Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
AI-based identification of photoreceptor degeneration and retinal pigment epithelial atrophy in inherited macular dystrophies
Author Affiliations & Notes
  • Ulrich Kellner
    Rare Retinal Disease Center, MVZ Augenärztliches Diagnostik- und Therapiecentrum Siegburg GmbH, Siegburg, Germany
    RetinaScience, Bonn, Germany
  • Simone Kellner
    Rare Retinal Disease Center, MVZ Augenärztliches Diagnostik- und Therapiecentrum Siegburg GmbH, Siegburg, Germany
    RetinaScience, Bonn, Germany
  • Heidi Stöhrq
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany
  • Christina Kiel
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany
  • Silke Weinitz
    Rare Retinal Disease Center, MVZ Augenärztliches Diagnostik- und Therapiecentrum Siegburg GmbH, Siegburg, Germany
    RetinaScience, Bonn, Germany
  • Ghazaleh Farmand
    Rare Retinal Disease Center, MVZ Augenärztliches Diagnostik- und Therapiecentrum Siegburg GmbH, Siegburg, Germany
  • Bernhard Hf Weber
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany
    Institute of Clinical Human Genetics, Universitatsklinikum Regensburg, Regensburg, Bayern, Germany
  • Footnotes
    Commercial Relationships   Ulrich Kellner None; Simone Kellner None; Heidi Stöhrq None; Christina Kiel None; Silke Weinitz None; Ghazaleh Farmand None; Bernhard Weber None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 3099. doi:
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      Ulrich Kellner, Simone Kellner, Heidi Stöhrq, Christina Kiel, Silke Weinitz, Ghazaleh Farmand, Bernhard Hf Weber; AI-based identification of photoreceptor degeneration and retinal pigment epithelial atrophy in inherited macular dystrophies. Invest. Ophthalmol. Vis. Sci. 2024;65(7):3099.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Progression of photoreceptor degeneration and retinal pigment epithelial (RPE) atrophy are the primary cause of functional loss in inherited macular dystrophies (IMD). Automated detection of photoreceptor degeneration and RPE atrophy would be helpful to analyze the natural course of IMD and provide relevant information for future treatment options.

Methods : Volume scan macular OCT (49 scans, 5,5x5,5 mm, Heidelberg Engineering, Germany) of 158 patients with genetically confirmed IMD were analyzed using the GA Monitor (RetInSight, Vienna, Austria) outside its intended use. All patients were examined at least once with OCT, fundus and near-infrared autofluorescence. In 74 patients one or more follow-up OCTs were available.

Results : IMD were associated with different genes (ABCA4: 70, PRPH2: 26, BEST1: 17, RS1: 14, RP1L1: 10 and several rare genes). In total, 859 OCTs could be analyzed of 310 eyes. Photoreceptor degeneration and RPE atrophy were reliably detected. In comparison with fundus autofluorescence OCT-based detection of RPE atrophy was superior especially in foveal and parafoveal areas. The analysis of progression was possible in 139 eyes of 74 patients with a time range between 1 and 12 years. The rate of progression varied between associated genes, but also between patients with the same associated gene. Photoreceptor degeneration preceded RPE atrophy, and during progression RPE atrophy developed in areas with prior photoreceptor degeneration.

Conclusions : AI-based identification of photoreceptor degeneration and RPE atrophy facilitates a detailed analysis of disease stage and progression. The natural course of the IMD can be monitored and the results can be used for patient counselling as well as future treatment planning.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

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