Role of imaging in glaucoma diagnosis and follow-up

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Abstract

The purpose of the review is to provide an update on the role of imaging devices in the diagnosis and follow-up of glaucoma with an emphasis on techniques for detecting glaucomatous progression and the newer spectral domain optical coherence tomography instruments. Imaging instruments provide objective quantitative measures of the optic disc and the retinal nerve fiber layer and are increasingly utilized in clinical practice. This review will summarize the recent enhancements in confocal scanning laser ophthalmoscopy, scanning laser polarimetry, and optical coherence tomography with an emphasis on how to utilize these techniques to manage glaucoma patients and highlight the strengths and limitations of each technology. In addition, this review will briefly describe the sophisticated data analysis strategies that are now available to detect glaucomatous change overtime.

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Ultrahigh-resolution, high-speed, Fourier domain optical coherence tomography and methods for dispersion compensation.

Maciej Wojtkowski, Vivek Srinivasan, Tony Ko … (2004)

Ultrahigh-resolution optical coherence tomography uses broadband light sources to achieve axial image resolutions on the few micron scale. Fourier domain detection methods enable more than an order of magnitude increase in imaging speed and sensitivity, thus overcoming the sensitivity limitations inherent in ultrahigh-resolution OCT using standard time domain detection. Fourier domain methods also provide direct access to the spectrum of the optical signal. This enables automatic numerical dispersion compensation, a key factor in achieving ultrahigh image resolutions. We present ultrahigh-resolution, high-speed Fourier domain OCT imaging with an axial resolution of 2.1 ìm in tissue and 16,000 axial scans per second at 1024 pixels per axial scan. Ultrahigh-resolution spectral domain OCT is shown to provide a ~100x increase in imaging speed when compared to ultrahigh-resolution time domain OCT. In vivo imaging of the human retina is demonstrated. We also present a general technique for automatic numerical dispersion compensation, which is applicable to spectral domain as well as swept source embodiments of Fourier domain OCT.

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Sparse Bayesian Learning and the Relevance Vector Machine

M. Tipping, E. Tipping M., M. L. Tipping … (2001)

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

Remo Susanna-Jr, Robert N. Weinreb, Christopher Bowd … (2004)

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.

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Author and article information

Journal

Journal ID (nlm-ta): Indian J Ophthalmol

Journal ID (publisher-id): IJO

Title: Indian Journal of Ophthalmology

Publisher: Medknow Publications (India )

ISSN (Print): 0301-4738

ISSN (Electronic): 1998-3689

Publication date (Print): January 2011

Volume: 59

Issue: Suppl1

Pages: S59-S68

Affiliations

[1 ]Department of Ophthalmology, Hamilton Glaucoma Center, University of California, San Diego, La Jolla, CA, USA

[2 ]L V Prasad Eye Institute, Banjara Hills, Hyderabad, India

Author notes

Correspondence to: Dr. Linda Zangwill, Department of Ophthalmology, Hamilton Glaucoma Center, University of California, San Diego, La Jolla, CA 9500, USA. E-mail: zangwill@ 123456glaucoma.ucsd.edu

Article

Publisher ID: IJO-59-59

DOI: 10.4103/0301-4738.73696

PMC ID: 3038504

PubMed ID: 21150036

SO-VID: 0d585b50-1b27-4300-ba04-d31c5ac764b1

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Role of imaging in glaucoma diagnosis and follow-up

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Abstract

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Karger: Ophthalmology

Most cited references 74

Ultrahigh-resolution, high-speed, Fourier domain optical coherence tomography and methods for dispersion compensation.

Sparse Bayesian Learning and the Relevance Vector Machine

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

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