Clinically applicable deep learning-based decision aids for treatment of neovascular AMD.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Published Date:

Abstract

PURPOSE: Anti-vascular endothelial growth factor (Anti-VEGF) therapy is currently seen as the standard for treatment of neovascular AMD (nAMD). However, while treatments are highly effective, decisions for initial treatment and retreatment are often challenging for non-retina specialists. The purpose of this study is to develop convolutional neural networks (CNN) that can differentiate treatment indicated presentations of nAMD for referral to treatment centre based solely on SD-OCT. This provides the basis for developing an applicable medical decision support system subsequently.

Authors

  • Matthias Gutfleisch
    Department of Ophthalmology, St. Franziskus-Hospital, Hohenzollernring 74, 48145, Muenster, Germany. Matthias.Gutfleisch@augen-franziskus.de.
  • Oliver Ester
    Westphalia DataLab GmbH, Muenster, Germany.
  • Sökmen Aydin
    Westphalia DataLab GmbH, Muenster, Germany.
  • Martin Quassowski
    Westphalia DataLab GmbH, Muenster, Germany.
  • Georg Spital
    Department of Ophthalmology, St. Franziskus-Hospital, Hohenzollernring 74, 48145, Muenster, Germany.
  • Albrecht Lommatzsch
    Department of Ophthalmology, St. Franziskus-Hospital, Hohenzollernring 74, 48145, Muenster, Germany.
  • Kai Rothaus
    Department of Ophthalmology, St. Franziskus-Hospital, Hohenzollernring 74, 48145, Muenster, Germany.
  • Adam Michael Dubis
    NIHR Biomedical Resource Centre, UCL Institute of Ophthalmology and Moorfields Eye Hospital NHS Trust, London, United Kingdom.
  • Daniel Pauleikhoff
    Department of Ophthalmology, St. Franziskus-Hospital, Hohenzollernring 74, 48145, Muenster, Germany.