the past several years, but more prospective studies are needed to demonstrate generalizability and clinical utility.SummaryIdentification of GA and of risk factors for GA development or progression is essential when counseling AMD patients and discussing prognosis. With new therapies on the horizon for the treatment of GA, identification of risk factors for the development and progression of GA will become critical in determining the patients who would be appropriate candidates for new targeted therapies.

Original languageEnglish
Pages (from-to)195-202
Number of pages8
JournalCurrent Opinion in Ophthalmology
Volume34
Issue number3
DOIs
StatePublished - May 1 2023

Bibliographical note

Publisher Copyright:
© 2023 Lippincott Williams and Wilkins. All rights reserved.

Keywords

  • age-related macular degeneration
  • artificial intelligence
  • geographic atrophy
  • optical coherence tomography

ASJC Scopus subject areas

  • Ophthalmology

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