{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T21:20:52Z","timestamp":1790716852276,"version":"4.1.0"},"reference-count":45,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,7]],"date-time":"2023-01-07T00:00:00Z","timestamp":1673049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Introduction. Glaucoma and non-arteritic anterior ischemic optic neuropathy (NAION) are optic neuropathies that can both lead to irreversible blindness. Several studies have compared optical coherence tomography angiography (OCTA) findings in glaucoma and NAION in the presence of similar functional and structural damages with contradictory results. The goal of this study was to use a deep learning system to differentiate OCTA in glaucoma and NAION. Material and methods. Sixty eyes with glaucoma (including primary open angle glaucoma, angle-closure glaucoma, normal tension glaucoma, pigmentary glaucoma, pseudoexfoliative glaucoma and juvenile glaucoma), thirty eyes with atrophic NAION and forty control eyes (NC) were included. All patients underwent OCTA imaging and automatic segmentation was used to analyze the macular superficial capillary plexus (SCP) and the radial peripapillary capillary (RPC) plexus. We used the classic convolutional neural network (CNN) architecture of ResNet50. Attribution maps were obtained using the \u201cIntegrated Gradients\u201d method. Results. The best performances were obtained with the SCP + RPC model achieving a mean area under the receiver operating characteristics curve (ROC AUC) of 0.94 (95% CI 0.92\u20130.96) for glaucoma, 0.90 (95% CI 0.86\u20130.94) for NAION and 0.96 (95% CI 0.96\u20130.97) for NC. Conclusion. This study shows that deep learning architecture can classify NAION, glaucoma and normal OCTA images with a good diagnostic performance and may outperform the specialist assessment.<\/jats:p>","DOI":"10.3390\/jcm12020507","type":"journal-article","created":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T05:57:14Z","timestamp":1673243834000},"page":"507","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A Deep Learning System Using Optical Coherence Tomography Angiography to Detect Glaucoma and Anterior Ischemic Optic Neuropathy"],"prefix":"10.3390","volume":"12","author":[{"given":"Roxane","family":"Bunod","sequence":"first","affiliation":[{"name":"Department of Ophthalmology 3, Quinze-Vingts National Ophthalmology Hospital, 28 Rue de Charenton, 75012 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M\u00e9lanie","family":"Lubrano","sequence":"additional","affiliation":[{"name":"Keen Eye Technologies SAS, 74 Rue du Faubourg Saint-Antoine, 75012 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antoine","family":"Pirovano","sequence":"additional","affiliation":[{"name":"Keen Eye Technologies SAS, 74 Rue du Faubourg Saint-Antoine, 75012 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00e9raldine","family":"Chotard","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology 4, Quinze-Vingts National Ophthalmology Hospital, 28 Rue de Charenton, 75012 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emmanuelle","family":"Brasnu","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology 3, Quinze-Vingts National Ophthalmology Hospital, 28 Rue de Charenton, 75012 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sylvain","family":"Berlemont","sequence":"additional","affiliation":[{"name":"Keen Eye Technologies SAS, 74 Rue du Faubourg Saint-Antoine, 75012 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antoine","family":"Labb\u00e9","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology 3, Quinze-Vingts National Ophthalmology Hospital, 28 Rue de Charenton, 75012 Paris, France"},{"name":"IHU FOReSIGHT, INSERM-DGOS CIC 1423, 17 Rue Moreau, 75012 Paris, France"},{"name":"INSERM, CNRS, Institut de la Vision, Sorbonne Universit\u00e9s, 7 Rue Moreau, 75012 Paris, France"},{"name":"Department of Ophthalmology, Ambroise Par\u00e9 Hospital, IHU FOReSIGHT, AP-HP, University of Paris Saclay, 9 Avenue Charles de Gaulle, 92100 Boulogne-Billancourt, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edouard","family":"Augstburger","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology 3, Quinze-Vingts National Ophthalmology Hospital, 28 Rue de Charenton, 75012 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christophe","family":"Baudouin","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology 3, Quinze-Vingts National Ophthalmology Hospital, 28 Rue de Charenton, 75012 Paris, France"},{"name":"IHU FOReSIGHT, INSERM-DGOS CIC 1423, 17 Rue Moreau, 75012 Paris, France"},{"name":"INSERM, CNRS, Institut de la Vision, Sorbonne Universit\u00e9s, 7 Rue Moreau, 75012 Paris, France"},{"name":"Department of Ophthalmology, Ambroise Par\u00e9 Hospital, IHU FOReSIGHT, AP-HP, University of Paris Saclay, 9 Avenue Charles de Gaulle, 92100 Boulogne-Billancourt, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e144","DOI":"10.1016\/S2214-109X(20)30489-7","article-title":"Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: The Right to Sight: An analysis for the Global Burden of Disease Study","volume":"9","author":"Steinmetz","year":"2021","journal-title":"Lancet Glob. 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