Ganglion Cell Complex: The Optimal Measure for Detection of Structural Progression in the Macula

Racial-ethnic disparities in concurrent rates of peripapillary & macular OCT parameters among a large glaucomatous clinical population

OBJECTIVES

To compare rates of change in peripapillary retinal nerve fibre layer (pRNFL) and macular ganglion cell-inner plexiform layer (mGCIPL) parameters among different race-ethnicities from a large electronic health record database of subjects with or suspected of glaucoma.

METHODS

In this retrospective cohort study, rates of change were obtained using joint longitudinal linear mixed models for eyes with ≥3 visits and ≥1 year of follow-up, adjusting for age, sex, intraocular pressure, central corneal thickness, and baseline pRNFL and mGCIPL thickness. Best linear unbiased predictor estimates of various parameters were stratified by baseline glaucoma severity and analysed by racial-ethnic group.

RESULTS

A total of 21,472 spectral domain optical coherence tomography (OCT) pRNFL scans and 14,431 mGCIPL scans from 2002 eyes were evaluated. A total of 200 (15.6%) and 601 (46.8%) subjects identified as non-Hispanic Black (NHB) and Hispanic, respectively. NHB eyes exhibited faster rates of change in pRNFL among glaucoma suspect (global pRNFL -0.57 ± 0.55 µm/year vs. -0.37 ± 0.62 µm/year among Hispanics, p < 0.001), mild glaucoma (superior pRNFL quadrant -1.20 ± 1.06 µm/year vs. -0.75 ± 1.51 µm/year among non-Hispanic Whites (NHW), p = 0.043), and moderate glaucoma eyes (superior pRNFL quadrant -1.31 ± 1.49 µm/year vs. -0.52 ± 1.26 µm/year among Hispanics, p = 0.003). NHB eyes exhibited faster rates of mGCIPL loss corresponding to pRNFL rates. Global pRNFL and mGCIPL rates were strongly correlated (R2 = 0.70).

CONCLUSIONS

Adjusted rates of pRNFL and mGCIPL loss significantly differed between racial-ethnic groups when stratified by glaucoma severity, with faster rates among NHB patients. These differences highlight key racial-ethnic disparities in adjusted rates of glaucoma OCT parameters.

Detecting Fast Progressors: Comparing a Bayesian Longitudinal Model to Linear Regression for Detecting Structural Changes in Glaucoma

PURPOSE

Demonstrate that a novel Bayesian hierarchical spatial longitudinal (HSL) model identifies macular superpixels with rapidly deteriorating ganglion cell complex (GCC) thickness more efficiently than simple linear regression (SLR).

DESIGN

Prospective cohort study.

SETTING

Tertiary Glaucoma Center.

SUBJECTS

One hundred eleven eyes (111 patients) with moderate to severe glaucoma at baseline and ≥4 macular optical coherence tomography scans and ≥2 years of follow-up.

OBSERVATION PROCEDURE

Superpixel-patient-specific GCC slopes and their posterior variances in 49 superpixels were derived from our latest Bayesian HSL model and Bayesian SLR. A simulation cohort was created with known intercepts, slopes, and residual variances in individual superpixels.

MAIN OUTCOME MEASURES

We compared HSL and SLR in the fastest progressing deciles on (1) proportion of superpixels identified as significantly progressing in the simulation study and compared to SLR slopes in cohort data; (2) root mean square error (RMSE), and SLR/HSL RMSE ratios.

RESULTS

Cohort- In the fastest decile of slopes per SLR, 77% and 80% of superpixels progressed significantly according to SLR and HSL, respectively. The SLR/HSL posterior SD ratio had a median of 1.83, with 90% of ratios favoring HSL. Simulation- HSL identified 89% significant negative slopes in the fastest progressing decile vs 64% for SLR. SLR/HSL RMSE ratio was 1.36 for the fastest decile of slopes, with 83% of RMSE ratios favoring HSL.

CONCLUSION

The Bayesian HSL model improves the estimation efficiency of local GCC rates of change regardless of underlying true rates of change, particularly in fast progressors.

Association of Long-Term Intraocular Pressure Variability and Rate of Ganglion Complex Thinning in Patients With Glaucoma

PURPOSE

To evaluate the association of mean intraocular pressure (IOP) and IOP variability (IOP fluctuation [SD of IOP] and the IOP range) with the rate of ganglion cell complex (GCC) layer thinning over time in patients with glaucoma.

DESIGN

Prospective cohort study.

METHODS

Participants with at least 4 visits and 2 years of follow-up of optical coherence tomography tests were included. A linear mixed-effect model was used to investigate the association of IOP parameters with the rates of GCC thinning. Subgroup analyses were conducted for eyes with early (MD ≥ -6 dB), and moderate to advanced stage (MD < -6 dB) at baseline.

RESULTS

The cohort consisted of 369 eyes of 249 glaucoma patients (282 early glaucoma and 87 moderate to advanced glaucoma) with mean (standard deviation [SD]) age of 68.2 (10.7) years over 5.1 years of follow-up. The mean rate of GCC change was -0.59 (95% confidence interval [CI], -0.67 to -0.52) µm per year. In multivariable models, faster annual rate of GCC thinning was associated with a higher IOP fluctuation (-0.17 [95% CI, -0.23 to -0.11] µm per 1-mmHg higher, P < .001) or higher IOP range (-0.07 [95% CI, -0.09 to -0.05] µm per 1-mmHg higher, P < .001) after adjustment for mean IOP and other confounding factors. Similar results were found for early and moderate to advanced stages of glaucoma.

CONCLUSIONS

IOP variability showed an independent association with macular change in patients with glaucoma regardless of severity at baseline, even after adjustment for mean IOP, supporting its potential value as a therapeutic target for clinical decision-making.

A Bayesian Hierarchical Spatial Longitudinal Model Improves Estimation of Local Macular Rates of Change in Glaucomatous Eyes

Purpose

Demonstrate that a novel Bayesian hierarchical spatial longitudinal (HSL) model improves estimation of local macular ganglion cell complex (GCC) rates of change compared to simple linear regression (SLR) and a conditional autoregressive (CAR) model.

Methods

We analyzed GCC thickness measurements within 49 macular superpixels in 111 eyes (111 patients) with four or more macular optical coherence tomography scans and two or more years of follow-up. We compared superpixel-patient-specific estimates and their posterior variances derived from the latest version of a recently developed Bayesian HSL model, CAR, and SLR. We performed a simulation study to compare the accuracy of intercept and slope estimates in individual superpixels.

Results

HSL identified a significantly higher proportion of significant negative slopes in 13/49 superpixels and a significantly lower proportion of significant positive slopes in 21/49 superpixels than SLR. In the simulation study, the median (tenth, ninetieth percentile) ratio of mean squared error of SLR [CAR] over HSL for intercepts and slopes were 1.91 (1.23, 2.75) [1.51 (1.05, 2.20)] and 3.25 (1.40, 10.14) [2.36 (1.17, 5.56)], respectively.

Conclusions

A novel Bayesian HSL model improves estimation accuracy of patient-specific local GCC rates of change. The proposed model is more than twice as efficient as SLR for estimating superpixel-patient slopes and identifies a higher proportion of deteriorating superpixels than SLR while minimizing false-positive detection rates.

Translational Relevance

The proposed HSL model can be used to model macular structural measurements to detect individual glaucoma progression earlier and more efficiently in clinical and research settings.

Association of Blood Pressure With Rates of Macular Ganglion Cell Complex Thinning in Patients With Glaucoma

Importance

There are scarce data on the association of blood pressure measures with subsequent macular structural rates of change in patients with glaucoma.

Objective

To investigate the association of baseline blood pressure measures with rates of change of the macular ganglion cell complex in patients with central or moderate to advanced glaucoma damage at baseline.

Design, Setting, and Participants

This prospective cohort study, conducted from August 2021 to August 2022, used data from patients in the Advanced Glaucoma Progression Study at the University of California, Los Angeles. Participants were between 39 and 80 years of age and had more than 4 macular imaging tests and 2 or more years of follow-up.

Exposures

A diagnosis of glaucoma with either central damage or a visual field mean deviation worse than -6 dB.

Main Outcomes and Measures

The main outcome was the association of blood pressure measures with ganglion cell complex rates of change. Macular ganglion cell complex thickness rates of change were estimated with a bayesian hierarchical model. This model included relevant demographic and clinical factors. Blood pressure measures, intraocular pressure, and their interactions were added to the model to assess the association of baseline blood pressure measures with global ganglion cell complex rates of change.

Results

The cohort included 105 eyes from 105 participants. The mean (SD) age, 10-2 visual field mean deviation, and follow-up time were 66.9 (8.5) years, -8.3 (5.3) dB, and 3.6 (0.4) years, respectively, and 67 patients (63.8%) were female. The racial and ethnic makeup of the cohort was 15 African American (14.3%), 23 Asian (21.9%), 12 Hispanic (11.4%), and 55 White (52.4%) individuals based on patient self-report. In multivariable analyses, female sex, history of taking blood pressure medications, higher intraocular pressure, thicker central corneal thickness, shorter axial length, higher contrast sensitivity at 12 cycles per degree, and higher baseline 10-2 visual field mean deviation were associated with faster ganglion cell complex thinning. Lower diastolic blood pressure was associated with faster rates of ganglion cell complex thinning at higher intraocular pressures. For intraocular pressures of 8 and of 16 mm Hg (10% and 90% quantiles, respectively), every 10 mm Hg-lower increment of diastolic blood pressure was associated with 0.011 μm/y slower and -0.130 μm/y faster rates of ganglion cell complex thinning, respectively.

Conclusions and Relevance

In this cohort study, a combination of lower diastolic blood pressure and higher intraocular pressure at baseline was associated with faster rates of ganglion cell complex thinning. These findings support consideration of evaluating and addressing diastolic blood pressure as a therapeutic measure in patients with glaucoma if supported by appropriate clinical trials.

Comparison of Ganglion Cell Layer and Ganglion Cell/Inner Plexiform Layer Measures for Detection of Early Glaucoma

PURPOSE

To test the hypothesis that macular ganglion cell layer (GCL) measurements detect early glaucoma with higher accuracy than ganglion cell/inner plexiform layer (GCIPL) thickness measurements.

DESIGN

Cross-sectional study.

PARTICIPANTS

The first cohort included 58 glaucomatous eyes with visual field mean deviation (MD) ≥ -6 dB and 125 normal eyes. The second cohort included 72 glaucomatous and 73 normal/glaucoma suspect (GS) eyes with scans able to create GCL/GCIPL deviation maps.

METHODS

In the first cohort, 8 × 8 GCL and GCIPL grids were exported and 5 superior and inferior sectors were defined. Global and sectoral GCL and GCIPL measures were used to predict glaucoma. In the second cohort, proportions of scan areas with abnormal (< 5% and < 1% cutoffs) and supernormal (> 95% and > 99% cutoffs) thicknesses on deviation maps were calculated. The extents of GCL and GCIPL abnormal areas were used to predict glaucoma.

MAIN OUTCOME MEASURES

Extents of abnormal GCL/GCIPL regions and areas under receiver operating characteristic curves (AUROC) for prediction of glaucoma were compared between GCL or GCIPL measures.

RESULTS

The average ± standard deviation MDs were -3.7 ± 1.6 dB and -2.7 ± 1.8 dB in glaucomatous eyes in the first and second cohorts, respectively. Global GCIPL thickness measures (central 18° × 18° macular region) performed better than GCL for early detection of glaucoma (AUROC, 0.928 vs. 0.884, respectively; P = 0.004). Superior and inferior sector 3 thickness measures provided the best discrimination with both GCL and GCIPL (inferior GCL AUROC, 0.860 vs. GCIPL AUROC, 0.916 [P = 0.001]; superior GCL AUROC, 0.916 vs. GCIPL AUROC, 0.900 [P = 0.24]). The extents of abnormal GCL regions at a 1% cutoff in the central elliptical area were 17.5 ± 22.2% and 6.4 ± 10.8% in glaucomatous and normal/GS eyes, respectively, versus 17.0 ± 22.2% and 5.7 ± 10.5%, respectively, for GCIPL (P = 0.06 for GCL and 0.002 for GCIPL). The extents of GCL and GCIPL supernormal regions were mostly similar in glaucomatous and normal eyes. The best performance for prediction of glaucoma in the second cohort was detected at a P value of < 1% within the entire scan for both GCL and GCIPL (AUC, 0.681 vs. 0.668, respectively; P = 0.29).

CONCLUSIONS

Macular GCL and GCIPL thicknesses are equivalent for identifying early glaucoma with current OCT technology. This is likely explained by limitations of inner macular layer segmentation and concurrent changes within the inner plexiform layer in early glaucoma.

Effect of idiopathic epiretinal membrane on macular ganglion cell complex measurement in eyes with glaucoma

Background/objectives

Co-existing idiopathic epiretinal membrane (ERM) and glaucoma complicate the estimation of glaucoma severity via optical coherence tomography (OCT). We investigated the effect of ERM and a new associated parameter, SUKIMA (space between the ERM and retinal surface), on ganglion cell complex (GCC) thickness in eyes with glaucoma, based on a matched comparison of visual field defects.

Subjects/methods

We retrospectively recruited 41 eyes from 34 glaucoma patients with idiopathic ERM and 41 eyes from 41 glaucoma patients without ERM as controls (matched by age, axial length, and mean visual field deviation). The thicknesses of GCC layers [retinal nerve fiber layer (RNFL), ganglion cell layer + inner plexiform layer (GCIPL), and GCC (RNFL + GCIPL)] were measured with swept-source OCT. We investigated the presence of SUKIMA and its effect on GCC measurements.

Results

RNFL, GCIPL, and GCC were thicker in ERM (+) eyes than in control eyes (31.0 ± 12.3 μm vs. 22.7 ± 10.8 μm, 62.6 ± 12.2 μm vs. 53.8 ± 5.9 μm, and 91.8 ± 16.6 μm vs. 76.8 ± 13.3 μm, respectively; P &lt; 0.01). Eyes in the ERM-associated SUKIMA (+) group had thicker GCIPL and GCC than those in the ERM-associated SUKIMA (−) and control groups (P &lt; 0.01).

Conclusion

ERM-associated SUKIMA affects GCC thickness and can result in underestimations of glaucoma severity. We should check for the presence of ERM using a B mode scan as well as check for the SKIMA sign.

Detection of Early Glaucomatous Damage: Performance of Summary Statistics From Optical Coherence Tomography and Perimetry

Purpose

To evaluate the diagnostic performance of optical coherence tomography (OCT) and visual field (VF) summary statistics (metrics) that are available in OCT and VF reports.

Methods

OCT disc and macular scans and 24-2 and 10-2 VFs were obtained from 56 healthy control (HC) eyes/participants and 61 eyes/patients with 24-2 mean deviation of better than –6 dB. All metrics were obtained from OCT radial, circle, and posterior pole cube scans and 24-2 and 10-2 VFs. Their diagnostic performances were evaluated, in isolation and in combinations. For specificity, the 56 HC eyes were used. For sensitivity, 40 of the 61 patient eyes were deemed likely glaucomatous based on an automated topographic method that evaluates structure–function (S–F) agreement. Any 1 of these 40 eyes not judged as abnormal by any given metric was considered a false negative.

Results

All single OCT and VF metrics misclassified HCs as glaucomatous and missed likely glaucomatous eyes. The best performing single metric was the temporal inferior thickness of the 3.5-mm circle scan, with 96% specificity and 83% sensitivity. Combinations of OCT–OCT and OCT–VF metrics markedly improved specificity. A newly proposed metric that evaluates structure–structure (S–S) agreement at a hemifield level had the highest accuracy. This S–S metric had 98% specificity and 80% sensitivity.

Conclusions

OCT and VF metrics, single or in combinations, have only moderate sensitivity for eyes with early glaucoma.

Translational Relevance

OCT and VF metrics combinations evaluating S–S or S–F agreement can be highly specific, which is an important implication for clinical and research purposes.