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Comparison of choroidal hypertransmission and retinal pigment epithelium loss for quantification of geographic atrophy across commonly used SD-OCT devices
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  • Published: 04 February 2026

Comparison of choroidal hypertransmission and retinal pigment epithelium loss for quantification of geographic atrophy across commonly used SD-OCT devices

  • Anna Eidenberger1,2,
  • Klaudia Birner1,2,
  • Sophie Frank-Publig1,2,
  • Johannes Schrittwieser1,2,
  • Merle Tratnig-Frankl1,2,
  • Markus Gumpinger2 &
  • …
  • Ursula Schmidt-Erfurth2 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Diseases
  • Medical research

Abstract

To compare the consistency of choroidal hypertransmission (HT) and retinal pigment epithelium (RPE) loss area measurements among three commonly used spectral-domain optical coherence tomography (OCT) devices and assess their robustness for monitoring of geographic atrophy (GA). Patients with GA were imaged during a single visit using the three different OCT: (1) Heidelberg Spectralis; (2) Zeiss Cirrus; (3) Topcon Maestro2. Expert readers manually annotated a total of 120 OCT volumes for RPE loss and HT. Dice similarity coefficients (DSC) were calculated to quantify the spatial overlap between the lesions within each OCT device. Intraclass correlation coefficients (ICC) and Bland–Altman analyses were used to assess inter-device agreement. Spatial overlap between HT and RPE loss ranged from moderate to good, with HT lesions being significantly larger than RPE loss areas across all devices (p < 0.001). Overall agreement was good for HT and RPE loss. Systematic biases emerged, with Cirrus yielding consistently smaller measurements compared to Spectralis or Maestro2. Lesion measurements demonstrated good agreement across all three OCT devices, yet device-dependent differences require caution when comparing data. Accounting for inter-device variability is an essential step toward reliable clinical endpoints and successful integration of automated OCT algorithms into clinical trials and routine AMD care.

Data availability

Data that support the findings of this study are available upon reasonable request from the corresponding author.

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Acknowledgements

The authors used ChatGPT (OpenAI, version: GPT-4o, accessed April 2025) to improve the grammar and style in this manuscript. All content edited using ChatGPT was reviewed and verified for accuracy by the authors.

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Authors and Affiliations

  1. Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria

    Anna Eidenberger, Klaudia Birner, Sophie Frank-Publig, Johannes Schrittwieser & Merle Tratnig-Frankl

  2. Laboratory for Ophthalmic Image Analysis (OPTIMA), Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria

    Anna Eidenberger, Klaudia Birner, Sophie Frank-Publig, Johannes Schrittwieser, Merle Tratnig-Frankl, Markus Gumpinger & Ursula Schmidt-Erfurth

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Contributions

AE, KB, SFP, USE: conception and design of the study. AE, KB, SFP, JS, MTF, MG: data collection and analysis. AE, USE: interpretation of the data. AE: preparation of manuscript. All authors were responsible for critical revision of the manuscript and final approval of the manuscript.

Corresponding author

Correspondence to Ursula Schmidt-Erfurth.

Ethics declarations

Competing interests

AE, KB, SFP, JS, MTF, MG: none USE: AbbVie (C), ADARx (C), Alcon (C), Alkeus (C), Allergan (C), Annexon (C), Apellis (C, F), Astellas (C), Aviceda (C), Bayer (C), Boehringer Ingelheim (C), Complement Therapeutics (C), EcoR1 (C), Galimedix (C), Genentech (F) Heidelberg Engineering (F), Janssen (C), Kodiak (C, F), Medscape (C), ONL (C), RetInSight (F), Roche (C, F), Topcon (C).

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Supplementary Material 1.

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Cite this article

Eidenberger, A., Birner, K., Frank-Publig, S. et al. Comparison of choroidal hypertransmission and retinal pigment epithelium loss for quantification of geographic atrophy across commonly used SD-OCT devices. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38182-7

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  • Received: 19 August 2025

  • Accepted: 29 January 2026

  • Published: 04 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-38182-7

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Keywords

  • Geographic atrophy
  • Hypertransmission
  • RPE loss
  • Optical coherence tomography
  • Artificial intelligence
  • Deep learning
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