Objective assessment of visual acuity: a refined model for analyzing the sweep VEP.

Abstract

The aim of this study was to develop a simple and reliable method for the objective assessment of visual acuity by optimizing the stimulus used in commercially available systems and by improving the methods of evaluation using a nonlinear function, the modified Ricker model. Subjective visual acuity in the normal subjects was measured with Snellen targets, best-corrected, and in some cases also uncorrected and with plus lenses (+ 1D, + 2D, + 3D). In patients, subjective visual acuity was measured best-corrected using the Freiburg Visual Acuity Test. Sweep VEP recordings to 11 spatial frequencies, with check sizes in logarithmically equidistant steps (0.6, 0.9, 1.4, 2.1, 3.3, 4.9, 7.3, 10.4, 18.2, 24.4, and 36.5cpd), were obtained from 56 healthy subjects aged between 17 and 69years (mean 42.5 ± 15.3SD years) and 20 patients with diseases of the lens (n = 6), retina (n = 8) or optic nerve (n = 6). The results were fit by a multiple linear regression (2nd-order polynomial) or a nonlinear regression (modified Ricker model) and parameters compared (limiting spatial frequency (sflimiting) and the spatial frequency of the vertex (sfvertex) of the parabola for the 2nd-order polynomial fitting, and the maximal spatial frequency (sfmax), and the spatial frequency where the amplitude is 2dB higher than the level of noise (sfthreshold) for the modified Ricker model. Recording with 11 spatial frequencies allows a more accurate determination of acuities above 1.0 logMAR. Tuning curves fitted to the results show that compared to the normal 2nd-order polynomial analysis, the modified Ricker model is able to describe closely the amplitudes of the sweep VEP in relation to the spatial frequencies of the presented checkerboards. In patients with a visual acuity better than about 0.5 (decimal), the predicted acuities based on the different parameters show a good match of the predicted visual acuities based on the models established in healthy volunteers to the subjective visual acuities. However, for lower visual acuities, both models tend to overestimate the visual acuity (up to ~ 0.4 logMAR), especially in patients suffering from AMD. Both models, the 2nd-order polynomial and the modified Ricker model performed equally well in the prediction of the visual acuity based on the amplitudes recorded using the sweep VEP. However, the modified Ricker model does not require the exclusion of data points from the fit, as necessary when fitting the 2nd-order polynomial model making it more reliable and robust against outliers, and, in addition, provides a measure for the noise of the recorded results.