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PURPOSE: To evaluate the performance of retinal nerve fiber layer (RNFL) thickness and optic nerve head (ONH) parameters analyzed with different offsets of reference plane in detecting early glaucomatous changes and in correlation with visual function using optical coherence tomography (OCT). METHODS: This was a cross-sectional study consisting of 41 normal subjects and 30 with early and 40 with advanced glaucoma. RNFL thickness and ONH parameters were measured with reference planes positioned at 95, 150, and 205 microm above the level of retinal pigment epithelium (RPE). Discriminating power for early glaucoma detection and correlation with visual field MD for each parameter at different levels of reference plane were compared by using the analyses of area under the receiver operating characteristic curves (AUCs) and linear regression, respectively. RESULTS: All ONH measurements were significantly different between normal and glaucoma groups, irrespective of the level of reference plane. In normal eyes, changing the reference plane position resulted in significant differences in ONH measurements. Among all the parameters examined, integrated rim volume and RNFL thickness measured at 150 microm above the RPE showed the largest AUC (0.966) for early glaucoma detection, and the strongest correlation with visual function (r = 0.793), respectively. CONCLUSIONS: OCT analysis of the ONH and RNFL is useful for early glaucoma detection. Among the three reference planes examined in this study, measurements analyzed at 150 microm above the RPE demonstrated the best performance for glaucoma detection and correlation with visual function. Compared with ONH measurements, RNFL thickness may be a better indicator, reflecting retinal ganglion cell function and monitoring disease progression.
Dr. C.K. Leung, Department of Ophthalmology, Caritas Medical Centre, 111 Wing Hong Street, Sham Shui Po, Hong Kong, People's Republic of China. tlims00@hotmail.com
6.9.2 Optical coherence tomography (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)