TY - JOUR
T1 - Steady-state PERG adaptation
T2 - a conspicuous component of response variability with clinical significance
AU - Monsalve, P.
AU - Ren, S.
AU - Triolo, G.
AU - Vazquez, L.
AU - Henderson, A. D.
AU - Kostic, M.
AU - Gordon, P.
AU - Feuer, W. J.
AU - Porciatti, V.
N1 - Funding Information:
Funding NIH-NEI RO1 EY019077 (VP), NIH center grant P30-EY014801 (VP), unrestricted grant to Bascom Palmer Eye Institute from Research to Prevent Blindness, Inc., provided support in the form of salary for Vittorio Porciatti, Maja Kostic (RO1 EY019077, RPB) and infrastructure (P30-EY014801). The sponsor had no role in the design or conduct of the study.
Publisher Copyright:
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2018/6/1
Y1 - 2018/6/1
N2 - Purpose: To investigate within-test variability of the steady-state PERG (SS-PERG). Methods: SS-PERGs were recorded in response to black–white horizontal gratings (1.6 cycles/deg, 98% contrast, 15.63 reversals/s, LED display, 25 deg square field, 800 cd/sqm mean luminance) using skin electrodes. PERG and noise (± reference) signals were averaged over 1024 epochs (~ 2.2 min) and Fourier analyzed to retrieve SS-PERG amplitude and phase. SS-PERGs were split into 16 partial averages (samples) of 64 epochs each, and corresponding amplitudes and phases combined in polar coordinates to assess their dispersion (within-test variability). To assess time-dependent variability, samples were clustered in four successive time segments of ~ 33 s each. Amplitude adaptation was defined as amplitude difference between initial and final clusters, and PERG phase adaptation as the corresponding phase difference. To determine the dynamic range of SS-PERG adaptation, recording was performed in normal controls of different age (n = 32) and patients with different severity of optic nerve dysfunction (early manifest glaucoma, EMG, n = 7; non-arteritic ischemic optic neuropathy, NAION, n = 5). Results: Amplitude adaptation was largest in younger controls (amplitude adaptation ÷ noise, SNR = 9.5, 95% CI 13.1, 5.9) and progressively decreased with increasing age (older subjects, SNR = 5.5, 95% CI 9.2, 1.8) and presence of disease (EMG: SNR = 2.4, 95% CI 3.5, 1.4; NAION: SNR = 1.9, 95% CI 6.5,-2.2). In 11 young subjects, amplitude adaptation was repeatable (test–retest in two sessions a week apart; intraclass correlation coefficient = 0.59). Phase adaptation was not significantly different from zero in all groups. Conclusions: SS-PERG adaptation accounts for a sizeable portion of the within-test variability. As it has robust SNR, sufficient test–retest variability, and is altered in disease, it may have physiological and clinical significance. This study suggests that SS-PERG protocols should include adaptation in addition to SS-PERG amplitude and phase/latency.
AB - Purpose: To investigate within-test variability of the steady-state PERG (SS-PERG). Methods: SS-PERGs were recorded in response to black–white horizontal gratings (1.6 cycles/deg, 98% contrast, 15.63 reversals/s, LED display, 25 deg square field, 800 cd/sqm mean luminance) using skin electrodes. PERG and noise (± reference) signals were averaged over 1024 epochs (~ 2.2 min) and Fourier analyzed to retrieve SS-PERG amplitude and phase. SS-PERGs were split into 16 partial averages (samples) of 64 epochs each, and corresponding amplitudes and phases combined in polar coordinates to assess their dispersion (within-test variability). To assess time-dependent variability, samples were clustered in four successive time segments of ~ 33 s each. Amplitude adaptation was defined as amplitude difference between initial and final clusters, and PERG phase adaptation as the corresponding phase difference. To determine the dynamic range of SS-PERG adaptation, recording was performed in normal controls of different age (n = 32) and patients with different severity of optic nerve dysfunction (early manifest glaucoma, EMG, n = 7; non-arteritic ischemic optic neuropathy, NAION, n = 5). Results: Amplitude adaptation was largest in younger controls (amplitude adaptation ÷ noise, SNR = 9.5, 95% CI 13.1, 5.9) and progressively decreased with increasing age (older subjects, SNR = 5.5, 95% CI 9.2, 1.8) and presence of disease (EMG: SNR = 2.4, 95% CI 3.5, 1.4; NAION: SNR = 1.9, 95% CI 6.5,-2.2). In 11 young subjects, amplitude adaptation was repeatable (test–retest in two sessions a week apart; intraclass correlation coefficient = 0.59). Phase adaptation was not significantly different from zero in all groups. Conclusions: SS-PERG adaptation accounts for a sizeable portion of the within-test variability. As it has robust SNR, sufficient test–retest variability, and is altered in disease, it may have physiological and clinical significance. This study suggests that SS-PERG protocols should include adaptation in addition to SS-PERG amplitude and phase/latency.
KW - Glaucoma
KW - Neural adaptation
KW - Non-arteritic ischemic optic neuropathy
KW - Pattern electroretinogram
KW - Variability
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U2 - 10.1007/s10633-018-9633-2
DO - 10.1007/s10633-018-9633-2
M3 - Article
C2 - 29779071
AN - SCOPUS:85047135058
SN - 0012-4486
VL - 136
SP - 157
EP - 164
JO - Documenta Ophthalmologica
JF - Documenta Ophthalmologica
IS - 3
ER -