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Abstract #12029 Published in IGR 7-1
Comparison of three optical coherence tomography scanning areas for detection of glaucomatous damage
Wollstein G; Ishikawa H; Wang J; Beaton SA; Schuman JSAmerican Journal of Ophthalmology 2005; 139: 39-43
PURPOSE: Several cross-sectional studies have demonstrated the capability of optical coherence tomography (OCT) to detect glaucomatous changes. OCT enables posterior pole scanning of three regions: macula, peripapillary, and optic nerve head (ONH). This study compared the ability of each region to detect glaucomatous damage. DESIGN: Retrospective observational cross-sectional study. METHODS: The study included 37 normal (37 subjects) and 37 glaucomatous eyes (26 subjects) that had comprehensive ocular examination, reliable and reproducible Swedish interactive thresholding algorithm standard 24-2 perimetry, and Stratus OCT scanning of macula, peripapillary, and ONH regions on the same visit. Optical nerve head (ONH) appearance did not form part of the inclusion criteria. The main outcome measure, was area under receiver operating characteristic curves (AROCs) that was calculated for each scanning region for distinguishing between normal and glaucomatous eyes. RESULTS: The highest AROCs for distinguishing between groups were for ONH parameters (rim area = 0.97, horizontal integrated rim width = 0.96, vertical integrated rim area = 0.95) and peripapillary nerve fiber layer (NFL) thickness (0.94) followed by macular volume and thickness (both 0.80). A statistically significant difference existed in ONH and NFL AROCs when compared with macular AROCs (P ≥ .007, for both) CONCLUSIONS: OCT ONH and NFL parameters provided similar discrimination capabilities between healthy eyes and those of glaucoma patients and superior discrimination capabilities when compared with macular parameters.
Dr. G. Wollstein, UPMC Eye Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15213, USA
Classification:
6.9.2 Optical coherence tomography (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
