Novel Structure–Function Models for Estimating Retinal Ganglion Cell Count Using Pattern Electroretinography in Glaucoma Suspects

<b>Background/Objectives</b>: The early detection of retinal ganglion cell (RGC) dysfunction is critical for timely intervention in glaucoma suspects (GSs). The combined structure–function index (CSFI), which uses visual field and optical coherence tomography (OCT) data to estimate RGC c...

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Main Authors: Andrew Tirsi, Isabella Tello, Timothy Foster, Rushil Kumbhani, Nicholas Leung, Samuel Potash, Derek Orshan, Celso Tello
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Diagnostics
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Online Access:https://www.mdpi.com/2075-4418/15/14/1756
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author Andrew Tirsi
Isabella Tello
Timothy Foster
Rushil Kumbhani
Nicholas Leung
Samuel Potash
Derek Orshan
Celso Tello
author_facet Andrew Tirsi
Isabella Tello
Timothy Foster
Rushil Kumbhani
Nicholas Leung
Samuel Potash
Derek Orshan
Celso Tello
author_sort Andrew Tirsi
collection DOAJ
description <b>Background/Objectives</b>: The early detection of retinal ganglion cell (RGC) dysfunction is critical for timely intervention in glaucoma suspects (GSs). The combined structure–function index (CSFI), which uses visual field and optical coherence tomography (OCT) data to estimate RGC counts, may be of limited utility in GSs. This study evaluates whether steady-state pattern electroretinogram (ssPERG)-derived estimates better predict early structural changes in GSs. <b>Methods</b>: Fifty eyes from 25 glaucoma suspects underwent ssPERG and spectral-domain OCT. Estimated RGC counts (eRGCC) were calculated using three parameters: ssPERG-Magnitude (eRGCC<sub>Mag</sub>), ssPERG-MagnitudeD (eRGCC<sub>MagD</sub>), and CSFI (eRGCC<sub>CSFI</sub>). Linear regression and multivariable models were used to assess each model’s ability to predict the average retinal nerve fiber layer thickness (AvRNFLT), average ganglion cell layer–inner plexiform layer thickness (AvGCL-IPLT), and rim area. <b>Results</b>: eRGCC<sub>Mag</sub> and eRGCC<sub>MagD</sub> were significantly correlated with eRGCC<sub>CSFI</sub>. Both PERG-derived models outperformed eRGCC<sub>CSFI</sub> in predicting AvRNFLT and AvGCL-IPLT, with eRGCC<sub>MagD</sub> showing the strongest association with AvGCL-IPLT. Conversely, the rim area was best predicted by eRGCC<sub>Mag</sub> and eRGCC<sub>CSFI</sub>. These findings support a linear relationship between ssPERG parameters and early RGC structural changes, while the logarithmic nature of visual field loss may limit eRGCC<sub>CSFI</sub>’s predictive accuracy in GSs. <b>Conclusions</b>: ssPERG-derived estimates, particularly eRGCC<sub>MagD</sub>, better predict early structural changes in GSs than eRGCC<sub>CSFI</sub>. eRGCC<sub>MagD</sub>’s superior performance in predicting GCL-IPLT highlights its potential utility as an early biomarker of glaucomatous damage. ssPERG-based models offer a simpler and more sensitive tool for early glaucoma risk stratification, and may provide a clinical benchmark for tracking recoverable RGC dysfunction and treatment response.
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spelling doaj-art-dff279c0efcb4d0fa94a226986e23bf92025-08-20T03:08:01ZengMDPI AGDiagnostics2075-44182025-07-011514175610.3390/diagnostics15141756Novel Structure–Function Models for Estimating Retinal Ganglion Cell Count Using Pattern Electroretinography in Glaucoma SuspectsAndrew Tirsi0Isabella Tello1Timothy Foster2Rushil Kumbhani3Nicholas Leung4Samuel Potash5Derek Orshan6Celso Tello7Department of Ophthalmology, Manhattan Eye, Ear, and Throat Hospital, Northwell Health, 210 E 64th St., 8th Floor, New York, NY 10065, USADepartment of Ophthalmology, Manhattan Eye, Ear, and Throat Hospital, Northwell Health, 210 E 64th St., 8th Floor, New York, NY 10065, USADonald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USADonald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USADonald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USAAlbert Einstein College of Medicine, Bronx, NY 10461, USADepartment of Ophthalmology, Larkin Community Hospital, Miami, FL 33431, USADepartment of Ophthalmology, Manhattan Eye, Ear, and Throat Hospital, Northwell Health, 210 E 64th St., 8th Floor, New York, NY 10065, USA<b>Background/Objectives</b>: The early detection of retinal ganglion cell (RGC) dysfunction is critical for timely intervention in glaucoma suspects (GSs). The combined structure–function index (CSFI), which uses visual field and optical coherence tomography (OCT) data to estimate RGC counts, may be of limited utility in GSs. This study evaluates whether steady-state pattern electroretinogram (ssPERG)-derived estimates better predict early structural changes in GSs. <b>Methods</b>: Fifty eyes from 25 glaucoma suspects underwent ssPERG and spectral-domain OCT. Estimated RGC counts (eRGCC) were calculated using three parameters: ssPERG-Magnitude (eRGCC<sub>Mag</sub>), ssPERG-MagnitudeD (eRGCC<sub>MagD</sub>), and CSFI (eRGCC<sub>CSFI</sub>). Linear regression and multivariable models were used to assess each model’s ability to predict the average retinal nerve fiber layer thickness (AvRNFLT), average ganglion cell layer–inner plexiform layer thickness (AvGCL-IPLT), and rim area. <b>Results</b>: eRGCC<sub>Mag</sub> and eRGCC<sub>MagD</sub> were significantly correlated with eRGCC<sub>CSFI</sub>. Both PERG-derived models outperformed eRGCC<sub>CSFI</sub> in predicting AvRNFLT and AvGCL-IPLT, with eRGCC<sub>MagD</sub> showing the strongest association with AvGCL-IPLT. Conversely, the rim area was best predicted by eRGCC<sub>Mag</sub> and eRGCC<sub>CSFI</sub>. These findings support a linear relationship between ssPERG parameters and early RGC structural changes, while the logarithmic nature of visual field loss may limit eRGCC<sub>CSFI</sub>’s predictive accuracy in GSs. <b>Conclusions</b>: ssPERG-derived estimates, particularly eRGCC<sub>MagD</sub>, better predict early structural changes in GSs than eRGCC<sub>CSFI</sub>. eRGCC<sub>MagD</sub>’s superior performance in predicting GCL-IPLT highlights its potential utility as an early biomarker of glaucomatous damage. ssPERG-based models offer a simpler and more sensitive tool for early glaucoma risk stratification, and may provide a clinical benchmark for tracking recoverable RGC dysfunction and treatment response.https://www.mdpi.com/2075-4418/15/14/1756retinal ganglion cellspattern electroretinogramglaucoma suspectsoptical coherence tomography
spellingShingle Andrew Tirsi
Isabella Tello
Timothy Foster
Rushil Kumbhani
Nicholas Leung
Samuel Potash
Derek Orshan
Celso Tello
Novel Structure–Function Models for Estimating Retinal Ganglion Cell Count Using Pattern Electroretinography in Glaucoma Suspects
Diagnostics
retinal ganglion cells
pattern electroretinogram
glaucoma suspects
optical coherence tomography
title Novel Structure–Function Models for Estimating Retinal Ganglion Cell Count Using Pattern Electroretinography in Glaucoma Suspects
title_full Novel Structure–Function Models for Estimating Retinal Ganglion Cell Count Using Pattern Electroretinography in Glaucoma Suspects
title_fullStr Novel Structure–Function Models for Estimating Retinal Ganglion Cell Count Using Pattern Electroretinography in Glaucoma Suspects
title_full_unstemmed Novel Structure–Function Models for Estimating Retinal Ganglion Cell Count Using Pattern Electroretinography in Glaucoma Suspects
title_short Novel Structure–Function Models for Estimating Retinal Ganglion Cell Count Using Pattern Electroretinography in Glaucoma Suspects
title_sort novel structure function models for estimating retinal ganglion cell count using pattern electroretinography in glaucoma suspects
topic retinal ganglion cells
pattern electroretinogram
glaucoma suspects
optical coherence tomography
url https://www.mdpi.com/2075-4418/15/14/1756
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