January 2008
Volume 49, Issue 1
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Visual Neuroscience  |   January 2008
Real-Time Rapid Acuity Assessment Using VEPs: Development and Validation of the Step VEP Technique
Author Affiliations
  • Alison M. Mackay
    From the Departments of Clinical Physics and
    Department of Clinical Physics, University of Glasgow, Glasgow, Scotland, United Kingdom; and the
  • Michael S. Bradnam
    From the Departments of Clinical Physics and
    Department of Clinical Physics, University of Glasgow, Glasgow, Scotland, United Kingdom; and the
  • Ruth Hamilton
    From the Departments of Clinical Physics and
    Department of Clinical Physics, University of Glasgow, Glasgow, Scotland, United Kingdom; and the
  • Alex T. Elliot
    Department of Clinical Physics, University of Glasgow, Glasgow, Scotland, United Kingdom; and the
  • Gordon N. Dutton
    Ophthalmology, Royal Hospital for Sick Children and The Queen Mother’s Hospital, Glasgow, Scotland, United Kingdom; the
    Department of Vision Science, Glasgow Caledonian University, Glasgow, Scotland, United Kingdom.
Investigative Ophthalmology & Visual Science January 2008, Vol.49, 438-441. doi:10.1167/iovs.06-0944
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      Alison M. Mackay, Michael S. Bradnam, Ruth Hamilton, Alex T. Elliot, Gordon N. Dutton; Real-Time Rapid Acuity Assessment Using VEPs: Development and Validation of the Step VEP Technique. Invest. Ophthalmol. Vis. Sci. 2008;49(1):438-441. doi: 10.1167/iovs.06-0944.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

purpose. To develop a reference range of visual acuities corresponding to thresholds found using the step VEP method of rapid, objective visual acuity assessment by using steady state (ss)VEPs in normal adults.

methods. Sixteen normal adults had visual acuity assessed five times with both the step VEP and with Glasgow Acuity Cards (GAC). Subjects were tested once without filters and with four different levels of optical filtering provided by Bangerter neutral-density filters. Acuity outcomes were compared by linear regression and Bland-Altman analysis.

results. Step VEP and GAC acuities correlated highly (r 2 = 0.60, P = 0.000). GAC scores were predicted with the equation: acuityGAC = (0.9 × acuitystep VEP) − 0.37. Step VEP acuity was 0.46 (95% CI: −0.13 to 1.06) logMAR units greater (poorer) than GAC acuities in these normal subjects. The disparity between test results did not vary with visual acuity.

conclusions. The step VEP provides a rapid, objective means of estimating visual acuity that can be related to acuity derived from a commonly used letter test.

Visual acuity is measured clinically using several subjective techniques such as letter charts 1 2 3 4 and preferential-looking tasks. 5 6 7 Immaturity, learning difficulties, motor, and intellectual impairment may result in some patients being unable to perform these assessments. VEPs provide an alternative and objective measurement of visual acuity in such patients. This method is also useful in patients who have suspected functional visual impairment. Recording VEPs to patterns of varying spatial frequency requires only that the patient focus on the stimulus. 8  
VEP acuity is usually measured with either serial transient VEP recordings or the sweep VEP. Because it was found that VEP amplitude was related to acuity and stimulus size, 9 transient VEPs have been recorded to varying spatial frequencies and acuity expressed as the highest spatial frequency (smallest pattern size) to which a reproducible response is recorded 10 11 12 13 or as the spatial frequency at which a regression line fitted to VEP amplitudes of increasing spatial frequencies reaches some predetermined noise floor. 14 15 16 The sweep VEP was developed to provide a rapid assessment of acuity 17 18 19 by repeatedly sweeping through many spatial frequencies. After several sweeps, the average response is analyzed for statistical significance and the threshold calculated by extrapolation, if and when a sufficient number of significant responses are found. This system has been evaluated in normal and preterm infants 20 21 22 and in a range of other clinical groups 23 24 25 26 27 28 29 and is possibly the most commonly used VEP acuity technique. 
Transient VEP acuity procedures inevitably take longer than sweep VEP acuity because of the slower presentation rate and the relative inefficiency of signal detection acquired by averaging and judgment of signal reproducibility by eye. 30 However, some aspects of transient VEP protocols have potential benefits: if a patient loses interest part way through testing, the results obtained, although not a threshold, can be interpreted as a minimum level of vision: “acuity is equal to or better than… .” 12 VEP size and clarity inform the decision about the next stimulus size and thus minimize the time spent viewing stimuli too far above or below threshold. Presenting fewer stimuli reduces test time and presenting the fewest possible subthreshold stimuli helps maintain the patient’s attention. These factors governed the design of our steady state (ss)VEP acuity assessment technique, the step VEP, which combines the rapidity of the sweep VEP with the ability to seek thresholds based on previous results as in transient VEP assessments. 
The purpose of this study was to compare step VEP acuity with standardized letter acuity in a group of normal adults, each with fully corrected vision and at various levels of artificially degraded vision, to develop a reference range of visual acuity values corresponding to step VEP thresholds. 
Methods
Step VEP
A system that separately acquires and analyses ssVEPs has been described previously. 31 In the present study, the system was further developed so that signal processing was performed in real time, and the results obtained were used to control stimulus presentation. Black and white reversing checkerboards at 100% contrast and 7.78 Hz were used to elicit ssVEPs, as preferred by international standards for clinical recording 32 and that tend to produce the largest amplitude responses. 33 Mean luminance was 60 cd/m2. Twenty-seven check sizes were available in 0.1-logMAR increments between 680 and 1.8 minutes (size refers to element diagonal). Three occipital EEG channels were recorded: Oz–Fz 32 ;LO-Fz; RO-Fz with ground at a mastoid. A fourth virtual channel of a one-dimensional Laplacian analysis of the three occipital electrodes was also recorded, which detects ssVEPs to some check sizes more quickly. 34 35 Signals were amplified and filtered between 1 and 100 Hz. 
Two simultaneous real-time analyses were performed on each raw data segment: Fourier analysis followed by T2 CIRC statistic 36 and Fourier analysis of cumulatively averaged segments followed by SNR calculation in the frequency domain. 37 These analyses are complementary in the rapid assessment of thresholds. 38 By using relative signal measures, threshold dependence on noise level is reduced. 37 Because detections are accepted from any one of eight channels (four channels × two analyses), a Bonferroni correction of 8 was applied to each channel (P = 0.005), to avoid reduced specificity and maintain an overall significance level for response detection of P = 0.04. 39 Two-second data segments were found to provide the best compromise between sensitivity, specificity, and test duration. 40  
A successive approximation algorithm was used to govern stimuli presentation. Initially, check size was reduced in large steps (0.4 logMAR). After the first detection failure (27 seconds of stimulation without a response 40 ), check size was increased in 0.2-logMAR steps; after the next result, check size was changed using a 0.1-logMAR step. A threshold is declared when responses to three consecutively reducing check sizes are scored: detection, detection, no detection. Threshold is converted to logMAR units by taking the logarithm of the check diagonal. The step VEP is fully automated, but allows the user to suspend the analysis when the subject’s fixation is poor. 
A dual graphics card allows stimuli to be presented on one monitor (patient screen) and analysis of information on the other (user screen). Graphics were developed to allow the user to monitor information on stimulation, analysis, and the complete assessment. The user graphics and a typical stimulus of the step VEP system are shown in Figure 1
Subjects
Sixteen normal adult volunteers aged 23–41 years (mean, 30), had the procedure explained to them in full and agreed to take part. Local ethics committee approval was obtained, and the research adhered to the tenets of the Declaration of Helsinki. All subjects had normal vision. 
Procedure
Each subject had visual acuity assessed five times, both with step VEP and with Glasgow Acuity Cards (GAC), once with normal refractive correction if required and four further times wearing four different levels of optical filtering provided by Bangerter neutral-density filters. This process resulted in five pairs of acuity measurements in each subject, five measures with step VEP and five with GAC. All test results were converted to common logMAR units for comparison, and linear regression was performed to quantify the association between step VEP acuity and GAC acuity. Bland-Altman analysis was performed to quantify the agreement between acuities. 41  
Results
Acuity measured by step VEP and by GAC correlated highly (r 2 = 0.60, P = 0.000; Fig. 2 ). Linear regression analysis showed that no individual subject significantly influenced results and therefore repeated measures could remain in the data set. 
Step VEP acuity was 0.46 logMAR units greater (poorer) than GAC acuity on average (95% CI: −0.13 to 1.06 logMAR; Bland-Altman plots, Fig. 3 ). This confidence interval of 1.2 logMAR units is larger than a clinically significant change (0.2 logMAR unit), 42 and so the two tests cannot be used interchangeably. Rather, it would be appropriate to express step VEP acuity as a range of possible subjective acuities, as represented by the 95% prediction intervals around the linear regression line (Fig. 2) , or to use the regression equation acuityGAC = (0.9 × acuitystep VEP) − 0.37, to define a median estimate with 0.6 logMAR unit error each way. 
Discussion
The step VEP system represents a development of previous real time ssVEP systems. Real time analysis of steady state VEPs has been used for acuity measures 17 18 43 and a real-time VEP system in which amplitude is employed to control subsequent stimulus parameters was first used to measure the absorption spectrum. 44  
In this study, the step VEP underestimated psychophysical acuity (GAC) by ∼0.46 logMAR units across all acuity levels. This 0.46 log unit offset may occur for several reasons. First, the skull attenuates all responses uniformly before they are recorded by the scalp electrode, which means that small responses to near-threshold stimuli are very difficult to discern from the background EEG. Second, acuity targets differ substantially: GAC letter charts versus flickering checks. Other studies comparing similar pairs of acuity targets have found similar discrepancies: Sweep VEP underestimated Bailey-Lovie letter acuity by 0.25 log units in a group of normal adults, 19 underestimated Snellen acuity by 0.5 log units in defocused adults, 33 and underestimated preferential-looking acuity by ∼0.37 log units in children with reasonably good acuity. 28 Similarly, tVEPs underestimated behavioral acuity (Keeler or Cardiff cards) by 0.76 logMAR in multiply handicapped children. 12 However, sweep VEP in children with cortical visual impairment gave better acuities than Teller cards by ∼0.3 log units. 24 This finding is in keeping with other studies that show sweep VEPs to provide equal or better acuity estimates than behavioral methods for those with very poor vision. 19 26 27 28 29 33 In contrast, we found no acuity dependence in the relationship between the step VEP and GAC acuity. In experiments where the same acuity target is used for electrophysiological and psychophysical comparisons, VEP thresholds are similar to 45 46 or underestimate psychophysical thresholds by ∼0.08, 33 0.15, 18 or 0.4 47 log units (contrast thresholds), generally smaller discrepancies than those seen for different acuity targets. Third, the oblique effect caused by using a checkerboard whose fundamental frequencies are obliquely oriented may also reduce the measured VEP acuity. 48 Finally, pattern reversal VEP amplitudes drop at midspatial frequencies, 49 and the step VEP may miss VEPs in the notch, although VEPs may be present in response to smaller check sizes. However, the symmetry of the distribution of points in Figure 2suggests this is not the case. Pattern-reversal VEPs are known to have larger amplitudes than pattern-onset VEPs in those with poor vision, 50 and the notch may be irrelevant, as it occurs below the threshold of many of the subjects when artificially degraded. 
The step VEP/GAC acuity difference has a 95% CI of 1.2 logMAR units, which is comparable with estimates by other workers of 0.8 log units 19 and 1.2 log units, 26 across a wide range of acuities. Although this broad range precludes the ability to predict acuity accurately, it is possible to state a likely range of behavioral acuity in patients in whom behavioral testing is not possible. 
In patients, the step VEP test defines acuity in 2.5 minutes on average, including periods of inattention. This interval is significantly shorter than the transient VEP test times of 7.5 minutes, and from experience, is also shorter than many subjective tests (Mackay AM, et al. IOVS 2002;43:ARVO E-Abstract 1811). This short test time is afforded by real-time analysis, an efficient presentation algorithm and employing reversing checkerboards to maximize the likely ssVEP amplitude in our patient group. 50 Although the step VEP test is not clinically interchangeable with subjective tests, the 95% prediction intervals (Fig. 2)from subjects in this study is a first stage in allowing a likely range of logMAR scores to be assigned to a patient’s step VEP result. The step VEP may also prove to be clinically useful for investigating nonorganic visual loss and for assessing patients who cannot perform reading or behavioral acuity tests. 
 
Figure 1.
 
The step VEP system. Monitor 1 is the user screen and monitor 2 is the patient screen. On monitor 1, the top left box shows four EEG channels (Laplacian at bottom), center top box shows the signal-to-noise ratio (SNR) analysis, and the top right box shows T2 CIRC analysis. The bottom box shows the 27 possible check sizes as dots (smallest at the right); black dot: untested check size; green dot: ssVEP detection and its amplitude; red dot: failure to detect an ssVEP. Squares: response phase. In the example illustrated, eight check sizes were viewed to achieve a threshold.
Figure 1.
 
The step VEP system. Monitor 1 is the user screen and monitor 2 is the patient screen. On monitor 1, the top left box shows four EEG channels (Laplacian at bottom), center top box shows the signal-to-noise ratio (SNR) analysis, and the top right box shows T2 CIRC analysis. The bottom box shows the 27 possible check sizes as dots (smallest at the right); black dot: untested check size; green dot: ssVEP detection and its amplitude; red dot: failure to detect an ssVEP. Squares: response phase. In the example illustrated, eight check sizes were viewed to achieve a threshold.
Figure 2.
 
The correlation between step VEP and GAC acuity including 95% prediction intervals (dashed lines) for estimating the range of subjective acuities corresponding to each step VEP outcome.
Figure 2.
 
The correlation between step VEP and GAC acuity including 95% prediction intervals (dashed lines) for estimating the range of subjective acuities corresponding to each step VEP outcome.
Figure 3.
 
Bland-Altman plot showing the difference between step VEP and GAC acuities as a function of mean acuity. Gray lines: 95% CI.
Figure 3.
 
Bland-Altman plot showing the difference between step VEP and GAC acuities as a function of mean acuity. Gray lines: 95% CI.
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Figure 1.
 
The step VEP system. Monitor 1 is the user screen and monitor 2 is the patient screen. On monitor 1, the top left box shows four EEG channels (Laplacian at bottom), center top box shows the signal-to-noise ratio (SNR) analysis, and the top right box shows T2 CIRC analysis. The bottom box shows the 27 possible check sizes as dots (smallest at the right); black dot: untested check size; green dot: ssVEP detection and its amplitude; red dot: failure to detect an ssVEP. Squares: response phase. In the example illustrated, eight check sizes were viewed to achieve a threshold.
Figure 1.
 
The step VEP system. Monitor 1 is the user screen and monitor 2 is the patient screen. On monitor 1, the top left box shows four EEG channels (Laplacian at bottom), center top box shows the signal-to-noise ratio (SNR) analysis, and the top right box shows T2 CIRC analysis. The bottom box shows the 27 possible check sizes as dots (smallest at the right); black dot: untested check size; green dot: ssVEP detection and its amplitude; red dot: failure to detect an ssVEP. Squares: response phase. In the example illustrated, eight check sizes were viewed to achieve a threshold.
Figure 2.
 
The correlation between step VEP and GAC acuity including 95% prediction intervals (dashed lines) for estimating the range of subjective acuities corresponding to each step VEP outcome.
Figure 2.
 
The correlation between step VEP and GAC acuity including 95% prediction intervals (dashed lines) for estimating the range of subjective acuities corresponding to each step VEP outcome.
Figure 3.
 
Bland-Altman plot showing the difference between step VEP and GAC acuities as a function of mean acuity. Gray lines: 95% CI.
Figure 3.
 
Bland-Altman plot showing the difference between step VEP and GAC acuities as a function of mean acuity. Gray lines: 95% CI.
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