THE BELGIAN OPHTHALMIC ASSOCIATIONS
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This abstract is assigned to session AOB Free Papers 2
| Presentation type | Oral presentation |
| Title | Artificial Intelligence Glaucoma Screening: Real-World Implementation and Validation |
| Purpose | This study evaluates whether artificial intelligence (AI) - based screening can detect asymptomatic patients and reduce morbidity. |
| Methods | Participants aged between 55-65 years identified from primary care databases were randomly invited to undergo glaucoma screening. Glaucoma risk was determined from the fundus image using an AI algorithm (MONA G-Risk®). Subjects were referred for further glaucoma assessment according to the AI’s outcome or an IOP of ≥24mmHg. Validation of the screening protocol was performed by reviewing the entire fundus photos dataset by six paired glaucoma experts. Referred participants performed visual field test as well as a face-to-face assessment with ophthalmologist. |
| Results | Of 1,038 subjects invited, 65% (671) were screened. The AI algorithm referred 9.8% (66/671) of participants while human-expert fundus review referred 77 more (143/671 or 21.3%). After excluding 42 who missed VF testing, 629 participants remained for analysis. Glaucoma was found in 6.4% (40/629; 95% CI 5–9%) and IOP ≥24 mmHg in 3.2% (20/629; 95% CI 2–5%). The AI algorithm’s sensitivity and specificity for detecting glaucoma were 78% (95% CI 62–89%) and 95% (95% CI 93–97%). The incremental cost-effectiveness ratio was €1,743 for the AI screening program implementation versus standard care scenario over a ten year horizon. |
| Conclusion | Glaucoma screening with AI technology outperformed human detection. AI could boost screening efficiency and case detection, paving the basis for earlier treatment and avoidable blindness prevention. |
| Conflict of interest | No |
| Details of conflicting interests | None |
Authors 1
| Initials | A |
| Last name | Cabrita |
| Department | Santa Maria University Hospital, Lisbon |
| City | Lisbon |
Authors 2
| Initials | Z |
| Last name | Wehbi |
| Department | UZ Leuven, Belgium |
| City | Leuven |
Authors 3
| Initials | I |
| Last name | Stalmans |
| Department | UZ Leuven, Belgium |
| City | Leuven |
Authors 4
| Initials | L |
| Last name | Pinto |
| Department | Santa Maria University Hospital, Lisbon |
| City | Lisbon |