PURPOSE: Previous studies have shown that the onset of high-contrast, fast reversing patterned stimuli induces rapid blood flow increase in retinal vessels in association with slow changes of the steady-state pattern electroretinogram (PERG) signal. We tested the hypothesis that adaptive PERG changes of normal controls differed from those of glaucoma suspects and patients with early manifest glaucoma. METHODS: Subjects were 42 glaucoma suspects (Standard Automated Perimetry-MD -0.89±1.8 dB), 22 early manifest glaucoma (MD -2.12±2.4 dB) with visual acuity of ≥20/20 and 16 age-matched normal controls from a previous study. The PERG signal was sampled every ~15 seconds over 4 minutes in response to gratings (1.6 cyc/degree, 100% contrast) reversing 16.28 times/s. Amplitude/phase values of successive PERG samples were fitted with a nonparametric locally weighted polynomial regression smoothing function to retrieve the initial and final values and calculate their difference (δ) and the residual SD around the fitted function. The magnitude of PERG adaptive change compared to random variability was calculated as log10 of percentage coefficient of variation (CoV)=100×residual SDr÷δ. Grand-average PERGs were also obtained by averaging all samples of the same series. RESULTS: The grand-average PERG amplitude [analysis of variance (ANOVA), P=0.02], but not phase (ANOVA, P=0.63), decreased with increasing severity of disease. Adaptive changes [log10 (CoV)] of PERG amplitude were not significantly associated with disease severity (ANOVA, P=0.27) but adaptive changes [log10 (CoV)] of PERG phase were (ANOVA, P=0.037; linear trend, P=0.011). CONCLUSIONS: The steady-state PERG signal displayed slow adaptive changes over time that could be isolated from random variability. PERG adaptive changes differed from those of grand-average PERGs (corresponding the standard steady-state PERG), thus representing a new source of biological information about retinal ganglion cell function that may have potential in the study of glaucoma and optic nerve diseases.
PURPOSE: Previous studies have shown that the onset of high-contrast, fast reversing patterned stimuli induces rapid blood flow increase in retinal vessels in association with slow changes of the steady-state pattern electroretinogram (PERG) signal. We tested the hypothesis that adaptive PERG changes of normal controls differed from those of glaucoma suspects and patients with early manifest glaucoma. METHODS: Subjects were 42 glaucoma suspects (Standard Automated Perimetry-MD -0.89±1.8 dB), 22 early manifest glaucoma (MD -2.12±2.4 dB) with visual acuity of ≥20/20 and 16 age-matched normal controls from a previous study. The PERG signal was sampled every ~15 seconds over 4 minutes in response to gratings (1.6 cyc/degree, 100% contrast) reversing 16.28 times/s. Amplitude/phase values of successive PERG samples were fitted with a nonparametric locally weighted polynomial regression smoothing function to retrieve the initial and final values and calculate their difference (δ) and the residual SD around the fitted function. The magnitude of PERG adaptive change compared to random variability was calculated as log10 of percentage coefficient of variation (CoV)=100×residual SDr÷δ. Grand-average PERGs were also obtained by averaging all samples of the same series. RESULTS: The grand-average PERG amplitude [analysis of variance (ANOVA), P=0.02], but not phase (ANOVA, P=0.63), decreased with increasing severity of disease. Adaptive changes [log10 (CoV)] of PERG amplitude were not significantly associated with disease severity (ANOVA, P=0.27) but adaptive changes [log10 (CoV)] of PERG phase were (ANOVA, P=0.037; linear trend, P=0.011). CONCLUSIONS: The steady-state PERG signal displayed slow adaptive changes over time that could be isolated from random variability. PERG adaptive changes differed from those of grand-average PERGs (corresponding the standard steady-state PERG), thus representing a new source of biological information about retinal ganglion cell function that may have potential in the study of glaucoma and optic nerve diseases.
Authors: Christopher Bowd; Gianmarco Vizzeri; Ali Tafreshi; Linda M Zangwill; Pamela A Sample; Robert N Weinreb Journal: Ophthalmology Date: 2009-01-22 Impact factor: 12.079
Authors: P Monsalve; S Ren; G Triolo; L Vazquez; A D Henderson; M Kostic; P Gordon; W J Feuer; V Porciatti Journal: Doc Ophthalmol Date: 2018-05-19 Impact factor: 2.379
Authors: Lívia M Brandão; Matthias Monhart; Andreas Schötzau; Anna A Ledolter; Anja M Palmowski-Wolfe Journal: J Ophthalmol Date: 2017-11-07 Impact factor: 1.909