Abstract
purpose. To evaluate and compare intra- and intertest variability components for
both standard automated perimetry (SAP) and frequency-doubling
technology (FDT) perimetry in a small group of normal individuals and
patients with glaucoma.
methods. The method of constant stimuli (MOCS) was used to examine matched test
locations with both SAP and FDT perimetry stimuli in a group of eight
normal individuals and seven patients with glaucoma. Subjects were
tested weekly at three predetermined visual field loci for 5
consecutive weeks. Frequency-of-seeing (FOS) curves were generated and
used to quantify threshold sensitivity (50% seen on FOS, in decibels),
intratest variability (FOS interquartile range, in decibels), and
intertest variability (interquartile range of weekly repeated threshold
determinations, in decibels).
results. In patients with glaucoma, SAP intra- and intertest variabilities were
found to increase with sensitivity reductions, as previously reported.
FDT perimetry revealed that both intra- and intertest variability
components did not appreciably change with reductions in sensitivity.
With the measurement scales used in this investigation, both intra- and
intertest variability components were significantly greater for SAP
than for FDT perimetry (P < 0.001 and P = 0.003, respectively). Intratest
variability exceeded intertest variability for both SAP
(P = 0.001) and FDT perimetry
(P < 0.001).
conclusions. For both SAP and FDT perimetry, variability occurring within a single
test session contributed more to total variability than between-session
variability. When the measurement scales available on commercial
instrumentation were used, FDT perimetry exhibited significantly less
variability than SAP, especially within regions of visual field
sensitivity loss. FDT perimetry therefore shows promise as an effective
test for detecting progressive glaucomatous visual field loss, although
prospective longitudinal validation is still required to determine
sensitivity to change.
The purpose of visual field examination in clinical
ophthalmology is threefold: detection of early defects, determination
of specific patterns of visual field loss for differential diagnostic
purposes, and monitoring of patients for evidence of progression,
stability, or improvement of visual field loss. Traditionally,
measurement of perimetric differential light thresholds with
conventional or standard automated perimetry (SAP) has been used for
these objectives. However, newer perimetric techniques using
alternative stimuli and test conditions have recently become available.
An example of this is frequency-doubling technology (FDT) perimetry,
which assesses contrast threshold by using low-spatial-frequency and
high-temporal-frequency test targets to stimulate mechanisms that
demonstrate nonlinear responses to contrast, which serves as the basis
for the frequency-doubling effect.
1 2 It has been
suggested that the frequency-doubling effect is mediated by a subset of
magnocellular (M) ganglion cells, referred to as
My-cells.
3 This My-cell subset reportedly has larger soma
and axon diameters than other M cells, exhibits relatively little
receptive field overlap, and constitutes less than 5% of the total
ganglion cell population. These physiological attributes make FDT
perimetry a good psychophysical test candidate for detection of
glaucoma, because of histologic data reporting that ganglion cells with
larger diameter axons may be preferentially lost in early
glaucoma,
4 5 and also because the reduced redundancy
hypothesis predicts that sparse subsets of ganglion cells will more
readily detect early damage.
6 7
FDT perimetry has been shown to exhibit high discriminatory power for
detection of early glaucoma
8 9 10 11 and is clinically
desirable, because the test is resilient to refractive errors and blur
and has a large dynamic range, and because threshold test strategies
are short in duration. In addition, in patients with glaucoma, it has
been reported that test–retest variability that occurs with FDT
perimetry does not increase as much with increases in defect severity
as with SAP. Provided FDT perimetry demonstrates adequate sensitivity
to change, its beneficial variability characteristics imply that it may
be useful for the detection of glaucomatous visual field
progression.
12
Two variability components have been described for threshold perimetry:
within a single test session (intratest) and between test sessions
(intertest). Tests that exhibit lower amounts of either of these
variability components are likely to be of greater clinical value,
because they may be better able to differentiate progressive visual
function loss from pathophysiologic variability. Quantification of
test–retest variability obtained from clinically applied thresholding
algorithms has been reported for both SAP and FDT
perimetry,
12 13 but does not provide information on the
described individual variability components. Although more rigorous
psychophysical evaluations of intratest variability for both normal and
glaucomatous visual fields have been reported for
SAP,
14 15 16 17 18 this information does not yet exist for FDT
perimetry. The use of these more rigorous psychophysical test
procedures has not been applied to determination of intertest
variability for either SAP or FDT perimetry. Data in previous reports
on intertest variability for SAP were obtained by using mathematical
methods of extraction from threshold estimates derived from repeated
staircase procedures,
19 20 21 22 rather than by more extensive
psychophysical approaches, such as longitudinal evaluation of precise
threshold measurements using repeated frequency-of-seeing (FOS) curves.
The purpose of this investigation was to precisely quantify and compare
intra- and intertest variability components for both SAP and FDT
perimetry in a small group of normal individuals and in a group of
patients with glaucoma.
Data were collected from one eye of seven patients with glaucoma
(one man, six women; age range, 45–86 years) and eight normal
individuals (four men, four women; age range, 21–50 years). Patients
with glaucoma were recruited from Devers Eye Institute and normal
individuals from staff members. All participants were selected on the
basis of good reliability (<20% fixation losses, <33%
false-positive errors, and <33% false-negative errors) on previous
Humphrey Field Analyzer (HFA; Humphrey Systems, Dublin, CA)
examinations.
A fellowship-trained glaucoma specialist diagnosed glaucoma in patients
on the basis of optic nerve head assessment and visual field status.
For patients with glaucoma, the range of mean deviations (MDs) on HFA
program 24-2 (full threshold) examination was from −3.36 to −8.56 dB
(mean, −5.77 dB). No patients with glaucoma were receiving miotic
glaucoma therapy, and natural pupil size was used. Each normal
individual had MD, pattern standard deviation (PSD), and corrected
pattern standard deviation (CPSD) within normal population limits
(P > 0.05); a normal glaucoma hemifield test result;
no history of ophthalmic or systemic disease; and normal findings in an
ocular examination. All subjects had best corrected visual acuity of
20/30 or better.
Informed consent was obtained from each participant in accordance with
the Declaration of Helsinki. The study was approved by the
institutional review board of Legacy Health System.
Matched test locations were examined for both conventional and
frequency-doubled stimuli. Subjects wore appropriate refractive
corrections for both tests. SAP testing was performed on an HFA (model
610; Humphrey) that was externally driven by a computer running custom
software. Test conditions identical with routine testing were used:
size III test target, 200-msec stimulus duration, and 31.5-apostilb
(asb; 10 candelas [cd]/m2) background
illumination. Frequency-doubling stimuli were presented on a 21-in.
video monitor (Multiscan G500; Sony, Tokyo, Japan) driven by a video
board (VSG2/3; Cambridge Research Systems, Rochester, UK).
Frequency-doubling stimuli were generated using the same spatiotemporal
properties used by the commercially available FDT perimeter (0.25
cyc/deg spatial frequency sinusoidal waveforms and 25-Hz counterphase
flicker). Mean luminance was 50 cd/m2. Other
properties of frequency-doubling stimuli were also controlled to
emulate the commercially available FDT instrumentation, including test
target configuration (square 10° × 10°) and stimulus duration
(720-msec total stimulus duration, with 160-msec linear on-ramp from
0% to tested contrast, 400-msec at test contrast, and 160-msec
off-ramp returning to 0% contrast).
The MOCS was used to examine three test locations between
fixation and 20° in each subject. All subjects received MOCS training
in a separate session (on different days) before data collection. In
the group of normal individuals, test locations were chosen so that
equal numbers of superior and inferior locations were used, with equal
spread among eccentricities, thereby providing data representative of
locations throughout tested areas of the visual field. In patients with
glaucoma, test locations were selected in visual field areas that
ranged between normal and moderately damaged (total deviation, up to−
10 dB) on the basis of the most recent SAP examination. This
total-deviation criterion was selected to avoid a floor effect that may
have artifactually truncated variability measurements, had deeper
defects been included.
Each subject was tested at these same three visual field loci weekly on
five consecutive occasions. For each test location and test session,
the MOCS range was centered using an average of two threshold estimates
obtained with a 4- to 2-dB double-reversal staircase algorithm. For
MOCS, seven stimulus luminances were examined, three each side of
estimated threshold. Step sizes between stimuli were adjusted to
approach both 0% and 100% seen, and ranged from 1 to 3 dB. Twenty
stimuli were presented at each stimulus luminance. Stimuli were
randomized between luminance levels and test location. Order of testing
at each session was determined randomly for each subject. Timing of
test during the day was not controlled. Subjects were given short rests
at regular intervals, if required.
It is important to recognize that although SAP and FDT perimetry both
make measurements of sensitivity in decibels, the two measurement
scales differ conceptually and so have different ranges and number of
intervals. Care should be taken to note that HFA decibels and FDT
decibels are not equivalent. In this study, SAP sensitivity
measurements used the proprietary logarithmic HFA scale of retinal
sensitivity. Each interval on this scale represents a 0.1-log unit (1
dB) attenuation of the brightest stimulus that the HFA can present
(10,000 asb). Higher numbers on this scale therefore represent dimmer
stimuli (thus denoting higher sensitivity) and vice versa. This HFA
decibel scale has a range of 4 log units (or 40 dB), with 0 dB being
equivalent to a 10,000-asb increment stimuli and 40 dB being 1 asb on a
31.5-asb background.
23 The scale used for FDT perimetry in
this study is also logarithmic but is a decibels scale of FDT stimulus
contrast sensitivity: 1 dB = log(1/contrast threshold) · 10. An
FDT stimulus that is visible at the maximum stimulus contrast of 100%
corresponds to an FDT scale measurement of 0 dB ([log(1/0)] · 10),
whereas a stimulus perceived at a contrast of 1% is equivalent to a
FDT sensitivity of 20 dB ([log(1/0)] · 10). The FDT scale therefore
has a range of 2 log units (20-dB intervals) to represent the stimulus
contrast range from 1% to 100% and uses 1-dB scale intervals. Because
1 dB on the HFA measurement scale is therefore fundamentally different
from 1 dB on the FDT measurement scale, this difference precludes
comparison of the instruments. In this study it was critical that
comparison between the variability of the instruments be based on the
number of scale intervals that characterize variability, although,
regrettably, both instruments use the same decibel nomenclature.
It is also important to note that the FDT scale used in this experiment
is not the same as the scale of the commercially available FDT device,
which has been adjusted by a proprietary multiplicative factor to
produce an HFA-equivalent range, although it uses the same number of
scale intervals, as described earlier.
FOS curves were constructed by fitting data using a cumulative
gaussian function (Tablecurve 2D; SPSS Science, Chicago, IL). FOS
curves were used to quantify threshold sensitivity (50% seen on FOS,
in decibels), intratest variability (FOS interquartile range, in
decibels) and intertest variability (interquartile range of five
repeated threshold sensitivity determinations over 4 weeks, in
decibels). Other groups have used interquartile range to quantify
intratest variability,
15 16 and this was selected for use
in this study, because it represents a quantity that is common to the
measurement scale of the instrumentation, thereby providing clinical
context.
The mean threshold and mean intratest variability over five repeat
visits were used in all analyses. It was assumed that by use of a
relatively short duration for data collection (4 weeks) any change in
threshold over the examination period could be attributed to intertest
variability, rather than glaucomatous progression.
Data analysis was performed by computer (Intercooled Stata 5.0; Stata,
College Station, TX, and SigmaStat 2.0; SPSS Science).
At any given time point, the amount of physiologic visual system
background noise against which a stimulus signal may be detected is
variable.
25 Over a short time, such as in a single test,
detection threshold is therefore probabilistic, with larger signals
having a higher likelihood of detection. This noise constitutes
intratest patient response variability. In addition, it has been
reported that longer term sensitivity changes, over hours or days, are
also present that are superimposed on intratest
variability.
19 These longer term sensitivity modulations
have been attributed to reversible ocular and neural sensitivity
fluctuations
20 and constitute intertest variability. Both
these variability components affect the precision, or reproducibility,
of visual field test results. Quantification of visual field test
variability is important, because it directly influences the ability of
the test to detect progression. Furthermore, this confounding influence
is augmented by increases in both intra- and intertest variability in
optic nerve diseases, such as glaucoma.
In clinical environments, tests with less variability are therefore
more desirable because they do not require as much sensitivity shift to
denote significant change or progression. In this view, previous
investigators have reported that high-pass resolution perimetry (HRP)
has lower variability than SAP
15 26 and Chauhan et
al.
27 have reported that this results in HRP’s being able
to detect glaucomatous visual field progression an average of 12 to 18
months earlier than SAP. However, it is important to recognize that low
variability does not ensure that a test is sensitive to change.
Prospective longitudinal investigations are still needed to establish
sensitivity to validate the technique as a clinically reliable means of
detecting progressive loss.
The experimental design used in this study provided robust measurements
of threshold and intratest variability, by using FOS curves. Our MOCS
procedure was performed for both SAP and FDT perimetry to provide a
quantitative comparison of their variability characteristics, while
also yielding the first FOS curve analysis for the FDT stimulus. In
addition, an alternative method of intertest variability quantification
was achieved by collection of data for FOS curve construction at the
same test locations on a number of visits. Measurement of intertest
variability in this manner was considered preferable to the previously
reported mathematical extraction techniques that were based on data
gathered using staircase strategies and therefore do not have the
accuracy and precision of FOS curves.
28 29 It was
interesting to note that these MOCS-based sensitivity estimates were,
in some cases, lower than anticipated from the total-deviation
inclusion criterion. This finding may be the result of error in
threshold estimation by either strategy, although the rigorous nature
of MOCS dictates that overestimation of sensitivity by the 4- to 2-dB
double-reversal adaptive staircase strategy is the most parsimonious
explanation.
29
The results of this study are in agreement with reports that
describe significantly increased levels of intra- and
intertest variability with SAP sensitivity reductions in
glaucoma.
13 14 16 18 20 For FDT perimetry,
although average levels of intra-and intertest variability were greater
in patients with glaucoma than in normal individuals, the differences
between the groups were small and were found to be independent of
sensitivity. The amounts of both variability components in this sample
were substantially and significantly less in FDT perimetry than in SAP.
Practically, these findings imply that FDT perimetry may be a valid
tool for detection of change in clinical situations, provided it can be
prospectively shown to exhibit similar or better sensitivity to change
than SAP.
A number of investigators have questioned the cause of increased
variability in damaged visual field areas in SAP.
12 18 30 Given that artifactual fixation errors have been ruled
out,
31 32 it may be postulated that factors responsible
for increased variability include greater background variability
noise—for example, atypical firing characteristics of damaged retinal
ganglion cells or reduced pooling of ganglion cell response signal
caused by lower ganglion cell densities resulting from glaucomatous
cell death.
33 Reports that SAP variability is independent
of the cause of optic nerve damage
18 and is reduced with
larger stimuli
30 are consistent with the latter of these
hypotheses. For these reasons it has been suggested that the larger FDT
perimetry stimulus size (10° compared with the 0.43° used in SAP)
contributes to its lower variability,
12 despite the
differences in relative density between sparse My-cells purported to
produce the frequency-doubling percept and abundant parvocellular
ganglion cells that detect SAP stimuli. The rationale underlying use of
different stimulus sizes for SAP and FDT perimetry in this study was to
permit generalization of the findings to clinical situations. Recent
studies have shown that higher spatial resolution FDT perimetry can be
performed reliably using 4° diameter stimuli in a pattern similar to
the 24-2 used by the HFA.
34 Studies evaluating the
variability characteristics of these smaller stimuli are under way.
In this investigation, intratest variability was found to be
significantly greater than intertest variability for both SAP and FDT
perimetry. It is particularly important to emphasize this result,
because many modern studies that quantify perimetric variability use
test–retest analyses. Test–retest methodology represents a compound
measurement of intra- and intertest variability, because results are
obtained using thresholding strategies used by commercially available
instrumentation, such as the adaptive staircase for SAP
13 and the modified binary search
35 36 for FDT
perimetry.
8 The results obtained by these strategies are
therefore affected by both intra- and intertest variability components.
For this reason, test–retest analysis may be mistakenly interpreted as
a quantification of intertest variability alone. By demonstrating that
intratest variability is a significantly larger variability component
than intertest variability, intratest variability therefore
contributes more to test–retest variability. It should also be noted
that test–retest analyses are subject to variability induced by the
thresholding strategy. Thresholding strategies that exhibit equal or
less intratest variability, such as those based on maximum
likelihood
37 (e.g., the Swedish Interactive threshold
algorithm [SITA]
38 or ZEST for FDT
perimetry
39 ) may be of greater value for monitoring
progression.
Although the comparison of the two perimetric techniques performed in
this investigation suggests that FDT perimetry demonstrates more
favorable variability characteristics than SAP, it is important to
recognize that this finding may have resulted from differences in
measurement scales between the two techniques. The measurement scale
used for FDT perimetry was purposely designed to be equivalent to the
20-interval scale used by the commercial instrumentation, but was
compared in this investigation with the 40-interval HFA scale.
Therefore, although FDT perimetry appeared to exhibit less variability
with this coarse measurement scale, use of such a scale may be less
sensitive to progressive loss than a finer scale. The issue of whether
FDT perimetry is more sensitive to change than SAP requires resolution
by prospective longitudinal clinical investigation. In addition, the
possibility that use of an equal number of scale intervals by both
techniques may yield minimal differences in variability components
should also be considered.
In summary, this study shows that under test and measurement scale
conditions similar to those used in clinical situations, FDT perimetry
exhibited significantly lower intra- and intertest variability than
SAP. FDT perimetry may therefore be preferable for monitoring
individuals with glaucoma, because less sensitivity change is required
to exceed variability. However, longitudinal investigations are
needed to establish the sensitivity of FDT perimetry to change. Also,
intratest variability contributes more to total variability than
intertest variability, implying that thresholding strategies with lower
intratest variability used with either SAP or FDT perimetry will be
able to differentiate significant change from variability. Thresholding
strategies with lower intratest variability may have preferable
discriminatory power for detection of progressive defects.
Supported in part by Grant EY03424 from the National Eye Institute
(CAJ).
Submitted for publication June 12, 2000; revised August 31 and December
13, 2000; accepted January 12, 2001.
Commercial relationships policy: F (CAJ); C (CAJ); N (all others).
Corresponding author: Paul G. D. Spry, Bristol Eye Hospital, Lower
Maudlin Street, Bristol BS1 2LX, UK.
[email protected]
Table 1. Summary Data for Intra- and Intertest Variability for SAP and FDT
Perimetry
Table 1. Summary Data for Intra- and Intertest Variability for SAP and FDT
Perimetry
| SAP | | FDT Perimetry | |
| Normal Individuals (n = 24) | Glaucoma Patients (n = 21) | Normal Individuals (n = 24) | Glaucoma Patients (n = 21) |
| Mean intratest variability | 1.5 ± 0.30 | 6.3 ± 5.01 | 1.0 ± 0.25 | 1.5 ± 0.42 |
| 95% confidence interval | 1.62–1.38 | 8.44–4.16 | 1.10–0.90 | 1.68–1.32 |
| Mean intertest variability | 0.7 ± 0.36 | 2.5 ± 2.12 | 0.7 ± 0.22 | 0.8 ± 0.40 |
| 95% confidence interval | 0.84–0.56 | 3.41–1.59 | 0.79–0.61 | 0.97–0.63 |
Table 2. Results of Linear Least-Squares Regression for Intratest Variability by
Test Type
Table 2. Results of Linear Least-Squares Regression for Intratest Variability by
Test Type
| Group | Slope | 95% CI (Slope) | P (Slope) | Y Intercept | 95% CI (Y Intercept) |
| SAP normal individuals | 0.02 | 0.07, −0.04 | 0.56 | 0.93 | 2.92, −1.05 |
| SAP glaucoma patients | −0.63 | −0.42, −0.83 | <0.001 | 20.20 | 25.01, 15.40 |
| FDT normal individuals | 0.04 | 0.13, −0.05 | 0.34 | 0.28 | 1.84, −1.27 |
| FDT glaucoma patients | −0.05 | 0.02, −0.12 | 0.18 | 1.94 | 2.69, 1.19 |
Table 3. Results of Linear Least-Squares Regression for Intertest Variability by
Test Type
Table 3. Results of Linear Least-Squares Regression for Intertest Variability by
Test Type
| Group | Slope | 95% CI (Slope) | P (Slope) | Y Intercept | 95% CI (Y Intercept) |
| SAP normal individuals | 0.01 | 0.08, −0.06 | 0.75 | 0.28 | 2.67, −2.10 |
| SAP glaucoma patients | −0.20 | −0.07, −0.32 | 0.003 | 6.84 | 9.67, 4.01 |
| FDT normal individuals | −0.10 | −0.03, −0.16 | 0.006 | 2.38 | 3.56, 1.19 |
| FDT glaucoma patients | −0.04 | 0.03, −0.10 | 0.26 | 1.20 | 1.92, 0.49 |
Kelly DH. Frequency doubling in visual responses. J Opt Soc Am A
. 1966;56:1628–1633.
[CrossRef] Kelly DH. Nonlinear visual responses to flickering sinusoidal gratings. J Opt Soc Am A
. 1981;71:1051–1055.
[CrossRef] Maddess T, Henry G. Performance of non-linear visual units in ocular hypertension and glaucoma. Clin Vis Sci. 1992;7:371–383.
Quigley HA, Dunkelberger GR, Green WR. Chronic human glaucoma causing selectively greater loss of large optic nerve fibers. Ophthalmology
. 1988;95:357–363.
[CrossRef] [PubMed]Glovinsky Y, Quigley HA, Dunkelberger GR. Retinal ganglion cell loss is size dependent in experimental glaucoma. Invest Ophthalmol Vis Sci
. 1991;32:484–491.
[PubMed]Johnson C. Selective versus non-selective losses in glaucoma. J Glaucoma. 1994;3:32–44.
Johnson CA. The Glenn A. Fry Award Lecture: early losses of visual function in glaucoma. Optom Vis Sci
. 1995;72:359–370.
[CrossRef] [PubMed]Johnson CA, Samuels SJ. Screening for glaucomatous visual field loss with frequency-doubling perimetry. Invest Ophthalmol Vis Sci
. 1997;38:413–425.
[PubMed]Quigley HA. Identification of glaucoma-related visual field abnormality with the screening protocol of frequency doubling technology. Am J Ophthalmol
. 1998;125:819–829.
[CrossRef] [PubMed]Yamada N, Chen PP, Mills RP, et al. Screening for glaucoma with frequency-doubling technology and Damato campimetry. Arch Ophthalmol
. 1999;117:1479–1484.
[CrossRef] [PubMed]Cello KE, Nelson–Quigg JM, Johnson CA. Frequency doubling technology perimetry for detection of glaucomatous visual field loss. Am J Ophthalmol
. 2000;129:314–322.
[CrossRef] [PubMed]Chauhan BC, Johnson CA. Test–retest variability of frequency-doubling perimetry and conventional perimetry in glaucoma patients and normal subjects. Invest Ophthalmol Vis Sci
. 1999;40:648–656.
[PubMed]Heijl A, Lindgren A, Lindgren G. Test–retest variability in glaucomatous visual fields. Am J Ophthalmol
. 1989;108:130–135.
[CrossRef] [PubMed]Weber J, Rau S. The properties of perimetric thresholds in normal and glaucomatous eyes. Ger J Ophthalmol
. 1992;1:79–85.
[PubMed]Chauhan BC, House PH. Intratest variability in conventional and high-pass resolution perimetry. Ophthalmology
. 1991;98:79–83.
[CrossRef] [PubMed]Chauhan BC, Tompkins JD, LeBlanc RP, McCormick TA. Characteristics of frequency-of-seeing curves in normal subjects, patients with suspected glaucoma, and patients with glaucoma. Invest Ophthalmol Vis Sci
. 1993;34:3534–3540.
[PubMed]Henson D, Chaudry S, Artes P. The relationship between sensitivity and variability in normal and glaucomatous visual fields. Wall M Wild JM eds. Perimetry Update 1998/9. 1999;95–101. Kugler The Hague.
Henson DB, Chaudry S, Artes PH, Faragher EB, Ansons A. Response variability in the visual field: comparison of optic neuritis, glaucoma, ocular hypertension, and normal eyes. Invest Ophthalmol Vis Sci
. 2000;41:417–421.
[PubMed]Bebie H, Fankhauser F, Spahr J. Static perimetry: accuracy and fluctuations. Acta Ophthalmol (
Copenh)
. 1976;54:339–348.
[PubMed]Flammer J, Drance SM, Zulauf M. Differential light threshold: short- and long-term fluctuation in patients with glaucoma, normal controls, and patients with suspected glaucoma. Arch Ophthalmol
. 1984;102:704–706.
[CrossRef] [PubMed]Wall M, Johnson CA, Kutzko KE, et al. Long- and short-term variability of automated perimetry results in patients with optic neuritis and healthy subjects. Arch Ophthalmol
. 1998;116:53–61.
[CrossRef] [PubMed]Blumenthal EZ, Sample PA, Zangwill L, et al. Comparison of long-term variability for standard and short-wavelength automated perimetry in stable glaucoma patients. Am J Ophthalmol
. 2000;129:309–313.
[CrossRef] [PubMed]Anderson DR, Patella VM. Automated Static Perimetry. 1999; 2nd ed. 12–17. Mosby St Louis.
Lester M, Mermoud A, Schnyder C. Frequency doubling technique in patients with ocular hypertension and glaucoma: correlation with octopus perimeter indices. Ophthalmology
. 2000;107:288–294.
[CrossRef] [PubMed]Barlow HB, Levick WR. Three factors limiting the reliable detection of light by retinal ganglion cells of the cat. J Physiol (Lond)
. 1969;200:1–24.
[PubMed]Wall M, Lefante J, Conway M. Variability of high-pass resolution perimetry in normals and patients with idiopathic intracranial hypertension. Invest Ophthalmol Vis Sci
. 1991;32:3091–3095.
[PubMed]Chauhan BC, House PH, McCormick TA, LeBlanc RP. Comparison of conventional and high-pass resolution perimetry in a prospective study of patients with glaucoma and healthy controls. Arch Ophthalmol
. 1999;117:24–33.
[CrossRef] [PubMed]Casson EJ, Shapiro LR, Johnson CA. Short-term fluctuation as an estimate of variability in visual field data. Invest Ophthalmol Vis Sci
. 1990;31:2459–2463.
[PubMed]Johnson CA, Chauhan BC, Shapiro LR. Properties of staircase procedures for estimating thresholds in automated perimetry. Invest Ophthalmol Vis Sci
. 1992;33:2966–2974.
[PubMed]Wall M, Kutzko KE, Chauhan BC. Variability in patients with glaucomatous visual field damage is reduced using size V stimuli. Invest Ophthalmol Vis Sci
. 1997;38:426–435.
[PubMed]Henson DB, Evans J, Chauhan BC, Lane C. Influence of fixation accuracy on threshold variability in patients with open angle glaucoma. Invest Ophthalmol Vis Sci
. 1996;37:444–450.
[PubMed]Demirel S, Johnson CA, Fendrich R, Vingrys AJ. The slope of frequency of seeing curves in normal, amblyopic and pathological vision: visual science and its applications. Opt Soc Am Tech Dig Ser. 1997;1:244–247.
Tolhurst DJ, Movshon JA, Dean AF. The statistical reliability of signals in single neurons in cat and monkey visual cortex. Vision Res
. 1983;23:775–785.
[CrossRef] [PubMed]Johnson C, Cioffi G, Van Buskirk E. Frequency doubling technology using a 24-2 stimulus presentation pattern. Optom Vis Sci
. 1999;76:571–581.
[CrossRef] [PubMed]Tyrell R, Owens D. A rapid technique to assess the resting states of the eyes and other threshold phenomena: the modified binary search (MOBS). Behav Res Methods Instrum Comput
. 1988;20:137–141.
[CrossRef] Johnson CA, Shapiro LR. A comparison of MOBS (modified binary search) and staircase test procedures in automated perimetry. J Opt Soc Am Tech Dig Ser. 1989;7:98–102.
King–Smith PE, Grigsby SS, Vingrys AJ, Benes SC, Supowit A. Efficient and unbiased modifications of the QUEST threshold method: theory, simulations, experimental evaluation and practical implementation. Vision Res
. 1994;34:885–912.
[CrossRef] [PubMed]Bengtsson B, Olsson J, Heijl A, Rootzén H. A new generation of algorithms for computerized threshold perimetry, SITA. Acta Ophthalmol Scand
. 1997;75:368–375.
[PubMed]Turpin A, Johnson CA, Vingrys AJ. Fast test procedures for frequency-doubling perimetry [ARVO Abstract]. Invest Ophthalmol Vis Sci. 2000;41(4)S1546.Abstract nr 1546