Posterior Pole Asymmetry Analysis as a Diagnostic Tool in Glaucoma Suspects: An Electrophysiological Approach.

Purpose: Spectral domain optical coherence tomography (SD-OCT) with posterior pole asymmetry analysis (PPAA) provides a mapping of posterior pole retinal thickness with asymmetry analysis between hemispheres of each eye. We investigated whether these structural abnormalities were correlated with functional retinal ganglion cell (RGC) loss, quantified by steady state pattern electroretinogram (ssPERG), in glaucoma suspects (GS). Methods: Twenty GS (34 eyes) were enrolled in a prospective study at the Manhattan Eye, Ear, and Throat Hospital. All subjects underwent ophthalmological examination, including Humphrey visual field, Spectralis Glaucoma Module Premium Edition (GMPE) SD-OCT PPAA, and ssPERG testing. The ability of ssPERG parameters (Magnitude [Mag, µv], MagnitudeD [MagD, µv], and MagD/Mag ratio) to predict PPAA thickness (total, superior, and inferior thickness, [µm]) was tested via adjusted multivariate linear regression analysis. Results: Mag explained 8% of variance in total PPAA change (F(1,29)=6.33, B=6.86, 95% CI: 1.29-12.44, p=0.018), 8% in superior PPAA change (F(1,29)=5.57, B=6.92, 95% CI: 0.92-12.92, p=0.025), and 7.1% in inferior PPAA change (F(1,29)=5.83, B=6.80, 95% CI: 1.04-12.56, p=0.022). Similarly, MagD explained 9.7% of variance in total PPAA change (F(1,29)=8.09, B=6.47, 95% CI: 1.82-11.13, p=0.008), 10% in superior PPAA change (F(1,29)=7.33, B=6.63, 95% CI: 1.62-11.63, p=0.011), and 8.5% in inferior PPAA change (F(1,29)=7.25, B=6.36, 95% CI: 1.53-11.18, p=0.012). MagD/Mag ratio and PPAA were not significantly associated. Conclusion: To the best of our knowledge, this is the first study demonstrating a positive relationship between RGC dysfunction and retinal thickness changes between the superior and inferior hemispheres. The detection of asymmetrical structural loss, combined with functional RGC assessment using ssPERG, may be an informative tool for early glaucoma diagnosis.

Structure-function models for estimating retinal ganglion cell count using steady-state pattern electroretinography and optical coherence tomography in glaucoma suspects and preperimetric glaucoma: an electrophysiological pilot study.

PURPOSE: To derive and validate structure-function models for estimating retinal ganglion cell (RGC) count using optical coherence tomography (OCT) and steady-state pattern electroretinography (ssPERG) parameters in glaucoma suspects (GS) and preperimetric glaucoma (PPG). METHODS: In this prospective cross-sectional study, 25 subjects (50 eyes) were recruited at the Manhattan Eye, Ear, and Throat Hospital. Subjects underwent comprehensive eye examinations, OCT, standard automated perimetry (SAP), and ssPERG testing. Eyes were divided into three groups based on the Global Glaucoma Staging System: healthy (N = 30), GS (N = 10), and PPG (N = 10) eyes. The combined structure-function index (CSFI), which estimates retinal ganglion cell count (eRGCCSFI) from SAP and OCT parameters, was calculated in each study subject. Two prediction formulas were derived using a generalized linear mixed model (GLMM) to predict eRGCCSFI from ssPERG parameters, age, and average retinal nerve fiber layer thickness (ARNFLT) in 30 eyes selected at random (training group). GLMM predicted values were cross-validated with the remaining 20 eyes (validation group). RESULTS: The ARNFLT, ssPERG parameters magnitude (Mag) and magnitudeD (MagD), and eRGCCSFI were significantly different among study groups (ANOVA p ≤ 0.001). Pearson correlations demonstrated significant associations among ARNFLT, ssPERG parameters, and eRGCCSFI (r2 ≥ 0.31, p < 0.001). Two GLMMs predicted eRGCCSFI from Mag (eRGCMag) and MagD (eRGCMagD), respectively, with significant equations (F(3,18), F(3,19) ≥ 58.37, R2 = 0.90, p < 0.001). eRGCMag and eRGCMagD in the validation group (R2 = 0.89) correlated with eRGCCSFI similarly to the training group. Multivariate pairwise comparisons revealed that eRGCMag and eRGCMagD distinguished between healthy, GS, and PPG eyes (p ≤ 0.035), whereas independent Mag, MagD, and ARNFLT measures did not distinguish between GS and PPG eyes. CONCLUSION: This pilot study offers the first combined structure-function models for estimating RGC count using ssPERG parameters. RGC counts estimated with these models were generalizable, strongly associated with CSFI estimates, and performed better than individual ssPERG and OCT measures in distinguishing healthy, GS, and PPG eyes.

Associations between steady-state pattern electroretinography and estimated retinal ganglion cell count in glaucoma suspects.

PURPOSE: To estimate retinal ganglion cell (RGC) count in glaucoma suspects (GS) and ascertain its relationships with steady-state pattern electroretinography (ssPERG) parameters. METHODS: In this prospective cross-sectional study, 22 subjects (44 eyes) were recruited at the Manhattan Eye, Ear, and Throat Hospital. Subjects underwent complete eye examinations, optical coherence tomography, standard automated perimetry, and ssPERG testing. Eyes were divided into two groups based upon clinical data: healthy subjects and GS. RGC count was estimated using the combined structure-function index. RESULTS: Estimated RGC count, average retinal nerve fiber layer thickness (ARNFLT), and average ganglion cell layer and inner plexiform layer thickness (GCIPLT) were reduced in GS eyes (p ≤ 0.001 for all parameters). Pearson correlations revealed that ssPERG magnitude and magnitudeD correlated with ARNFLT (r ≥ 0.53, p < 0.001), GCIPLT (r > 0.38, p < 0.011), and estimated RGC count (r > 0.46, p < 0.002). Six mediation analyses revealed that estimated RGC count mediated the relationships among ssPERG parameters, ARNFLT, and GCIPLT. CONCLUSION: Steady-state PERG parameters demonstrated linear correlations with estimated RGC count. The associations among ssPERG parameters and structural measures were mediated by estimated RGC count.

Pattern Electroretinogram Parameters Are Associated with Optic Nerve Morphology in Preperimetric Glaucoma after Adjusting for Disc Area.

PURPOSE: We examined the relationships between pattern electroretinogram and optical coherence tomography derived optic nerve head measurements, after controlling for disc area. METHODS: Thirty-two eyes from 20 subjects with preperimetric glaucoma underwent pattern electroretinogram and optical coherence tomography. Pattern electroretinogram parameters (Magnitude, MagnitudeD, and MagnitudeD/Magnitude ratio) and optic nerve head measurements (rim area, average cup to disc ratio, vertical cup to disc ratio, cup volume, retinal nerve fiber layer thickness sectors, and Bruch's membrane opening-minimum rim width thickness sectors) were analyzed after controlling for disc area. RESULTS: Magnitude and MagnitudeD were significantly associated with rim area (r ≥ 0.503, p ≤ 0.004). All pattern electroretinogram parameters significantly correlated with Bruch's membrane opening-minimum rim width sectors-temporal superior and nasal inferior (r = 0.400, p=0.039)-and retinal nerve fiber layer sectors-superior, nasal superior, and inferior (r ≥ 0.428, p ≤ 0.026). Magnitude and MagnitudeD explained an additional 26.8% and 25.2% of variance in rim area (B = 0.174 (95% CI: 0.065, 0.283), p=0.003, and B = 0.160 (95% CI: 0.056, 0.265), p=0.004), respectively. MagnitudeD and MagnitudeD/Magnitude ratio explained an additional 13.4% and 12.8% of the variance in Bruch's membrane opening-minimum rim width global (B = 38.921 [95% CI: 3.872, 73.970], p=0.031, and B = 129.024 (95% CI: 9.589, 248.460), p=0.035), respectively. All Bruch's membrane opening-minimum rim width sectors and retinal nerve fiber layer sectors (nasal superior, nasal inferior, and inferior) were significantly correlated with rim area (r ≥ 0.389, p ≤ 0.045). CONCLUSION: PERG abnormalities can predict rim area loss in preperimetric glaucoma after controlling for disc area. We recommend controlling for disc area to increase diagnostic accuracy in early glaucoma.