Paul H Artes1, Balwantray C Chauhan. 1. Ophthalmology and Visual Sciences, Dalhousie University, Halifax, Nova Scotia, Canada. paul@dal.ca
Abstract
PURPOSE: To describe a methodology for establishing signal-to-noise ratios (SNRs) for different perimetric techniques, and to compare SNRs of frequency-doubling technology (FDT2) perimetry and standard automated perimetry (SAP). METHODS: Fifteen patients with open-angle glaucoma (median MD, -2.6 dB, range +0.2 to -16.1 dB) were tested six times with FDT2 and SAP (SITA Standard program 24-2) within a 4-week period. Signals were estimated from the average superior-inferior difference between the mean deviation (MD) values in five mirror-pair sectors of the Glaucoma Hemifield Test, and noise from the dispersion of these differences over the six repeated tests. SNRs of FDT2 and SAP were compared by mixed-effects modeling. RESULTS: There was moderate correlation between the signals of FDT2 and SAP (r(2) = 0.68, P < 0.001), but no correlation of noise (r(2) = 0.01, P = 0.16). Although both signal as well as noise estimates were higher with FDT2 compared with SAP, 60% to 70% of sector pairs showed higher SNRs with FDT2. The SNRs of FDT2 were between 20% and 40% higher than those of SAP (P = 0.01). There were no meaningful differences between parametric and nonparametric estimates of signal, noise, or SNR. CONCLUSION: The higher SNRs of FDT2 suggest that this technique is at least as efficient as SAP at detecting localized visual field losses. Signal/noise analyses may provide a useful approach for comparing visual field tests independent of their decibel scales and may provide an initial indication of sensitivity to visual field change over time.
PURPOSE: To describe a methodology for establishing signal-to-noise ratios (SNRs) for different perimetric techniques, and to compare SNRs of frequency-doubling technology (FDT2) perimetry and standard automated perimetry (SAP). METHODS: Fifteen patients with open-angle glaucoma (median MD, -2.6 dB, range +0.2 to -16.1 dB) were tested six times with FDT2 and SAP (SITA Standard program 24-2) within a 4-week period. Signals were estimated from the average superior-inferior difference between the mean deviation (MD) values in five mirror-pair sectors of the Glaucoma Hemifield Test, and noise from the dispersion of these differences over the six repeated tests. SNRs of FDT2 and SAP were compared by mixed-effects modeling. RESULTS: There was moderate correlation between the signals of FDT2 and SAP (r(2) = 0.68, P < 0.001), but no correlation of noise (r(2) = 0.01, P = 0.16). Although both signal as well as noise estimates were higher with FDT2 compared with SAP, 60% to 70% of sector pairs showed higher SNRs with FDT2. The SNRs of FDT2 were between 20% and 40% higher than those of SAP (P = 0.01). There were no meaningful differences between parametric and nonparametric estimates of signal, noise, or SNR. CONCLUSION: The higher SNRs of FDT2 suggest that this technique is at least as efficient as SAP at detecting localized visual field losses. Signal/noise analyses may provide a useful approach for comparing visual field tests independent of their decibel scales and may provide an initial indication of sensitivity to visual field change over time.