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CompletedNCT05208931Updated Apr 13, 2023

Development of an Optimal Algorithm for the Management of Patients With Retinal Pigment Epithelium Detachment in Neovascular Age-related Macular Degeneration Using Artificial Intelligence

An observational study in Neovascular Age-related Macular Degeneration, sponsored by The S.N. Fyodorov Eye Microsurgery State Institution. Completed at 1 site in Russian Federation. Open to participants aged 18 Years to 80 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2023-04-13.

Sponsored by The S.N. Fyodorov Eye Microsurgery State Institution · Observational

Study type
Observational
Model
Case-control
Time perspective
Retrospective
Enrollment
300
Ages
18 Years to 80 Years
Sex
All
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Study summary

The study involves the development of an algorithm for predicting anatomical and functional results of therapy with angiogenesis inhibitors in patients with retinal pigment epithelium detachments in neovascular age-related macular degeneration, based on primary optical coherence tomography of the macular zone and clinical data.

Read the detailed description

Patients were divided into 3 groups according to the results of therapy: adhesion of detachment, lack of adherence to detachment, rupture of detachment. For these groups, OCT images of the macular zone with maximum detachment before therapy are selected. These images, along with other clinical parameters, are input to the algorithm. The result is one of the 3 treatment outcomes listed above. The methods that will be used to develop the algorithm include methods for processing and transforming data, deep machine learning, metrics for calculating the accuracy of algorithms.

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Conditions studied

  • Neovascular Age-related Macular Degeneration

Keywords

  • Machine learning
  • Artificial intelligence
  • anti-VEGF therapy
  • AMD
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In context

Macular Degeneration

1,474 studies on the registry are indexed under Macular Degeneration; 206 are open to participants now.

This study's enrollment of 300 is above the median of 106 across 421 observational studies indexed under Macular Degeneration.

Browse Macular Degeneration studies →

Lead sponsor

The S.N. Fyodorov Eye Microsurgery State Institution is the lead sponsor of 11 studies on the registry; 2 are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
18 Years to 80 Years
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Probability sample

Study population

Patients with retinal pigment epithelium detachments with age-related neovascular macular degeneration

Inclusion criteria

  • Linear B - scan through the macular area with the longest detachment
  • Other pathologies

Exclusion criteria

Exclusion criteria:

  • Images without detachment
  • Images on which it is possible to diagnose the need for therapy only in the presence of additional factors not considered in the study.
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Study design

Observational model
Case-control
Time perspective
Retrospective
Enrollment
300 participants (actual)

Groups and cohorts

  • adhesion

    the group in which the adhesion of neuroepithelial detachment was observed after Anti-vascular endothelial growth factor therapy

    Procedure: Anti-vascular endothelial growth factor therapy

  • no adhesion

    group in which there was no adherence of neuroepithelial detachment after Anti-vascular endothelial growth factor therapy

    Procedure: Anti-vascular endothelial growth factor therapy

  • разрыв

    group in which neuroepithelial detachment rupture was observed after anti-vascular endothelial growth factor therapy

    Procedure: Anti-vascular endothelial growth factor therapy

Interventions

  • ProcedureAnti-vascular endothelial growth factor therapy

    0.05 ml anti-VEGF, intravitreal, monthly

    Also known as: anti-VEGF

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What researchers measure

Primary outcomes

  1. Prediction algorithm

    Neural network classifier

    Time frame: 1.09.2022

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Study locations

1 site
  • The S.N. Fyodorov Eye Microsurgery State Institution
    Krasnodar, 350012, Russian Federation
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References and documents

Publications

  • Rohm M, Tresp V, Muller M, Kern C, Manakov I, Weiss M, Sim DA, Priglinger S, Keane PA, Kortuem K. Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration. Ophthalmology. 2018 Jul;125(7):1028-1036. doi: 10.1016/j.ophtha.2017.12.034. Epub 2018 Feb 14. PubMed 29454659 ↗
  • Prahs P, Radeck V, Mayer C, Cvetkov Y, Cvetkova N, Helbig H, Marker D. OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications. Graefes Arch Clin Exp Ophthalmol. 2018 Jan;256(1):91-98. doi: 10.1007/s00417-017-3839-y. Epub 2017 Nov 10. PubMed 29127485 ↗
  • Schmidt-Erfurth U, Bogunovic H, Sadeghipour A, Schlegl T, Langs G, Gerendas BS, Osborne A, Waldstein SM. Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration. Ophthalmol Retina. 2018 Jan;2(1):24-30. doi: 10.1016/j.oret.2017.03.015. Epub 2017 May 31. PubMed 31047298 ↗
  • Bogunovic H, Montuoro A, Baratsits M, Karantonis MG, Waldstein SM, Schlanitz F, Schmidt-Erfurth U. Machine Learning of the Progression of Intermediate Age-Related Macular Degeneration Based on OCT Imaging. Invest Ophthalmol Vis Sci. 2017 May 1;58(6):BIO141-BIO150. doi: 10.1167/iovs.17-21789. PubMed 28658477 ↗
  • Schmidt-Erfurth U, Waldstein SM, Klimscha S, Sadeghipour A, Hu X, Gerendas BS, Osborne A, Bogunovic H. Prediction of Individual Disease Conversion in Early AMD Using Artificial Intelligence. Invest Ophthalmol Vis Sci. 2018 Jul 2;59(8):3199-3208. doi: 10.1167/iovs.18-24106. PubMed 29971444 ↗
  • Kozina, E. V., S. N. Sakhnov, V. V. Myasnikova, E. V. Bykova, and L. E. Aksenova. 2021. 'Modern Trends in Diagnostics and Prediction of Results of Anti-Vascular Endothelial Growth Factor Therapy of Pigment Epithelial Detachment in Neovascular Agerelated Macular Degeneration Using Deep Machine Learning Method (Literature Review)'. Acta Biomedica Scientifica 6 (6-1): 190-203. https://doi.org/10.29413/ABS.2021-6.6-1.22.
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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Apr 13, 2023, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT05208931
Lead sponsor
The S.N. Fyodorov Eye Microsurgery State Institution
Responsible party
Viktoria Myasnikova (Deputy Director for Research, The S.N. Fyodorov Eye Microsurgery State Institution) — Principal investigator
First posted
Jan 26, 2022
Start date
Nov 1, 2021
Primary completion
Sep 1, 2022
Completion
Sep 1, 2022
Last update
Apr 13, 2023

Study contacts

Viktoria Myasnikova, D.Med.Sc.
study director · Deputy Director for Research

Oversight

Data monitoring committee
Yes
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Apr 2023. You cannot join it, but the record below documents what was studied.

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