Prevalence of glaucomatous-appearing discs in patients undergoing artificial intelligence screening for diabetic retinopathy
Year: 2023
Type: article
Study design: Observational Study
Abstract: To determine the prevalence of optic disc changes suspicious for glaucoma (OCSG) which may be overlooked by artificial intelligence-based diabetic retinopathy (DR) screening systems in place of in-person dilated screening exams. This was a retrospective cross-sectional study. High-resolution images were retrieved for 677 consecutive automated DR screening exams performed in adult patients. These were reviewed by two blinded readers for evidence of OCSG, which included increased vertical cup-to-disc ratio (VCDR), beta-zone peripapillary atrophy, optic disc hemorrhage, vessel bayoneting, rim thinning, and/or central vessel nasalization. The prevalence of OCSG was reported and compared between subjects designated as referable versus non-referable for DR. In total, 823 eyes of 413 subjects were included. The total OCSG prevalence was 4.8% to 20.6%, with no statistically significant difference between patients designated referable versus non-referable on artificial intelligence-based DR screening. The combined classification reliability of the image readers was moderate to substantial compared to a glaucoma specialist. OCSG were detected in 4.8% to 20.6% of adult diabetic patients who underwent AI-based DR screening in our cohort. This represents a significant prevalence of optic disc findings which, if detected on manual screening, would have prompted referral for a glaucoma workup. Such findings illustrate the need for artificial intelligence-based screening platforms which cover multiple high-prevalence ophthalmic conditions. Replacing manual dilated screening exams with systems optimized for a single disease may increase the risk of missing comorbid ocular disease.
Source: JFO Open Ophthalmology
Authors: Harshvardhan Chawla, Camille P. Hicks, Lama Assi, Joel P. Epling, Lena J. Al-Dujaili, Jayne S. Weiss
Institution: Louisiana State University
Language: English
Topic: Retinal Imaging and Analysis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,640
OpenAlex ID: W4380986757