Diagnostic Abilities of Variable and Enhanced Corneal Compensation Algorithms of GDx in Different Severities of Glaucoma.

PURPOSE: To compare the abilities of retinal nerve fiber layer (RNFL) parameters of variable corneal compensation (VCC) and enhanced corneal compensation (ECC) algorithms of scanning laser polarimetry (GDx) in detecting various severities of glaucoma. METHODS: Two hundred and eighty-five eyes of 194 subjects from the Longitudinal Glaucoma Evaluation Study who underwent GDx VCC and ECC imaging were evaluated. Abilities of RNFL parameters of GDx VCC and ECC to diagnose glaucoma were compared using area under receiver operating characteristic curves (AUC), sensitivities at fixed specificities, and likelihood ratios. RESULTS: After excluding 5 eyes that failed to satisfy manufacturer-recommended quality parameters with ECC and 68 with VCC, 56 eyes of 41 normal subjects and 161 eyes of 121 glaucoma patients [36 eyes with preperimetric glaucoma, 52 eyes with early (MD>-6 dB), 34 with moderate (MD between -6 and -12 dB), and 39 with severe glaucoma (MD<-12 dB)] were included for the analysis. Inferior RNFL, average RNFL, and nerve fiber indicator parameters showed the best AUCs and sensitivities both with GDx VCC and ECC in diagnosing all severities of glaucoma. AUCs and sensitivities of all RNFL parameters were comparable between the VCC and ECC algorithms (P>0.20 for all comparisons). Likelihood ratios associated with the diagnostic categorization of RNFL parameters were comparable between the VCC and ECC algorithms. CONCLUSION: In scans satisfying the manufacturer-recommended quality parameters, which were significantly greater with ECC than VCC algorithm, diagnostic abilities of GDx ECC and VCC in glaucoma were similar.

Structure-Function Relationship in Glaucoma Using Ganglion Cell-Inner Plexiform Layer Thickness Measurements.

PURPOSE: To evaluate the structure-function relationship between ganglion cell-inner plexiform layer (GCIPL) thickness at the macula and 10-2 standard automated perimetry (SAP) in glaucoma and to evaluate the relationship using a recently proposed linear model. METHODS: In a cross-sectional analysis, structure-function relationship was determined in 50 glaucomatous eyes (40 patients, mean deviation: -15.4 ± 7.5 dB) and 21 control eyes (13 subjects, mean deviation: -3.4 ± 3.0 dB), which had undergone 10-2 SAP and GCIPL imaging on the same day. Functional loss was derived from total deviation numerical values on 10-2 SAP and calculated on both a linear (reciprocal of Lambert) and a decibel scale after accounting for the retinal ganglion cell displacement at the macula. Strength of relationship was reported as coefficient of determination (R2) of the linear regression models fitted to the data separately for different sectors. The relationship was also evaluated using a linear model. RESULTS: The R2 for the associations between GCIPL thickness sectors and the corresponding sector SAP total deviation values ranged from 0.19 (for superonasal GCIPL sector) to 0.60 (for average GCIPL thickness) when functional loss was calculated on the decibel scale and 0.16 (for superonasal sector) to 0.54 (for inferior sector) on the linear scale. All associations were statistically significant (P < 0.05). The linear model fitted the data reasonably well. CONCLUSIONS: Significant structure-function associations were found between GCIPL thickness measurements at the macula and the functional loss measured on 10-2 SAP in glaucoma. Best fit was found for the inferior and average GCIPL sector thickness. The linear model was useful to study the structure-function relationship.

Comparing glaucoma progression on 24-2 and 10-2 visual field examinations.

PURPOSE: To compare the rate of mean deviation (MD) change on 24-2 versus 10-2 VFs in treated glaucomatous eyes with 5 or more examinations. METHODS: In a retrospective study, 24-2 and 10-2 VFs of 131 glaucoma patients (167 eyes) who had undergone at least 5 VFs examinations during their follow-up were analyzed. All these patients had VF defects both on 24-2 and 10-2 VFs. Rates of MD change were calculated using best linear unbiased predictions (BLUP). RESULTS: Median age, MD on 24-2 VF at baseline, number of VFs performed during follow-up and follow-up duration were 55 years, -16.9 dB, 9 and 9 years respectively. Median rate of MD change was significantly greater (p<0.001) on 10-2 VF (-0.26 dB/year; interquartile range [IQR]: -0.47, -0.11) compared to 24-2 VFs (-0.19 dB/year; IQR: -0.41, -0.03). Comparing the rates of MD change in eyes with different severities of VF loss (early [MD better than -6 dB], moderate [-6 dB to -12 dB], advanced [-12 to -20 dB] and severe [MD worse than -20 dB]) at baseline (based on the MD on 24-2 VF), median rate of MD change was comparable between 10-2 and 24-2 VFs in mild (-0.45 dB/year vs. -0.40 dB/year, P = 0.42) and moderate (-0.32 dB/year vs. -0.40 dB/year, P = 0.26) VF loss categories, while the same were significantly greater on 10-2 VFs in advanced (-0.28 dB/year vs. -0.21 dB/year, P = 0.04) and severe (-0.18 dB/year vs. -0.06 dB/year, P<0.001) VF loss categories. CONCLUSIONS: In patients with VF defects both on 24-2 and 10-2 VFs, evaluating the rate of MD change on 10-2 VFs may help in better estimation of glaucoma progression, especially so in eyes with advanced glaucoma at baseline.

Comparing the Structure-Function Relationship at the Macula With Standard Automated Perimetry and Microperimetry.

PURPOSE: To compare the structure-function relationship between ganglion cell-inner plexiform layer (GCIPL) thickness measurements using spectral-domain optical coherence tomography (SDOCT) and visual sensitivities measured using standard automated perimetry (SAP) and microperimetry (MP) at the macula in glaucoma. METHODS: In a prospective study, 45 control eyes (29 subjects) and 60 glaucoma eyes (45 patients) underwent visual sensitivity estimation at the macula (central 10°) by SAP and MP, and GCIPL thickness measurement at the macula by SDOCT. Structure-function relationships between GCILP thickness and visual sensitivity loss with SAP and MP at various macular sectors were assessed using the Hood and Kardon model. To compare structure-function relationship with SAP and MP, we calculated the number of data points falling outside the 5th and the 95th percentile values of the Hood and Kardon model with each of the perimeters. RESULTS: The number of points falling outside the 5th and 95th percentile values of the Hood and Kardon model ranged from 28 (superior sector) to 48 (inferonasal sector) with SAP and 33 (superior sector) to 49 (inferonasal sector) with MP. The difference in the number of points falling outside the 5th and 95th percentile values with SAP and MP was statistically insignificant (P > 0.05, χ(2) test) for all the sectors. CONCLUSIONS: Visual sensitivity measurements of both SAP and MP demonstrated a similar relationship with the GCIPL measurements of SDOCT at the macula in glaucoma.

The ISNT rule in glaucoma: revisiting with spectral domain optical coherence tomography.

PURPOSE: To evaluate the ability of the neuroretinal rim (NRR) rules determined using spectral domain optical coherence tomography (SDOCT) in diagnosing glaucoma and to study the effect of optic disc size and disease severity on the diagnostic ability of these rules. METHODS: In a cross-sectional study, 125 eyes of 96 glaucoma patients and 96 eyes of 72 control subjects underwent optic nerve head (ONH) imaging with SDOCT. Inferior (I), superior (S), nasal (N) and temporal (T) NRR areas were automatically determined by the sdoct software. Diagnostic abilities of ISNT (I > S > N > T), IT (I > T) and ST (S > T) rules in glaucoma were evaluated using sensitivity, specificity and likelihood ratios (LR). Effect of optic disc size and disease severity [based on mean deviation (MD) on visual fields] on the diagnostic ability of the NRR rules was evaluated using regression models. RESULTS: Sensitivities of ISNT, IT and ST rules were 80.8%, 60.0% and 29.6%, respectively, and the specificities were 32.3%, 84.4% and 93.8%, respectively. Positive LRs of ISNT, IT and ST rules were 1.19, 3.84 and 4.74, respectively, and negative LRs were 0.60, 0.47 and 0.75, respectively. Sensitivities of ISNT (coefficient: -1.06, p = 0.02) and IT (-0.71, 0.05) rules decreased with increasing disc size. Positive LR of IT rule increased significantly (-0.01, 0.04) with decreasing MD, and negative LR of IT rule decreased (got better) significantly (0.26, 0.05) with decreasing disc size. CONCLUSIONS: Neuroretinal rim rules, as determined by SDOCT, do not allow robust differentiation of glaucomatous from non-glaucomatous discs.

Atypical birefringence pattern and the diagnostic ability of scanning laser polarimetry with enhanced corneal compensation in glaucoma.

PURPOSE: To evaluate the effect of typical scan score (TSS), when within the acceptable limits, on the diagnostic performance of retinal nerve fibre layer (RNFL) parameters with the enhanced corneal compensation (ECC) protocol of scanning laser polarimetry (SLP) in glaucoma. METHODS: In a cross-sectional study, 203 eyes of 160 glaucoma patients and 140 eyes of 104 control subjects underwent RNFL imaging with the ECC protocol of SLP. TSS was used to quantify atypical birefringence pattern (ABP) images. Influence of TSS on the diagnostic ability of SLP parameters was evaluated by receiver operating characteristic (ROC) regression models after adjusting for the effect of disease severity [based on mean deviation (MD)] on standard automated perimetry). RESULTS: Diagnostic abilities of all RNFL parameters of SLP increased when the TSS values were higher. This effect was statistically significant for TSNIT (coefficient: 0.08, p<0.001) and inferior average parameters (coefficient: 0.06, p=0.002) but not for nerve fibre indicator (NFI, coefficient: 0.03, p=0.21). In early glaucoma (MD of -5 dB), predicted area under ROC curve (AUC) for TSNIT average parameter improved from 0.642 at a TSS of 90 to 0.845 at a TSS of 100. In advanced glaucoma (MD of -15 dB), AUC for TSNIT average improved from 0.832 at a TSS of 90 to 0.947 at 100. CONCLUSION: Diagnostic performances of TSNIT and inferior average RNFL parameters with ECC protocol of SLP were significantly influenced by TSS even when the TSS values were within the acceptable limits. Diagnostic ability of NFI was unaffected by TSS values.

Comparing spectral-domain optical coherence tomography and standard automated perimetry to diagnose glaucomatous optic neuropathy.

PURPOSE: To compare the abilities of standard automated perimetry (SAP) and spectral-domain optical coherence tomography (SDOCT) in diagnosing eyes with glaucomatous optic neuropathy (GON). METHODS: In a cross-sectional study, 280 eyes of 175 subjects referred to tertiary eye care center by general ophthalmologists for a glaucoma evaluation underwent retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC) imaging with SDOCT. All subjects had at least 2 reliable and repeatable SAP. Two glaucoma experts masked to clinical and SAP results classified the optic nerves into GON and nonglaucomatous groups based on digital optic disc photographs. Ability of SDOCT parameters and SAP to discriminate GON eyes from nonglaucomatous eyes was evaluated using sensitivity, specificity, and likelihood ratios (LR). RESULTS: Experts classified 179 eyes into GON and 101 eyes into nonglaucomatous group. Sensitivity of SAP (69.8%) was significantly lower (P<0.05) than that of inferior quadrant RNFL thickness (83.8%), average RNFL thickness (77.2%), GCC focal loss volume (FLV, 81.5%), and global loss volume (GLV, 82.6%). Specificity and positive LR of SAP (95% and14.1, respectively) were significantly greater than those of all RNFL parameters, FLV (84.2% and 5.1) and GLV (82.2% and 4.6). Negative LR of SAP (0.32) was significantly inferior to that of inferior quadrant RNFL thickness (0.22), FLV (0.22), and GLV (0.21). CONCLUSIONS: Most of the RNFL and GCC parameters of SDOCT had better sensitivities and negative LRs to diagnose GON compared with SAP. The specificities and positive LRs of most SDOCT parameters were inferior to that of SAP.

Role of visual field reliability indices in ruling out glaucoma.

IMPORTANCE: Standard automated perimetry is the current criterion standard for assessment of visual field (VF) loss in glaucoma. The 3 commonly used reliability indices to judge the quality of standard automated perimetry results are fixation losses (FLs) and false-positive (FP) and false-negative (FN) response rates. However, the influence of reliability indices, when within the manufacturer-recommended limits, on VF classification has been sparsely studied. OBJECTIVE: To evaluate the role of VF reliability indices in ruling out glaucoma. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional study of 291 eyes of 291 participants referred to a tertiary eye care facility by general ophthalmologists. The participants were suspected to have glaucoma based on optic disc appearance, but the eyes were judged to be normal with physiological cupping by glaucoma experts on masked evaluation of optic disc photographs. All participants underwent VF testing with the Swedish interactive threshold algorithm standard 24-2 program. MAIN OUTCOMES AND MEASURES: Logistic regression models were used to evaluate the associations between reliability indices and FP classifications on VF testing (glaucoma hemifield test as outside normal limits and pattern standard deviation with P < .05). RESULTS: Median FL, FP, and FN response rates were 7%, 1%, and 2%, respectively. Among the 241 participants with reliable VF results (FL <20% and FP response rate <15%), the VF classification was normal in 188 (78.0%) and glaucoma (FP) in 53 (22.0%). Probability of FP VF classification was associated with FN response rates (odds ratio [OR], 1.36; 95% CI, 1.25-1.48, P < .001) but did not appear to be associated with FLs (OR, 0.96; 95% CI, 0.90-1.03, P = .30) or FP response rates (OR, 0.96; 95% CI, 0.83-1.12, P = .64). Predicted probability of FP VF classification was 9% (95% CI, 6%-14%), 40% (32%-49%), and 82% (68%-91%) at FN response rates of 0%, 8%, and 16%, respectively. CONCLUSIONS AND RELEVANCE: This study suggests that FN response rates have an effect on the ability of automated VF assessments to rule out glaucoma. Since FN response rates are ignored by the manufacturer while flagging a test as unreliable, clinicians and researchers may benefit by realizing that FN response rates can lead to FP VF classification, even when their frequencies are small.

Reference Standard Test and the Diagnostic Ability of Spectral Domain Optical Coherence Tomography in Glaucoma.

PURPOSE: To evaluate the relationship between the reference standard used to diagnose glaucoma and the diagnostic ability of spectral domain optical coherence tomograph (SDOCT). METHODS: In a cross-sectional study, 280 eyes of 175 consecutive subjects, referred to a tertiary eye care center for glaucoma evaluation, underwent optic disc photography, visual field (VF) examination, and SDOCT examination. The cohort was divided into glaucoma and control groups based on 3 reference standards for glaucoma diagnosis: first based on the optic disc classification (179 glaucoma and 101 control eyes), second on VF classification (glaucoma hemifield test outside normal limits and pattern SD with P-value of <5%, 130 glaucoma and 150 control eyes), and third on the presence of both glaucomatous optic disc and glaucomatous VF (125 glaucoma and 155 control eyes). Relationship between the reference standards and the diagnostic parameters of SDOCT were evaluated using areas under the receiver operating characteristic curve, sensitivity, and specificity. RESULTS: Areas under the receiver operating characteristic curve and sensitivities of most of the SDOCT parameters obtained with the 3 reference standards (ranging from 0.74 to 0.88 and 72% to 88%, respectively) were comparable (P>0.05). However, specificities of SDOCT parameters were significantly greater (P<0.05) with optic disc classification as reference standard (74% to 88%) compared with VF classification as reference standard (57% to 74%). CONCLUSIONS: Diagnostic parameters of SDOCT that was significantly affected by reference standard was the specificity, which was greater with optic disc classification as the reference standard. This has to be considered when comparing the diagnostic ability of SDOCT across studies.

Ganglion cell-inner plexiform layer thickness of high definition optical coherence tomography in perimetric and preperimetric glaucoma.

PURPOSE: We determined the diagnostic performance of ganglion cell-inner plexiform layer (GCIPL) parameters of high definition optical coherence tomography (HD-OCT) in perimetric and preperimetric glaucoma, and compared it to optic nerve head (ONH) and peripapillary retinal nerve fiber layer (RNFL) parameters. METHODS: In a cross-sectional study, 53 eyes of normal subjects and 83 eyes of glaucoma patients (62 perimetric and 21 preperimetric) from the Longitudinal Glaucoma Evaluation Study (LOGES) underwent HD-OCT imaging with Optic Disc and Macular Cube protocols. Diagnostic abilities of GCIPL, ONH, and RNFL parameters were determined using area under receiver operating characteristic curves (AUC) and likelihood ratios (LR). RESULTS: The AUCs of GCIPL parameters to diagnose perimetric glaucoma ranged from 0.84 to 0.90. The same of ONH and RNFL parameters ranged from 0.88 to 0.97 and 0.56 to 0.94, respectively. The AUCs of GCIPL, ONH, and RNFL parameters to diagnose preperimetric glaucoma ranged from 0.55 to 0.63, 0.77 to 0.92, and 0.39 to 0.80, respectively. For diagnosing preperimetric glaucoma, AUCs of all GCIPL parameters were significantly lower (P < 0.05) than those of the global ONH (vertical cup-to-disc ratio [CDR]; AUC, 0.92) and RNFL (average RNFL; AUC, 0.79) parameters. Outside normal limits category of GCIPL parameters also were associated with significantly smaller effects on the posttest probability of perimetric and preperimetric glaucoma. CONCLUSIONS: The diagnostic ability of GCIPL parameters was similar to that of ONH and peripapillary RNFL parameters in perimetric glaucoma. However, in preperimetric glaucoma, the diagnostic ability of GCIPL parameters was significantly lower than that of ONH and RNFL parameters.

Scanning the macula for detecting glaucoma.

BACKGROUND: With the advent of spectral domain optical coherence tomography (SDOCT), there has been a renewed interest in macular region for detection of glaucoma. However, most macular SDOCT parameters currently are thickness parameters which evaluate thinning of the macular layers but do not quantify the extent of area over which the thinning has occurred. We therefore calculated a new macular parameter, "ganglion cell complex surface abnormality ratio (GCC SAR)" that represented the surface area over which the macular thickness was decreased. PURPOSE: To evaluate the ability of SAR in detecting perimetric and preperimetric glaucoma. DESIGN: Retrospective image analysis. MATERIALS AND METHODS: 68 eyes with perimetric glaucoma, 62 eyes with preperimetric glaucoma and 165 control eyes underwent GCC imaging with SDOCT. SAR was calculated as the ratio of the abnormal to total area on the GCC significance map. STATISTICAL ANALYSIS: Diagnostic ability of SAR in glaucoma was compared against that of the standard parameters generated by the SDOCT software using area under receiver operating characteristic curves (AUC) and sensitivities at fixed specificities. RESULTS: AUC of SAR (0.91) was statistically significantly better than that of GCC average thickness (0.86, P = 0.001) and GCC global loss volume (GLV; 0.88, P = 0.01) in differentiating perimetric glaucoma from control eyes. In differentiating preperimetric glaucoma from control eyes, AUC of SAR (0.72) was comparable to that of GCC average thickness (0.70, P > 0.05) and GLV (0.72, P > 0.05). Sensitivities at specificities of 80% and 95% of SAR were comparable (P > 0.05 for all comparisons) to that of GCC average thickness and GLV in diagnosing perimetric and preperimetric glaucoma. CONCLUSION: GCC SAR had a better ability to diagnose perimetric glaucoma compared to the SDOCT software provided global GCC parameters. However, in diagnosing preperimetric glaucoma, the ability of SAR was similar to that of software provided global GCC parameters.