Structural and functional assessment of macula to diagnose glaucoma.

PurposeTo compare the diagnostic abilities of structural (ganglion cell-inner plexiform layer (GCIPL) thickness measured using spectral domain optical coherence tomography (SDOCT)) and functional (visual sensitivities measured using standard automated perimetry (SAP) and microperimetry (MP)) assessments of macula in glaucoma.MethodsIn a prospective study, 46 control eyes (28 subjects) and 61 glaucoma eyes (46 patients) underwent visual sensitivity estimation at macula (central 10°) by SAP and MP, and GCIPL thickness measurement at macula by SDOCT. Glaucoma was diagnosed by experts based on the optic disc and retinal nerve fiber layer changes. Area under the receiver-operating characteristic (AUC) curves and sensitivities at 95% specificity were used to assess the diagnostic ability of visual sensitivity and GCIPL measurements at various macular sectors.ResultsAUCs of GCIPL parameters ranged between 0.58 and 0.79. AUCs of SAP and MP sensitivities ranged between 0.59 and 0.71, and 0.59 and 0.72, respectively. There were no statistically significant differences between the AUCs of corresponding sector measurements (P>0.10 for all comparisons). Sensitivities at 95% specificities ranged from 31-59% for GCIPL parameters, 16-34% for SAP, and 8-38% for MP parameters. Sensitivities were significantly better with GCIPL compared with SAP and MP parameters in diagnosing glaucoma. Inferotemporal, inferior, and superotemporal sector measurements of GCIPL and visual sensitivity showed the best abilities to diagnose glaucoma.ConclusionsComparing the diagnostic abilities of structural and functional tests at macula in glaucoma, GCIPL thickness measurements with SDOCT performed better than the visual sensitivity measurements by SAP and MP.

Retinal nerve fiber layer evaluation of spectral domain optical coherence tomograph and scanning laser polarimeter to diagnose glaucoma.

PURPOSE: To compare the abilities of retinal nerve fiber layer (RNFL) parameters of spectral domain optical coherence tomograph (SDOCT) and scanning laser polarimeter (GDx enhanced corneal compensation; ECC) in detecting glaucoma. METHODS: In a cross-sectional study, 215 eyes of 165 subjects (106 eyes of 79 glaucoma patients and 109 eyes of 86 controls) referred by general ophthalmologists for glaucoma evaluation underwent RNFL imaging with SDOCT and GDx ECC. Ability of RNFL parameters of SDOCT to discriminate glaucoma eyes from control eyes was compared with that of GDx ECC using area under operating characteristic curves (AUCs), sensitivities at fixed specificities, and likelihood ratios (LRs). RESULTS: AUC of the average RNFL thickness of SDOCT to differentiate glaucoma from control eyes (0.868) was comparable (P=0.32) to that of GDx ECC (0.855). Sensitivity at 95% specificity was 63.2% for average RNFL thickness of SDOCT and 48.1% for the average RNFL measurement of GDx ECC. LRs of outside normal limits category of SDOCT parameters ranged between 5.6 and 7.7 while the same of GDx ECC parameters ranged between 3.1 and 3.7. LRs of within normal limits category of SDOCT parameters ranged between 0.18 and 0.24 while the same of GDx ECC parameters ranged between 0.20 and 0.32. CONCLUSION: Though AUCs and sensitivities at fixed specificities were comparable between the RNFL parameters of SDOCT and GDx ECC in diagnosing glaucoma, LRs indicated that the RNFL parameters of SDOCT were better in 'ruling in' glaucoma.

Agreement between event-based and trend-based glaucoma progression analyses.

PURPOSE: To evaluate the agreement between event- and trend-based analyses to determine visual field (VF) progression in glaucoma. METHODS: VFs of 175 glaucoma eyes with ≥5 VFs were analyzed by proprietary software of VF analyzer to determine progression. Agreement (κ) between trend-based analysis of VF index (VFI) and event-based analysis (glaucoma progression analysis, GPA) was evaluated. For eyes progressing by event- and trend-based methods, time to progression by two methods was calculated. RESULTS: Median number of VFs per eye was 7 and follow-up 7.5 years. GPA classified 101 eyes (57.7%) as stable, 30 eyes (17.1%) as possible and 44 eyes (25.2%) as likely progression. Trend-based analysis classified 122 eyes (69.7%) as stable (slope >-1% per year or any slope magnitude with P>0.05), 53 eyes (30.3%) as progressing with slope <-1% per year, P≤0.05 (sensitive criteria), and 37 eyes (21.1%) as progressing with slope <-1% per year, P≤0.01 (specific criteria). κ between sensitive criteria of GPA (possible combined with likely progression) and trend-based analysis was 0.48, and between specific criteria of GPA (possible clubbed with no progression) and trend-based analysis was 0.50. In eyes progressing by sensitive criteria of both methods (42 eyes), median time to progression by GPA (4.9 years) was similar (P=0.30) to trend-based method (5.0 years). This was also similar in eyes progressing by specific criteria of both methods (25 eyes; 5.6 years versus 5.9 years, P=0.23). CONCLUSION: Agreement between event- and trend-based progression analysis was moderate. GPA seemed to detect progression earlier than trend-based analysis, but this wasn't statistically significant.

Retinal nerve fiber layer and macular inner retina measurements by spectral domain optical coherence tomograph in Indian eyes with early glaucoma.

PURPOSE: To compare the diagnostic abilities of peripapillary retinal nerve fiber layer (RNFL) and macular inner retina (MIR) measurements by spectral domain optical coherence tomography (SD-OCT) in Indian eyes early glaucoma. METHODS: In an observational, cross-sectional study, 125 eyes of 64 normal subjects and 91 eyes of 59 early glaucoma patients underwent RNFL and MIR imaging with SD-OCT. Glaucomatous eyes had characteristic optic nerve and RNFL abnormalities and correlating visual field defects and a mean deviation of better than or equal to -6 dB on standard automated perimetry. Areas under the receiver operating characteristic curves (AUC), sensitivities at a fixed specificity and likelihood ratios (LRs) were estimated for all RNFL and MIR parameters. RESULTS: The AUCs for the RNFL parameters ranged from 0.537 for the temporal quadrant thickness to 0.821 for the inferior quadrant RNFL thickness. AUCs for the MIR parameters ranged from 0.603 for the superior minus inferior MIR thickness average to 0.908 for ganglion cell complex focal loss volume (GCC-FLV). AUC for the best MIR parameter (GCC-FLV) was significantly better (P<0.001) than that of the best RNFL parameter (inferior quadrant thickness). The sensitivities of these parameters at high specificity of 95%, however, were comparable (52.7% vs58.2%). Evaluation of the LRs showed that outside normal limits results of most of the RNFL and MIR parameters were associated with large effects on the post-test probability of disease. CONCLUSION: MIR parameters with RTVue SD-OCT were as good as the RNFL parameters to detect early glaucoma.