PURPOSE: To evaluate the performance of ganglion cell layer/inner plexiform layer (GCL/IPL) measurements with spectral-domain optical coherence tomography (Cirrus HD-OCT) for detection of early glaucoma and to compare results to retinal nerve fiber layer (RNFL) measurements. DESIGN: Cross-sectional prospective diagnostic study. METHODS: We enrolled 99 subjects, including 59 eyes with glaucoma (47 subjects) (mean deviation >-6.0 dB) and 91 normal eyes (52 subjects). Patients underwent biometry and peripapillary and macular OCT imaging. Performance of the GCL/IPL and RNFL algorithms was evaluated with area under receiver operating characteristic curves (AUC), likelihood ratios, and sensitivities/specificities adjusting for covariates. Combination of best parameters was explored. RESULTS: Average (SD) mean deviation in the glaucoma group was -2.5 (1.9) dB. On multivariate analyses, age (P < 0.001) and axial length (P = 0.03) predicted GC/IPL measurements in normal subjects. No significant correlation was found between average or regional GC/IPL thickness and respective outer retina (OR) thickness measurements (P > 0.05). Average RNFL thickness performed better than average GCL/IPL measurements for detection of glaucoma (AUC = 0.964 vs 0.937; P = 0.04). The best regional measures from each algorithm (inferior quadrant RNFL vs minimum GCL/IPL) had comparable performances (P = 0.78). Entering the GC/IPL to OR ratio into prediction models did not enhance the performance of the GCL/IPL measures. Combining the best parameters from each algorithm improved detection of glaucoma (P = 0.04). CONCLUSIONS: Regional GCL/IPL measures derived from Cirrus HD-OCT performed as well as regional RNFL outcomes for detection of early glaucoma. Using the GC/IPL to OR ratio did not enhance the performance of GCL/IPL parameters. Combining the best measures from the 2 algorithms improved detection of glaucoma.
PURPOSE: To evaluate the performance of ganglion cell layer/inner plexiform layer (GCL/IPL) measurements with spectral-domain optical coherence tomography (Cirrus HD-OCT) for detection of early glaucoma and to compare results to retinal nerve fiber layer (RNFL) measurements. DESIGN: Cross-sectional prospective diagnostic study. METHODS: We enrolled 99 subjects, including 59 eyes with glaucoma (47 subjects) (mean deviation >-6.0 dB) and 91 normal eyes (52 subjects). Patients underwent biometry and peripapillary and macular OCT imaging. Performance of the GCL/IPL and RNFL algorithms was evaluated with area under receiver operating characteristic curves (AUC), likelihood ratios, and sensitivities/specificities adjusting for covariates. Combination of best parameters was explored. RESULTS: Average (SD) mean deviation in the glaucoma group was -2.5 (1.9) dB. On multivariate analyses, age (P < 0.001) and axial length (P = 0.03) predicted GC/IPL measurements in normal subjects. No significant correlation was found between average or regional GC/IPL thickness and respective outer retina (OR) thickness measurements (P > 0.05). Average RNFL thickness performed better than average GCL/IPL measurements for detection of glaucoma (AUC = 0.964 vs 0.937; P = 0.04). The best regional measures from each algorithm (inferior quadrant RNFL vs minimum GCL/IPL) had comparable performances (P = 0.78). Entering the GC/IPL to OR ratio into prediction models did not enhance the performance of the GCL/IPL measures. Combining the best parameters from each algorithm improved detection of glaucoma (P = 0.04). CONCLUSIONS: Regional GCL/IPL measures derived from Cirrus HD-OCT performed as well as regional RNFL outcomes for detection of early glaucoma. Using the GC/IPL to OR ratio did not enhance the performance of GCL/IPL parameters. Combining the best measures from the 2 algorithms improved detection of glaucoma.
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