Deep Learning to Predict Geographic Atrophy Area and Growth Rate from Multimodal Imaging.

Journal: Ophthalmology. Retina
Published Date:

Abstract

OBJECTIVE: To develop deep learning models for annualized geographic atrophy (GA) growth rate prediction using fundus autofluorescence (FAF) images and spectral-domain OCT volumes from baseline visits, which can be used for prognostic covariate adjustment to increase power of clinical trials.

Authors

  • Neha Anegondi
    Clinical Imaging Group, Genentech, Inc., South San Francisco, California; Roche Ophthalmology Personalized Healthcare, Genentech, Inc., South San Francisco, California.
  • Simon S Gao
    gRED Computational Science, Genentech, Inc., South San Francisco, California.
  • Verena Steffen
    gRED Computational Science, Genentech, Inc., South San Francisco, California.
  • Richard F Spaide
    Vitreous Retina Macula Consultants of New York, New York, New York; and.
  • SriniVas R Sadda
    Doheny Image Analysis Laboratory, Doheny Eye Institute, Los Angeles, CA, USA.
  • Frank G Holz
    Department of Ophthalmology, University of Bonn, Bonn, Germany.
  • Christina Rabe
    Roche Ophthalmology Personalized Healthcare, Genentech, Inc., South San Francisco, California; Biostatistics, Genentech, Inc., South San Francisco, California.
  • Lee Honigberg
    Roche Ophthalmology Personalized Healthcare, Genentech, Inc., South San Francisco, California; Biomarker Development, Genentech, Inc., South San Francisco, California.
  • Elizabeth M Newton
    Genentech, Inc., South San Francisco, California.
  • Julia Cluceru
    Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA.
  • Michael G Kawczynski
    From the Department of Radiology and Biomedical Imaging (Y.D., J.H.S., H.T., R.H., N.W.J., T.P.C., M.S.A., C.M.A., S.C.B., R.R.F., S.Y.H., Y.S., R.A.H., M.H.P., B.L.F.) and Institute for Computational Health Sciences (J.H.S., M.G.K., H.T., D.L., K.A.Z., D.H.), University of California, San Francisco, 550 Parnassus Ave, San Francisco, CA 94143; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, Calif (Y.D.); and Department of Radiology, University of California, Davis, Sacramento, Calif (L.N.).
  • Thomas Bengtsson
    Genentech, Inc., South San Francisco, CA, USA.
  • Daniela Ferrara
    Genentech, Inc., South San Francisco, California.
  • Qi Yang
    Department of Radiology, The First Hospital of Jilin University, No.1, Xinmin Street, Changchun 130021, China (Y.W., M.L., Z.M., J.W., K.H., Q.Y., L.Z., L.M., H.Z.).