PURPOSE: To determine whether the thicknesses of the different parameters of the ganglion cell complex (GCC) and peripapillary retinal nerve fiber layer can be used to differentiate eyes with glaucoma from normal eyes. METHODS: Two hundred sixty-one eyes, including 68 normal eyes and 32 preperimetric glaucoma, 81 early glaucoma, and 80 advanced glaucoma were analyzed in the present study. The thicknesses of the GCC and retinal nerve fiber layer were measured using RTVue spectral-domain optical coherence tomographic (SD-OCT) images. The area under the receiver operating characteristic (AUROC) curve and sensitivities at fixed specificities were calculated for each parameter. A logistic regression analysis was used to determine the risk factors for glaucoma. RESULTS: The 2 largest AUROC curves for all glaucoma stages were those for the GCC parameters. The global loss volume (GLV) was always one of the 2 highest values of the AUROC curve. The GLV also had the highest sensitivity at a fixed specificity to identify glaucoma at early and advanced stage. The focal loss volume (FLV) had the largest AUROC curve value and the highest sensitivity at a fixed specificity for advanced glaucoma. The logistic regression analysis showed that the GLV was one of the factors that predicted preperimetric glaucoma [odds ratio (OR)=1.74] and early glaucoma (OR=1.22), whereas the FLV was useful for detecting advanced glaucoma (OR=2.32). CONCLUSIONS: The SD-OCT-derived macular GCC parameters can be used to detect preperimetric and perimetric glaucoma. The new GCC parameters, GLV and FLV, performed well in discriminating glaucomatous eyes from normal eyes.
PURPOSE: To determine whether the thicknesses of the different parameters of the ganglion cell complex (GCC) and peripapillary retinal nerve fiber layer can be used to differentiate eyes with glaucoma from normal eyes. METHODS: Two hundred sixty-one eyes, including 68 normal eyes and 32 preperimetric glaucoma, 81 early glaucoma, and 80 advanced glaucoma were analyzed in the present study. The thicknesses of the GCC and retinal nerve fiber layer were measured using RTVue spectral-domain optical coherence tomographic (SD-OCT) images. The area under the receiver operating characteristic (AUROC) curve and sensitivities at fixed specificities were calculated for each parameter. A logistic regression analysis was used to determine the risk factors for glaucoma. RESULTS: The 2 largest AUROC curves for all glaucoma stages were those for the GCC parameters. The global loss volume (GLV) was always one of the 2 highest values of the AUROC curve. The GLV also had the highest sensitivity at a fixed specificity to identify glaucoma at early and advanced stage. The focal loss volume (FLV) had the largest AUROC curve value and the highest sensitivity at a fixed specificity for advanced glaucoma. The logistic regression analysis showed that the GLV was one of the factors that predicted preperimetric glaucoma [odds ratio (OR)=1.74] and early glaucoma (OR=1.22), whereas the FLV was useful for detecting advanced glaucoma (OR=2.32). CONCLUSIONS: The SD-OCT-derived macular GCC parameters can be used to detect preperimetric and perimetric glaucoma. The new GCC parameters, GLV and FLV, performed well in discriminating glaucomatous eyes from normal eyes.
Authors: Xunda Luo; Nimesh B Patel; Lakshmi P Rajagopalan; Ronald S Harwerth; Laura J Frishman Journal: Invest Ophthalmol Vis Sci Date: 2014-06-26 Impact factor: 4.799
Authors: Erica Bresciani-Battilana; Ivan C Teixeira; Diego T Q Barbosa; Cristiano Caixeta-Umbelino; Maurício D Paolera; Niro Kasahara Journal: Int Ophthalmol Date: 2014-09-03 Impact factor: 2.031
Authors: Ivan C Teixeira; Erica Bresciani-Battilana; Diego T Q Barbosa; Cristiano Caixeta-Umbelino; Maurício D Paolera; Niro Kasahara Journal: Int Ophthalmol Date: 2014-11-26 Impact factor: 2.031