Macular ganglion cell-inner plexiform vs retinal nerve fiber layer measurement to detect early glaucoma with superior or inferior hemifield defects

Correlations between Steady-State Pattern Electroretinogram and Humphrey Visual Field Analyzer Global Indices and Their Associations with Retinal Ganglion Cell Layer-Inner Plexiform Layer Thickness in Glaucoma Suspects

Purpose

The purpose of this study was to investigate the utility of steady state pattern electroretinogram (ss-PERG) in detecting retinal ganglion cell (RGC) dysfunction in glaucoma suspects (GS) who had normal 24-2 Humphrey Visual Fields (HFA).

Materials and Methods

This was a prospective cohort study of GS patients who were identified based on optic disc appearance with normal HFAs. Patients received a complete eye examination, standard automated perimetry (SAP), optical coherence tomography (OCT), and ss-PERG measurements. The ss-PERG parameters, Magnitude (Mag), Magnitude D (MagD), and MagD/Mag ratio, were examined, along with their relationships between HFA and OCT measurements.

Results

Twenty-five patients were included in this study, with a total of 49 eyes. Fifteen eyes had abnormal ss-PERG parameters and when compared to GS eyes with normal ss-PERG parameters, there were significant differences in HFA 24-2, retinal nerve fiber layer (RNFL) thickness, and ganglion cell layer and inner plexiform layer (GCL + IPL) thickness. All ss-PERG parameters were significantly correlated with 24-2 VF mean deviation (MD) and visual field index (VFI), as well as 10-2 VF MD after controlling for age, sex, intraocular pressure, central corneal thickness, and spherical equivalent. When controlled for age, spherical equivalent, and IOP, MagD/Mag ratio significantly contributed to the variance in average GCL + IPL thicknesses, whereas 24-2 VF MD and 10-2 VF MD did not. MagD/Mag ratio also significantly accounted for variance in all macular GCL + IPL sectors, while 10-2 VF MD did not.

Conclusions

ss-PERG has significant correlations with HFA global indices and was predictive of GCL + IPL thickness in GS patients. Clinical Significance. ss-PERG may serve as a useful functional tool for detecting and measuring RGC dysfunction in GS. It appears to be more sensitive than HFA in the detection of early changes in GCL + IPL thicknesses and may be helpful to use in conjunction with current diagnostic studies to improve the ability of monitoring GS progression.

Association of Rates of Ganglion Cell and Inner Plexiform Thinning With Development of Glaucoma in Eyes With Suspected Glaucoma

Importance

In eyes with suspected glaucoma, it is clinically relevant to find diagnostic tests for the risk of development of perimetric glaucoma.

Objective

To investigate the association between rates of ganglion cell/inner plexiform layer (GCIPL) and circumpapillary retinal nerve fiber layer (cpRNFL) thinning and the development of perimetric glaucoma in eyes with suspected glaucoma.

Design, Setting, and Participants

This observational cohort study used data collected in December 2021 from a tertiary center study and a multicenter study. Participants with suspected glaucoma were followed up for 3.1 years. The study was designed in December 2021 and finalized in August 2022.

Exposures

Development of perimetric glaucoma was defined as having 3 consecutive results showing abnormal visual fields. Using linear mixed-effect models, rates of GCIPL were compared between eyes with suspected glaucoma that did and did not develop perimetric glaucoma. A joint longitudinal multivariable survival model was used to investigate the performance of rates of GCIPL and cpRNFL thinning in predicting the risk of developing perimetric glaucoma.

Main Outcomes and Measures

Rates of GCIPL thinning and hazard ratio (HR) of developing perimetric glaucoma.

Results

Among a total of 462 participants, the mean (SD) age was 63.3 (11.1) years, and 275 patients (60%) were female. Of 658 eyes, 153 eyes (23%) developed perimetric glaucoma. The mean rates of GCIPL thinning were faster in eyes that developed perimetric glaucoma (-1.28 vs -0.66 μm/y for minimum GCIPL thinning; difference, -0.62; 95% CI, -1.07 to -0.16; P = .02). Based on the joint longitudinal survival model, every 1-μm/y faster rate of minimum GCIPL and rate of global cpRNFL thinning were associated with a 2.4 and 1.9 higher risk of developing perimetric glaucoma, respectively (HR, 2.4; 95% CI, 1.8 to 3.2, and HR, 1.99; 95% CI, 1.76 to 2.22, respectively; P < .001). Among the predictive factors, African American race (HR, 1.56; 95% CI, 1.05 to 2.34; P = .02), male sex (HR, 1.47; 95% CI, 1.02 to 2.15; P = .03), 1-dB higher baseline visual field pattern standard deviation (HR, 1.73; 95% CI, 1.56 to 1.91; P < .001), and 1-mm Hg higher mean intraocular pressure during follow-up (HR, 1.11; 95% CI, 1.05 to 1.17; P < .001) were associated with higher risk of developing perimetric glaucoma.

Conclusions and Relevance

This study found that faster rates of GCIPL and cpRNFL thinning were associated with higher risks of developing perimetric glaucoma. Rates of cpRNFL thinning and specifically GCIPL thinning may be useful measures for monitoring eyes with suspected glaucoma.

Central Macular Topographic and Volumetric Measures: New Biomarkers for Detection of Glaucoma

Purpose

To test the hypothesis that newly developed shape measures using optical coherence tomography (OCT) macular volume scans can discriminate patients with perimetric glaucoma from healthy subjects.

Methods

OCT structural measures defining macular topography and volume were recently developed based on cubic Bézier curves. We exported macular volume scans from 135 eyes with glaucoma (133 patients) and 155 healthy eyes (85 subjects) and estimated global and quadrant-based measures. The best subset of measures to predict glaucoma was explored with a gradient boost model (GBM) with subsequent logistic regression. Accuracy and area under receiver operating curves (AUC) were the primary metrics. In addition, we separately investigated model performance in 66 eyes with mild glaucoma (mean deviation ≥ -6 dB).

Results

Average (±SD) 24-2 mean deviation was -8.2 (±6.1) dB in eyes with glaucoma. The main predictive measures for glaucoma were temporal inferior rim height, nasal inferior pit volume, and temporal inferior pit depth. Lower values for these measures predicted higher risk of glaucoma. Sensitivity, specificity, and AUC for discriminating between healthy and glaucoma eyes were 81.5% (95% CI = 76.6-91.9%), 89.7% (95% CI = 78.7-94.2%), and 0.915 (95% CI = 0.882-0.948), respectively. Corresponding metrics for mild glaucoma were 84.8% (95% CI = 72.1%-95.5%), 85.8% (95% CI = 87.1%-97.4%), and 0.913 (95% CI = 0.867-0.958), respectively.

Conclusions

Novel macular shape biomarkers detect early glaucoma with clinically relevant performance. Such biomarkers do not depend on intraretinal segmentation accuracy and may be helpful in eyes with suboptimal macular segmentation.

Translational Relevance

Macular shape biomarkers provide valuable information for detection of early glaucoma and may provide additional information beyond thickness measurements.

Correlation of Ocular Biometric Parameters and Macular Ganglion Cell Layer in Normal Eyes

PURPOSE

To determine the association between ocular biometric parameters and macular ganglion cell layer (MGCL) thickness in normal eyes.

METHODS

This observational cohort study was conducted with 76 eyes of 76 healthy subjects. Keratometry, pachymetry, corneal volume, iridocorneal angle were measured with Sirius (CSO, Florence, Italy); axial length, anterior chamber depth, anterior chamber volume, corneal diameter were measured with IOL Master (Carl Zeiss Meditec, Dublin, California). For all participants, serial horizontal Spectralis Domain Optical Coherence Tomography (SD-OCT, Heidelberg Engineering, GmbH, Dossenheim, Germany) scans of the macula and peripapillary retinal nerve fiber layer (RNFL) analysis were obtained using SD-OCT. The relationship between numerical variables was given by Pearson correlation coefficient.

RESULTS

The mean age of the subjects was 36.3 ± 11.9 years (between 19 and 70 y). Fifty-one patients were female (67.1%) and twenty-five patients were male (32.9%). MGCL was found to be correlated with anterior chamber depth, anterior chamber volume, iridocorneal angle, axial length and white to white (p = .015 r = 0.594, p = .002 r = 0.365, p = .013 r = 0.299, p = .004 r = 0.335, p = .013 r = 0.289, respectively). In addition, MGCL was correlated positively with the mean global and superotemporal RNFL (p ≤ 0.005). However, neither central corneal thickness nor keratometry values were found to be correlated with MGCL.

CONCLUSION

The results of this study showed that MGCL thickness is affected by ocular biometric parameters. Therefore, these parameters should be taken into consideration when interpreting MGCL thickness measurements in the diagnosis of glaucoma.

Macular imaging with optical coherence tomography in glaucoma

With the advent of spectral-domain optical coherence tomography, imaging of the posterior segment of the eye can be carried out rapidly at multiple anatomical locations, including the optic nerve head, circumpapillary retinal nerve fiber layer, and macula. There is now ample evidence to support the role of spectral-domain optical coherence tomography imaging of the macula for detection of early glaucoma. Macular spectral-domain optical coherence tomography measurements demonstrate high reproducibility, and evidence on its utility for detection of glaucoma progression is accumulating. We present a comprehensive review of macular spectral-domain optical coherence tomography imaging emerging as an essential diagnostic tool in glaucoma.