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

Medeiros, Felipe A.; Zangwill, Linda M.; Bowd, Christopher; Vessani, Roberto M.; Susanna, Remo; Weinreb, Robert N.

doi:10.1016/j.ajo.2004.08.069

« Previous Next »American Journal of Ophthalmology
Volume 139, Issue 1 , Pages 44-55, January 2005

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

Felipe A. Medeiros, MD
- Hamilton Glaucoma Center and Department of Ophthalmology, University of California, San Diego, California
- Department of Ophthalmology, University of São Paulo, São Paulo, Brazil.
Linda M. Zangwill, PhD
- Hamilton Glaucoma Center and Department of Ophthalmology, University of California, San Diego, California
Christopher Bowd, PhD
- Hamilton Glaucoma Center and Department of Ophthalmology, University of California, San Diego, California
Roberto M. Vessani, MD
- Department of Ophthalmology, University of São Paulo, São Paulo, Brazil.
Remo Susanna Jr, MD
- Department of Ophthalmology, University of São Paulo, São Paulo, Brazil.
Robert N. Weinreb, MD
- Hamilton Glaucoma Center and Department of Ophthalmology, University of California, San Diego, California
- Inquiries to Felipe A. Medeiros, MD, Hamilton Glaucoma Center, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0946

Accepted 26 August 2004.

Purpose

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.

Design

Observational case-control study.

Methods

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.

Results

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.

Conclusions

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.