Porciatti Vittorio, Bosse Brandon, Parekh Prashant K, Shif Olga A, Feuer William J, Ventura Lori M
McKnight Vision Research Center, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL.
J Glaucoma. 2014 Oct-Nov;23(8):494-500. doi: 10.1097/IJG.0b013e318285fd95.
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.
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.
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).
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.
先前的研究表明,高对比度、快速反转的图案刺激的开始会导致视网膜血管中的血流迅速增加,同时伴有稳态图形视网膜电图(PERG)信号的缓慢变化。我们检验了这样一个假设,即正常对照的适应性PERG变化与青光眼可疑患者和早期显性青光眼患者的变化不同。
受试者包括42名青光眼可疑患者(标准自动视野计平均缺损 -0.89±1.8 dB)、22名早期显性青光眼患者(平均缺损 -2.12±2.4 dB),视力≥20/20,以及来自先前一项研究的16名年龄匹配的正常对照。在4分钟内,以每秒16.28次的频率反转的光栅(1.6周/度,100%对比度)刺激下,每隔约15秒对PERG信号进行采样。连续PERG样本的幅度/相位值用非参数局部加权多项式回归平滑函数拟合,以获取初始值和最终值,并计算它们的差值(δ)以及拟合函数周围的残余标准差。与随机变异性相比,PERG适应性变化的幅度以变异系数百分比(CoV)的对数10计算 = 100×残余标准差r÷δ。通过对同一系列的所有样本求平均,也获得了总体平均PERG。
随着疾病严重程度的增加,总体平均PERG幅度[方差分析(ANOVA),P = 0.02]下降,但相位(ANOVA,P = 0.63)没有下降。PERG幅度的适应性变化[log10(CoV)]与疾病严重程度没有显著相关性(ANOVA,P = 0.27),但PERG相位的适应性变化[log10(CoV)]与疾病严重程度相关(ANOVA,P = 0.037;线性趋势,P = 0.011)。
稳态PERG信号随时间显示出缓慢的适应性变化,这种变化可以与随机变异性区分开来。PERG适应性变化与总体平均PERG(对应标准稳态PERG)的变化不同,因此代表了一种关于视网膜神经节细胞功能的新的生物学信息来源,这可能在青光眼和视神经疾病的研究中具有潜力。