An observational study in Optic Neuropathy, Optic Neuropathy, Ischemic and Optic Neuritis, sponsored by Fondation Ophtalmologique Adolphe de Rothschild. Completed at 1 site in France. Per ClinicalTrials.gov, last updated 2025-09-08.
Sponsored by Fondation Ophtalmologique Adolphe de Rothschild · Observational
The research team, recognized as a world leader in Artificial Intelligence for neuro-ophthalmology, has shown that it is possible to diagnose certain neuro-ophthalmologic or neurologic disorders from a single retinal fundus image (Milea et al, New England Journal of Medicine, 2020). However, clinical practice requires identifying a broader spectrum of diseases (inflammatory, ischemic, hereditary, neurodegenerative) within the same analysis.
The main objective is to develop, through a new algorithm capable of classifying multiple disorders from a smaller set of conventional retinal images.
This project meets a significant public health need: the global shortage of neuro-ophthalmologists. It aims to provide healthcare professionals with a rapid triage tool to detect serious and treatable conditions, enabling timely intervention.
The study will include patients with clearly defined neuro-ophthalmologic or neurologic conditions, confirmed diagnoses, and retinal imaging. Clinical, paraclinical, and imaging data collected during standard care will be used, with strict anonymization according to legal and institutional requirements.
Specific Objectives :
61 studies on the registry are indexed under Optic Nerve Diseases; 22 are open to participants now.
This study's enrollment of 693 is above the median of 56 across 21 observational studies indexed under Optic Nerve Diseases.
Browse Optic Nerve Diseases studies →Fondation Ophtalmologique Adolphe de Rothschild is the lead sponsor of 316 studies on the registry; 78 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Color fundus photographs taken within 30 days from the date of onset
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Deep learning algorithm applied on retrospectively collected color fundus photographs
Diagnostic performance of the Artificial Intelligence algorithm in detecting multiple neuro-ophthalmologic and neurologic conditions from retinal imaging.
Evaluation of the algorithm's sensitivity, specificity, and area under the receiver operating caracteristics curve for classifying multiple neuro-ophthalmologic and neurologic pathologies using retinal fundus photography and Optical Coherence Tomography images, compared with expert-established reference diagnoses.
Time frame: baseline
Plan to share: No
This study is completed, as verified in Sep 2025. You cannot join it, but the record below documents what was studied.
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