Performance of Optic Disc Optical Coherence Tomography Normative Database in a Large, Diverse, Real-World Cohort.
Rithambara Ramachandran, Ming-Chen Lu, Leslie M Niziol, Maria A Woodward, Angela R Elam, Leroy Johnson, Martha Kershaw, David C Musch, Amanda Bicket, Denise John, Wood Sarah Dougherty, Amy Zhang, Jason Zhang, Joan O'Brien, Paula Anne Newman-Casey
Summary
OCT normative databases should accurately reflect diverse populations to avoid misclassification by RNFL thickness color codes. Larger data sets should be leveraged to encompass the full spectrum of healthy optic nerve anatomy.
Abstract
PRCIS
Current optical coherence tomography normative sample data may not represent the diversity of human optic nerve anatomy needed to accurately classify all individuals with true glaucomatous optic neuropathy.
PURPOSE
To compare optic nerve head (ONH) measurements between published values from an optical coherence tomography (OCT) normative database and a larger, more diverse cohort of healthy individuals.
PATIENTS AND METHODS
ONH parameters from healthy participants of the Michigan Screening and Intervention for Glaucoma and Eye Health through Telemedicine (MI-SIGHT) program and the Topcon Maestro-1 normative cohort were compared. χ 2 tests compared MI-SIGHT retinal nerve fiber layer (RNFL) quadrant color-code labels with the expected distribution and multinomial logistic regression identified factors associated with label classifications.
RESULTS
In all, 1084 MI-SIGHT and 399 Topcon eyes were evaluated. The MI-SIGHT cohort was older (54 vs. 46 y), with more individuals identifying as black (61% vs. 20%), fewer as Hispanic (4% vs. 18%), and spherical equivalents closer to plano (-0.6 vs. -1.2 diopters) compared to the Topcon cohort (all P <0.001). Black/African American MI-SIGHT participants had larger cup-to-disc ratios and cup volumes, while white MI-SIGHT participants had smaller ONH values, except for rim area and rim volume, compared to Topcon participants (all P <0.001). The MI-SIGHT cohort's RNFL color codes did not follow the expected distribution ( P <0.05); more MI-SIGHT RNFL quadrant measurements were assigned as white (10.6% and 6.3% MI-SIGHT vs. 5% Topcon) and red codes (2.2% and 1.8% MI-SIGHT vs. <1% Topcon) than expected in the superior and inferior quadrants, respectively.
CONCLUSIONS
OCT normative databases should accurately reflect diverse populations to avoid misclassification by RNFL thickness color codes. Larger data sets should be leveraged to encompass the full spectrum of healthy optic nerve anatomy.
Keywords
More by Rithambara Ramachandran
View full profile →Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression.
Comparison between the Recommendations of Glaucoma Specialists and OCT Report Specialists for Further Ophthalmic Evaluation in a Community-Based Screening Study.
The Association of Social Determinants of Health on Monitoring for Disease Progression Among Patients With Primary Open-Angle Glaucoma.
Top Research in Optic Nerve & Disc
Browse all →Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.
Relationship between Optical Coherence Tomography Angiography Vessel Density and Severity of Visual Field Loss in Glaucoma.
Inflammation in Glaucoma: From the back to the front of the eye, and beyond.
In the Knowledge Library
Discussion
Comments and discussion will appear here in a future update.