Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography

• Published in: American journal of ophthalmology 2005, Vol.139 (1), p.44-55
• Main Authors: Medeiros, Felipe A., Zangwill, Linda M., Bowd, Christopher, Vessani, Roberto M., Susanna, Remo, Weinreb, Robert N.
• Format: Article
• Language: English
• Subjects: Aged; Area Under Curve; Biological and medical sciences; Body Weights and Measures; Colleges & universities; Cross-Sectional Studies; Defects; Diagnostic Techniques, Ophthalmological; Discriminant Analysis; Glaucoma; Glaucoma - diagnosis; Glaucoma and intraocular pressure; Humans; Intraocular Pressure; Macula Lutea - pathology; Medical sciences; Nerve Fibers - pathology; Ophthalmology; Optic Disk - pathology; Optic nerve; Optics; Reproducibility of Results; Retinal Ganglion Cells - pathology; ROC Curve; Sensitivity and Specificity; Tomography, Optical Coherence - methods
• ISSN: 0002-9394; 1879-1891
• DOI: 10.1016/j.ajo.2004.08.069

To compare the ability of optical coherence tomography retinal nerve fiber layer (RNFL), optic nerve head, and macular thickness parameters to differentiate between healthy eyes and eyes with glaucomatous visual field loss. Observational case-control study. Eighty-eight patients with glaucoma and 78 healthy subjects were included. All patients underwent ONH, RNFL thickness, and macular thickness scans with Stratus OCT during the same visit. ROC curves and sensitivities at fixed specificities were calculated for each parameter. A discriminant analysis was performed to develop a linear discriminant function designed to identify and combine the best parameters. This LDF was subsequently tested on an independent sample consisting of 63 eyes of 63 subjects (27 glaucomatous and 36 healthy individuals) from a different geographic area. No statistically significant difference was found between the areas under the ROC curves (AUC) for the RNFL thickness parameter with the largest AUC (inferior thickness, AUC = 0.91) and the ONH parameter with largest AUC (cup/disk area ratio, AUC = 0.88) ( P = .28). The RNFL parameter inferior thickness had a significantly larger AUC than the macular thickness parameter with largest AUC (inferior outer macular thickness, AUC = 0.81) ( P = .004). A combination of selected RNFL and ONH parameters resulted in the best classification function for glaucoma detection with an AUC of 0.97 when applied to the independent sample. RNFL and ONH measurements had the best discriminating performance among the several Stratus OCT parameters. A combination of ONH and RNFL parameters improved the diagnostic accuracy for glaucoma detection using this instrument.