Application of a Deep Learning System to Detect Papilledema on Nonmydriatic Ocular Fundus Photographs in an Emergency Department
1
Issued Date
2024-05-01
Resource Type
ISSN
00029394
eISSN
18791891
Scopus ID
2-s2.0-85188184066
Pubmed ID
37926337
Journal Title
American Journal of Ophthalmology
Volume
261
Start Page
199
End Page
207
Rights Holder(s)
SCOPUS
Bibliographic Citation
American Journal of Ophthalmology Vol.261 (2024) , 199-207
Suggested Citation
Biousse V., Najjar R.P., Tang Z., Lin M.Y., Wright D.W., Keadey M.T., Wong T.Y., Bruce B.B., Milea D., Newman N.J., Fraser C.L., Micieli J.A., Costello F., Bénard-Séguin É., Yang H., Chan C.K.M., Cheung C.Y., Chan N.C., Hamann S., Gohier P., Vautier A., Rougier M.B., Chiquet C., Vignal-Clermont C., Hage R., Khanna R.K., Tran T.H.C., Lagrèze W.A., Jonas J.B., Ambika S., Fard M.A., La Morgia C., Carbonelli M., Barboni P., Carelli V., Romagnoli M., Amore G., Nakamura M., Fumio T., Petzold A., Wenniger lj M.d.B., Kho R., Fonseca P.L., Bikbov M.M., Najjar R.P., Ting D., Loo J.L., Tow S., Singhal S., Vasseneix C., Wong T.Y., Lamoureux E., Yu Chen C., Aung T., Schmetterer L., Sanda N., Thuman G., Hwang J.M., Vanikieti K., Suwan Y., Padungkiatsagul T., Yu-Wai-Man P., Jurkute N., Hong E.H., Biousse V., Peragallo J.H., Datillo M., Kedar S., Patil A., Aung A., Boyko M., Alsakran W.A., Zayani A., Bouthour W., Banc A., Mosley R., Labella F., Miller N.R., Chen J.J., Mejico L.J., Kilangalanga J.N. Application of a Deep Learning System to Detect Papilledema on Nonmydriatic Ocular Fundus Photographs in an Emergency Department. American Journal of Ophthalmology Vol.261 (2024) , 199-207. 207. doi:10.1016/j.ajo.2023.10.025 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/97755
Title
Application of a Deep Learning System to Detect Papilledema on Nonmydriatic Ocular Fundus Photographs in an Emergency Department
Author(s)
Biousse V.
Najjar R.P.
Tang Z.
Lin M.Y.
Wright D.W.
Keadey M.T.
Wong T.Y.
Bruce B.B.
Milea D.
Newman N.J.
Fraser C.L.
Micieli J.A.
Costello F.
Bénard-Séguin É.
Yang H.
Chan C.K.M.
Cheung C.Y.
Chan N.C.
Hamann S.
Gohier P.
Vautier A.
Rougier M.B.
Chiquet C.
Vignal-Clermont C.
Hage R.
Khanna R.K.
Tran T.H.C.
Lagrèze W.A.
Jonas J.B.
Ambika S.
Fard M.A.
La Morgia C.
Carbonelli M.
Barboni P.
Carelli V.
Romagnoli M.
Amore G.
Nakamura M.
Fumio T.
Petzold A.
Wenniger lj M.d.B.
Kho R.
Fonseca P.L.
Bikbov M.M.
Najjar R.P.
Ting D.
Loo J.L.
Tow S.
Singhal S.
Vasseneix C.
Wong T.Y.
Lamoureux E.
Yu Chen C.
Aung T.
Schmetterer L.
Sanda N.
Thuman G.
Hwang J.M.
Vanikieti K.
Suwan Y.
Padungkiatsagul T.
Yu-Wai-Man P.
Jurkute N.
Hong E.H.
Biousse V.
Peragallo J.H.
Datillo M.
Kedar S.
Patil A.
Aung A.
Boyko M.
Alsakran W.A.
Zayani A.
Bouthour W.
Banc A.
Mosley R.
Labella F.
Miller N.R.
Chen J.J.
Mejico L.J.
Kilangalanga J.N.
Najjar R.P.
Tang Z.
Lin M.Y.
Wright D.W.
Keadey M.T.
Wong T.Y.
Bruce B.B.
Milea D.
Newman N.J.
Fraser C.L.
Micieli J.A.
Costello F.
Bénard-Séguin É.
Yang H.
Chan C.K.M.
Cheung C.Y.
Chan N.C.
Hamann S.
Gohier P.
Vautier A.
Rougier M.B.
Chiquet C.
Vignal-Clermont C.
Hage R.
Khanna R.K.
Tran T.H.C.
Lagrèze W.A.
Jonas J.B.
Ambika S.
Fard M.A.
La Morgia C.
Carbonelli M.
Barboni P.
Carelli V.
Romagnoli M.
Amore G.
Nakamura M.
Fumio T.
Petzold A.
Wenniger lj M.d.B.
Kho R.
Fonseca P.L.
Bikbov M.M.
Najjar R.P.
Ting D.
Loo J.L.
Tow S.
Singhal S.
Vasseneix C.
Wong T.Y.
Lamoureux E.
Yu Chen C.
Aung T.
Schmetterer L.
Sanda N.
Thuman G.
Hwang J.M.
Vanikieti K.
Suwan Y.
Padungkiatsagul T.
Yu-Wai-Man P.
Jurkute N.
Hong E.H.
Biousse V.
Peragallo J.H.
Datillo M.
Kedar S.
Patil A.
Aung A.
Boyko M.
Alsakran W.A.
Zayani A.
Bouthour W.
Banc A.
Mosley R.
Labella F.
Miller N.R.
Chen J.J.
Mejico L.J.
Kilangalanga J.N.
Author's Affiliation
Ufa Eye Research Institute
Graduate School of Medicine
Farabi Eye Hospital
Istituto delle Scienze Neurologiche di Bologna
Université Grenoble Alpes
Seoul National University Bundang Hospital
Duke-NUS Medical School
Fondation Adolphe de Rothschild
Norton College of Medicine
NUS Yong Loo Lin School of Medicine
Medical Research Foundation, Chennai
Tsinghua University
Universitätsklinikum Freiburg
Singapore Eye Research Institute
Universite Catholique de Lille
Sun Yat-Sen University
Centro Hospitalar e Universitário de Coimbra
National University of Singapore
Universität Heidelberg
Moorfields Eye Hospital NHS Foundation Trust
Faculty of Medicine Ramathibodi Hospital, Mahidol University
Save Sight Institute
Hôpitaux Universitaires de Genève
CHU Angers
Singapore National Eye Centre
Rigshospitalet
Mayo Clinic
Groupe Hospitalier Pellegrin
Chinese University of Hong Kong
Toronto Western Hospital University of Toronto
Emory University School of Medicine
University of Calgary
Amsterdam UMC - University of Amsterdam
Johns Hopkins University School of Medicine
Saint Joseph Hospital
Democratic Republic of Congo
American Eye Center
Graduate School of Medicine
Farabi Eye Hospital
Istituto delle Scienze Neurologiche di Bologna
Université Grenoble Alpes
Seoul National University Bundang Hospital
Duke-NUS Medical School
Fondation Adolphe de Rothschild
Norton College of Medicine
NUS Yong Loo Lin School of Medicine
Medical Research Foundation, Chennai
Tsinghua University
Universitätsklinikum Freiburg
Singapore Eye Research Institute
Universite Catholique de Lille
Sun Yat-Sen University
Centro Hospitalar e Universitário de Coimbra
National University of Singapore
Universität Heidelberg
Moorfields Eye Hospital NHS Foundation Trust
Faculty of Medicine Ramathibodi Hospital, Mahidol University
Save Sight Institute
Hôpitaux Universitaires de Genève
CHU Angers
Singapore National Eye Centre
Rigshospitalet
Mayo Clinic
Groupe Hospitalier Pellegrin
Chinese University of Hong Kong
Toronto Western Hospital University of Toronto
Emory University School of Medicine
University of Calgary
Amsterdam UMC - University of Amsterdam
Johns Hopkins University School of Medicine
Saint Joseph Hospital
Democratic Republic of Congo
American Eye Center
Corresponding Author(s)
Other Contributor(s)
Abstract
Purpose: The Fundus photography vs Ophthalmoscopy Trial Outcomes in the Emergency Department (FOTO-ED) studies showed that ED providers poorly recognized funduscopic findings in patients in the ED. We tested a modified version of the Brain and Optic Nerve Study Artificial Intelligence (BONSAI) deep learning system on nonmydriatic fundus photographs from the FOTO-ED studies to determine if the deep learning system could have improved the detection of papilledema had it been available to ED providers as a real-time diagnostic aid. Design: Retrospective secondary analysis of a cohort of patients included in the FOTO-ED studies. Methods: The testing data set included 1608 photographs obtained from 828 patients in the FOTO-ED studies. Photographs were reclassified according to the optic disc classification system used by the deep learning system (“normal optic discs,” “papilledema,” and “other optic disc abnormalities”). The system's performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 1-vs-rest strategy, with reference to expert neuro-ophthalmologists. Results: The BONSAI deep learning system successfully distinguished normal from abnormal optic discs (AUC 0.92 [95% confidence interval {CI} 0.90-0.93]; sensitivity 75.6% [73.7%-77.5%] and specificity 89.6% [86.3%-92.8%]), and papilledema from normal and others (AUC 0.97 [0.95-0.99]; sensitivity 84.0% [75.0%-92.6%] and specificity 98.9% [98.5%-99.4%]). Six patients with missed papilledema in 1 eye were correctly identified by the deep learning system as having papilledema in the other eye. Conclusions: The BONSAI deep learning system was able to reliably identify papilledema and normal optic discs on nonmydriatic photographs obtained in the FOTO-ED studies. Our deep learning system has excellent potential as a diagnostic aid in EDs and non-ophthalmology clinics equipped with nonmydriatic fundus cameras.