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PURPOSE: To compare the ability of Cirrus retinal nerve fiber layer (RNFL) thickness and the Color Reflectivity Discretization Analysis (CORDA), a novel optical coherence tomography (OCT) analysis method, to differentiate between normal subjects, glaucoma suspects, and glaucoma patients. PATIENTS AND METHODS: Analysis of peripapillary OCT images using Cirrus SD-OCT (optic nerve head cube 200×200 protocol) and postacquisition CORDA analysis of peripapillary RNFL B-scan images was performed. In total, 291 eyes of 148 subjects (94 normal eyes, 100 primary open-angle glaucoma suspect eyes, and 97 eyes with primary open-angle glaucoma) were included. Area under the receiver operating characteristic curve was estimated for each region and method (Cirrus vs. CORDA) for differentiating eyes with glaucoma, and those that are glaucoma suspect, from normal eyes. RESULTS: CORDA HR1 parameter discriminated glaucoma patients from normal subjects more accurately than Cirrus RNFL thickness in nasal (P=0.003) and temporal (P=0.001) regions. HR1 showed greater area under the receiver operating characteristic curve than Cirrus RNFL thickness when discriminating glaucoma suspects from normal subjects in the superior (P=0.02), nasal (P=0.003), and temporal (P=0.001) regions. Both were similar for mean and the inferior regions. CONCLUSIONS: In this study, the novel CORDA HR1 differentiated between normal subjects and glaucoma suspects more accurately than Cirrus RNFL, and in temporal and nasal regions when discriminating between normal and glaucomatous eyes. CORDA analysis may improve the diagnostic accuracy of Cirrus OCT for glaucoma and glaucoma suspects.
*Northern Virginia Ophthalmology Associates, Falls Church, VA §Diopsys Inc., Pine Brook, NJ ‡Division of Biostatistics, Thomas Jefferson University †Wills Eye Hospital, Glaucoma Research Center, Philadelphia, PA.
Full article6.9.2.2 Posterior (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis > 6.9.2 Optical coherence tomography)
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)