 |
|
Discriminating Between Normal and Glaucomatous Eyes Using the Heidelberg Retina Tomograph, GDx Nerve Fiber Analyzer, and Optical Coherence Tomograph
Linda M. Zangwill, PhD;
Christopher Bowd, PhD;
Charles C. Berry, PhD;
Julia Williams, BS;
Eytan Z. Blumenthal, MD;
César A. Sánchez-Galeana, MD;
Christiana Vasile, MD;
Robert N. Weinreb, MD
Arch Ophthalmol. 2001;119:985-993.
ABSTRACT
| |
Objective To compare the ability of 3 instruments, the Heidelberg Retina Tomograph
(HRT), the GDx Nerve Fiber Analyzer (GDx), and the Optical Coherence Tomograph
(OCT), to discriminate between healthy eyes and eyes with early to moderate
glaucomatous visual field loss.
Subjects and Methods Forty-one patients with early to moderate glaucomatous visual field
loss and 50 healthy subjects were included in the study. The HRT, GDx, and
OCT imaging and visual field testing were completed on 1 eye from each subject
within a 6-month interval. Statistical differences in sensitivity at fixed
specificities of 85%, 90%, and 95% were evaluated. In addition, areas under
the receiver operating characteristic (ROC) curve were compared.
Results No significant differences were found between the area under the ROC
curve and the best parameter from each instrument: OCT thickness at the 5-o'clock
inferior temporal position (mean ± SE, 0.87 ± 0.04), HRT mean
height contour in the nasal inferior region (mean ± SE, 0.86 ±
0.04), and GDx linear discriminant function (mean ± SE, 0.84 ±
0.04). Twelve HRT, 2 GDx, and 9 OCT parameters had an area under the ROC curve
of at least 0.81. At a fixed specificity of 90%, significant differences were
found between the sensitivity of OCT thickness at the 5-o'clock inferior temporal
position (71%) and parameters with sensitivities less than 52%. Qualitative
assessment of stereophotographs resulted in a sensitivity of 80%.
Conclusion Although the area under the ROC curves was similar among the best parameters
from each instrument, qualitative assessment of stereophotographs and measurements
from the OCT and HRT generally had higher sensitivities than measurements
from the GDx.
INTRODUCTION
NEW METHODS including confocal scanning laser ophthalmoscopy, scanning
laser polarimetry, and optical coherence tomography have been developed to
provide real-time, quantitative information describing the optic disc and
retinal nerve fiber layer (RNFL). Each of these methods uses different features
of the retina or RNFL, and different properties of light to obtain clinical
measurements of optic disc topography or RNFL thickness. Because RNFL and
optic disc damage have been shown to precede visual field loss,1-8
objective methods of measuring these conditions may help physicians diagnose
and monitor glaucoma.
Despite considerable overlap in optic disc and RNFL measurements, statistically
significant differences between glaucomatous and healthy eyes using either
confocal scanning laser ophthalmoscopy, scanning laser polarimetry, or optical
coherence tomography parameters have been reported.9-14
Several different strategies are available for summarizing the information
on optic disc topography and RNFL thickness obtained with these instruments.
First, each method provides several summary measurements of single parameters
(eg, RNFL thickness, rim area, or cup shape). The use of combinations of parameters
in discriminant analysis has also been evaluated.10, 15
Finally, normative databases have been used to identify parameters outside
a normal range of measurements.
There are, however, conflicting reports regarding the ability of these
methods to discriminate between normal and glaucomatous eyes. Because of the
large variability in reported sensitivity and specificity measures, studies
are needed to confirm estimates of these measures by different investigators
in varied study populations. Comparison across studies can be difficult because
of differences in study design and characteristics of the study population.
Because the ability to detect glaucoma improves with increasing severity of
the disease, it is important to compare methods using similar inclusion and
exclusion criteria as well as similar population characteristics, including
age and severity of glaucoma. To best reduce the influence of population characteristics
across studies, it is valuable to compare the ability of each method to detect
glaucoma in the same study population.
This study was designed to compare, in one study population, the ability
of the 3 methods to discriminate between healthy eyes and eyes with early
to moderate glaucomatous visual field loss using commercially available instruments:
a confocal scanning laser ophthalmoscope (Heidelberg Retina Tomograph [HRT];
Heidelberg Engineering, Heidelberg, Germany), a scanning laser polarimeter
(GDx Nerve Fiber Analyzer [GDx]; Laser Diagnostic Technologies, San Diego,
Calif), and the Optical Coherence Tomograph (OCT; Humphrey-Zeiss, Dublin,
Calif).
SUBJECTS AND METHODS
SUBJECTS
The study included 1 randomly selected eye from each of 41 glaucoma
patients with early to moderate glaucomatous visual field loss and each of
50 healthy subjects. Healthy subjects were included if their age equaled or
exceeded that of the youngest patient with glaucoma (40 years of age). Ninety
percent of normal subjects and patients with glaucoma were younger than 78
years. Mean age of the glaucomatous patients and normal subjects was 66.2
years (95% confidence interval [CI], 62.2-70.4 years) and 56.1 years (95%
CI, 52.6-59.5 years), respectively.
Prior to ocular imaging, all subjects underwent a complete ophthalmologic
examination that included slitlamp biomicroscopy, intraocular pressure (IOP)
measurement, dilated stereoscopic fundus examination, stereoscopic photography
of the optic disc, and standard (achromatic) full-threshold visual field testing
with program 24-2 (Humphrey Field Analyzer; Humphrey-Zeiss). Informed consent
was obtained from all participants, and the University of California–San
Diego Human Subjects Committee approved all methods used.
Glaucomatous visual field loss was defined as a corrected-pattern standard
deviation outside of the 95% normal limits or a glaucoma hemifield test outside
of the 99% normal limits. Two abnormal visual fields were required. Mean deviation
of the visual field test in these glaucomatous (open angle) eyes was -5.14
dB (95% CI, -3.47 to -6.81 dB), indicating early to moderate visual
field damage. In 3 cases, when repeated achromatic visual field testing was
unavailable, repeated abnormal fields were defined as 1 abnormal achromatic
field and 1 abnormal short-wavelength automated perimetry field. The same
criteria for defects were used for short-wavelength automated perimetry fields
and achromatic fields. Patients with glaucoma had no history of diabetes and
were not using medication known to affect visual sensitivity at the time of
visual field testing. Best-corrected visual acuity was 20/40 or better. To
avoid overstating the area under the receiver operating characteristic (ROC)
curves and sensitivities of the tests,16 appearance
of the optic disc and/or RNFL were not inclusion or exclusion criteria for
the glaucoma group.
Healthy eyes had a measured IOP of 22 mm Hg or less with no history
of elevated IOP. These eyes had intact rims; no evidence of hemorrhage, notching,
excavation, or RNFL defect; and symmetrical optic discs (asymmetry of vertical
cup-disc ratio <0.2) based on clinical examination. Visual field results
showed a corrected-pattern standard deviation, mean deviation, and glaucoma
hemifield test results within normal limits. Healthy subjects had no history
of diabetes or other systemic disease, had no ophthalmological or neurological
surgery or disease, and were not using medication known to affect visual sensitivity
at the time of visual field testing. Best-corrected visual acuity at the time
of testing was 20/40 or better.
All subjects underwent ocular imaging with the HRT, GDx, and OCT. For
each subject, all ocular imaging and visual field examinations were completed
within 6 months.
INSTRUMENTATION
Confocal Scanning Laser Ophthalmoscope
The HRT employs confocal scanning diode technology to provide topographical
measures of the optic disc and peripapillary retina. The topographical image
is derived from 32 optical sections at consecutive focal depth planes. Each
image consists of 256x256 pixels, with each pixel corresponding to retinal
height at its location.
Topographical parameters included with HRT software and investigated
in this study were mean cup depth, maximum cup depth, height variation in
contour, mean height contour, cup shape, disc area, cup area, cup-disc area
ratio, cup volume below surface, rim area, rim volume above reference plane,
rim disc ratio, RNFL thickness, RNFL cross-section, and reference height.
We also examined values from the discriminant analysis formula of Mikelberg
et al10 (the HRT classification in current
HRT software version 2.01; Heidelberg Engineering, Heidelberg, Germany) and
one developed by Bathija et al.9 This instrument
and these parameters have been discussed in more detail elsewhere.10, 17-18
Several of these parameters were further examined by region. Temporal
superior (45°-90° unit circle), nasal superior (91°-135°),
nasal inferior (226°-270°), and temporal inferior (271°-315°)
regions for disc area, cup area, mean height contour, cup volume, rim volume,
maximum cup depth, cup shape, rim area, rim disc ratio, and RNFL thickness
were all evaluated. Particular attention was given to the superior and inferior
regions because these areas have proved informative in glaucoma diagnosis.19-20
Three 15° field-of-view scans judged to be of acceptable quality
were obtained for each test eye. A mean topographic image of these 3 scans
was created using HRT software version 2.01. A trained technician outlined
the optic disc margin on the mean topographic image while viewing stereoscopic
photographs of the optic disc.
Scanning Laser Polarimetry
The GDx Nerve Fiber Analyzer uses scanning laser technology coupled
with an integrated polarization modulator to provide a retardation map of
the peripapillary retina based on the birefringent properties of the RNFL.
This instrument measures retardation of light that has double passed the birefringent
fibers of the RNFL. Each resulting image consists of 256x256 pixels,
with each pixel corresponding to the retardation value at its location.
GDx software–provided parameters investigated in this study were
the GDx number (a neural network assessment of glaucoma likelihood); average
thickness, volume, and symmetry (superior quadrant thickness/inferior quadrant
thickness); superior ratio (superior quadrant thickness/temporal quadrant
thickness); inferior ratio (inferior quadrant thickness/temporal quadrant
thickness); superior/nasal ratio; maximum modulation (thickest quadrant/thinnest
quadrant)/(thinnest quadrant); superior maximum (average of thickest 1500
pixels in superior quadrant); inferior maximum; ellipse modulation; ellipse
average; superior average; inferior average; and superior integral. The latter
5 parameters are measured relative to an ellipse surrounding the optic disc.
GDx quadrants are defined as temporal (334°-24° unit circle), superior
(25°-144°), nasal (145°-214°), and inferior (215°-334°).
The value of a discriminant analysis model proposed by Weinreb et al15 was also investigated. Details of this instrument
and these parameters have been discussed elsewhere.11-12,15, 21-22
Three scans judged to be of acceptable quality were obtained for each
test eye. A mean retardation map composed of these 3 scans was created using
GDx software version 2.0.09. The optic disc margin was outlined on the mean
retardation image by a trained technician.
Optical Coherence Tomography
The OCT employs low-coherence interferometry to assess peripapillary
RNFL thickness. Details of this instrument have been described elsewhere.14, 23-24 In brief, the OCT
measures RNFL thickness by the difference in temporal delay of back-scattered
light from the RNFL and a reference beam. The RNFL is differentiated from
other retinal layers using an edge detection algorithm. Nerve fiber layer
thickness is defined as the number of pixels between the anterior and posterior
edges of the RNFL (software version A4X1; Humphrey-Zeiss). Each resulting
image consists of RNFL thickness measurements (in micrometers) at 100 points
along a 360° circular ring around the optic disc.
Optical Coherence Tomography parameters automatically calculated with
existing software included mean RNFL thickness (360° measure), temporal
quadrant thickness (316°-45° unit circle), superior quadrant thickness
(46°-135°), nasal quadrant thickness (136°-225°), inferior
quadrant thickness (226°-315°), and thickness for each of 12 clock-hour
positions with the 3-o'clock position as temporal; 6-o'clock position, inferior;
9-o'clock position, nasal; and 12-o'clock position, superior. The following
parameters were derived from the existing measurements in an attempt to measure
modulation or differences between the superior and inferior regions and between
the nasal and temporal RNFL thickness measurements: inferior 3 minus nasal
(mean RNFL thickness of the inferior 3 clock-hour positions [5-, 6-, and 7-o'clock
positions] minus RNFL thickness of the nasal clock-hour position [9]), inferior
3 minus temporal, superior 3 minus nasal, superior 3 minus temporal, and maximum
minus minimum (mean RNFL thickness in thickest quadrant minus mean RNFL thickness
in the thinnest quadrant).
Three circular 3.4-mm-diameter scans, centered on the optic disc and
judged to be of acceptable quality, were obtained for each test eye. This
approximate scan diameter was found to be optimal for RNFL analysis in a prototype
instrument.25 The landmark option was used
to facilitate placement of the scan circle at the same location on repeated
scans. Mean RNFL thickness for quadrant, clock-hour measurements, and derived
parameters were determined from the 3 images obtained.
STEREOPHOTOGRAPHY
Simultaneous stereophotographs were obtained using a Topcon camera (TRC-SS;
Topcon Instrument Corp of America, Paramus, NJ) after maximal pupil dilation.
All photograph evaluations were performed using a stereoscopic viewer (Asahi
Pentax Stereo Viewer II; Asahi Optical Co, Tokyo, Japan) with a standard fluorescent
lightbulb. At least 2 experienced graders (C.V., E.Z.B., and C.A.S.), masked
to patient identification and diagnosis, reviewed each photograph independently
and recorded the photograph as either glaucomatous, normal, indeterminate,
or poor quality. For this study, indeterminate was classified as normal, and
poor-quality photographs were excluded from the analysis. Disagreements in
grading were resolved by consensus.
STATISTICAL ANALYSES
t Tests were used to evaluate optic disc and
RNFL measurement differences between glaucomatous and healthy eyes. Bonferroni
adjustments were made based on the number of comparisons within each analysis
(eg, HRT, GDx, and OCT analyses).
Receiver operating characteristic curves were used to describe the ability
of each parameter to differentiate glaucomatous from healthy eyes. An area
under the ROC curve of 1.0 represents perfect discrimination, whereas an area
of 0.5 represents chance discrimination. The method of DeLong et al26 was used to compare areas under the ROC curve. Minimum
specificity cutoffs of 85%, 90%, and 95% were used for comparing the sensitivity
of the best single parameter with the sensitivity of the remaining parameters
by the McNemar test for paired proportions.
RESULTS
CONFOCAL SCANNING LASER OPHTHALMOSCOPY
Measures for the 20 global and regional HRT parameters with the largest
areas under the ROC curve for both glaucomatous and healthy eyes are presented
in Table 1. After the Bonferroni
adjustment ( = .0008; 59 comparisons), significant differences between
study groups were found for all HRT parameters except mean cup depth, maximum
cup depth, disc area, cup volume, and reference height, as well as the 4 disc
area regions (superior temporal, superior nasal, inferior temporal, and inferior
nasal) and the 4 maximum cup depth regions.
|
|
|
|
Table 1. Heidelberg Retina Tomograph–Measured Parameter Values
for Glaucomatous and Healthy Eyes*
|
|
|
The HRT parameters with the greatest area under the ROC curve (ROC area)
were mean height contour nasal inferior (0.86), linear discriminant function
(0.85),9 and rim disc ratio temporal inferior
(0.84) (Table 1, Figure 1). Nine of the top 10 regional parameters reflected measurements
in the inferior region. There were no significant differences between ROC
curve areas for these 20 parameters (for all comparisons, P>.05).
|
|
|
|
Figure 1. Receiver operating characteristic
(ROC) curves (and area under ROC curve) of best variables from the Heidelberg
Retina Tomograph (HRT; confocal scanning laser ophthalmoscope; Heidelberg
Engineering, Heidelberg, Germany). The HRT linear discriminant function is
from Bathija et al.9
|
|
|
SCANNING LASER POLARIMETRY
Measures for GDx parameters for both glaucomatous and normal eyes and
areas under the ROC curve are presented in Table 2. After the Bonferroni adjustment ( = .003; 15 comparisons),
significant differences between study groups were found for all GDx parameters
except symmetry (P = .024), superior ratio (P = .007), and inferior ratio (P
= .149).
|
|
|
|
Table 2. GDx-Measured Parameter Values for Glaucomatous and Healthy
Eyes*
|
|
|
The GDx parameters with the greatest area under the ROC curve (ROC area)
were linear discriminant function15 (0.85),
GDx number (0.81), superior-nasal ratio (0.77), superior maximum (0.77), and
superior average (0.77). There were no significant differences between ROC
curve areas for these parameters (for all comparisons, P>.05). Areas under the ROC curve for the 3 parameters with the largest
areas are shown in Figure 2.
|
|
|
|
Figure 2. Receiver operating characteristic
(ROC) curves (and area under ROC curve) of best variables from the GDx Nerve
Fiber Analyzer (a scanning laser polarimeter; Laser Diagnostic Technologies,
San Diego, Calif). GDx number indicates a neural network assessment of glaucoma
likelihood.
|
|
|
OPTICAL COHERENCE TOMOGRAPHY
Measures for all OCT parameters for both glaucomatous and normal eyes
and areas under the ROC curve are presented in Table 3. After the Bonferroni adjustment ( = .002; 22 comparisons),
significant differences between study groups were found for all OCT parameters
except nasal quadrant thickness, thickness at the 9-o'clock position (nasal
clock-hour), thickness at the 3-o'clock position (temporal clock-hour), and
thickness at the 8-o'clock position.
|
|
|
|
Table 3. Optical Coherence Tomograph–Measured Parameter Values
for Glaucomatous and Healthy Eyes*
|
|
|
The OCT parameters with the greatest area under the ROC curve were all
related to the inferior region: thickness at the 5-o'clock position (0.87),
inferior quadrant thickness (0.84), and inferior 3 minus nasal (0.83) (Figure 3). There were no significant differences
between ROC curve areas for these parameters (for all comparisons, P>.05).
|
|
|
|
Figure 3. Receiver operating characteristic
(ROC) curves (and area under ROC curve) of best variables from the Optical
Coherence Tomograph (Humphrey-Zeiss, Dublin, Calif).
|
|
|
We also determined whether a linear discriminant function combining
individual OCT parameters would be a better predictor of glaucoma than single
parameters by using Fisher linear discriminant functions to develop classification
rules. These rules differentiate glaucomatous from healthy eyes by using all
subsets of measures from the OCT. We created linear discriminant functions
by examining the ratios for subsets consisting of 1 variable, 2 variables,
3 variables, and so on. No linear discriminant function resulted in a greater
area under the ROC curve than the single best individual parameter (thickness
at the 5-o'clock position).
Differences in RNFL thickness may have been affected by differences
in disc size between diagnostic groups; in subjects with larger discs, OCT
RNFL measurements are taken nearer to the disc because of the set radius of
the circular scan. We examined the difference in disc size between the diagnostic
groups (t test) and found no significant results
(P>0.1 for all).
COMPARING HRT, GDx, AND OCT
The 3 parameters with the greatest area under the ROC curve for each
instrument were OCT thickness at the 5-o'clock position (0.87), HRT mean height
contour nasal inferior (0.86), and GDx linear discriminant function (0.84)
(Figure 4). There were no significant
differences between ROC curve areas for these parameters (for all comparisons, P>.05).
|
|
|
|
Figure 4. Receiver operating characteristic
(ROC) curves (and area under ROC curve) of best variables from the Optical
Coherence Tomograph (Humphrey-Zeiss, Dublin, Calif), GDx Nerve Fiber Analyzer
(a scanning laser polarimeter; Laser Diagnostic Technologies, San Diego, Calif),
and Heidelberg Retina Tomograph (a confocal scanning laser ophthalmoscope;
Heidelberg Engineering, Heidelberg, Germany). The GDx linear discriminant
function is from Weinreb et al.15
|
|
|
Among parameters with an area under the ROC curve of at least 0.81,
9 were OCT parameters, 12 were HRT parameters, and 2 were GDx parameters (Table 4). Areas under the ROC curve of
the parameters in Table 4 were
not significantly different from each other (for all comparisons, P>.05). However, significant (P<.05) differences
between the sensitivity of the single best individual parameter, OCT thickness
at the 5-o'clock position, and parameters with sensitivities of approximately
47% or less were found at specificities of at least 90% (6 parameters) and
95% (18 parameters) (Table 4).
At a specificity of 85%, significant differences were found between the variable
with the highest sensitivity, HRT mean height contour nasal inferior (81%),
and 8 parameters with sensitivities less than 59%.
|
|
|
|
Table 4. Sensitivities and Specificities for the Parameters With Areas
Under the ROC Curve of More Than 0.80*
|
|
|
Interestingly, at specificities of 90% or greater and 95% or greater,
6 (14.6%) of 41 and 10 (24%) of the 51 glaucomatous eyes in this study, respectively,
were classified as normal by each of the "best" (largest ROC area) parameters
from each instrument (Figure 5).
At a specificity of 85%, all 41 patients were classified as having glaucomatous
eyes by at least 1 instrument. There also was limited agreement among these
parameters concerning which eyes were glaucomatous. Depending on the specificity
level chosen, between 5 and 17 eyes were correctly identified as glaucomatous
by the best parameters of all 3 instruments (Figure 5). There was better agreement in the correct classification
of normal eyes. Thirty-two (64%), 40 (80%), and 46 (92%) of the 50 normal
eyes were correctly classified by the best parameters from each instrument
for specificities of 85%, 90%, and 95%, respectively. All normal eyes were
correctly classified by at least 1 instrument.
|
|
|
|
Figure 5. Venn diagram showing the number
of eyes correctly classified as glaucomatous by the best parameter of each
instrument at a fixed specificity of at least 85% (A), 90% (B), and 95% (C).
There was limited agreement among instruments in the detection of 41 glaucomatous
eyes.
|
|
|
STEREOPHOTOGRAPHY
We also compared the sensitivity for detecting glaucoma by standardized
qualitative grading of stereophotographs. Photographs were graded for 40 of
the 41 glaucomatous eyes; 1 photograph was of poor quality and could not be
graded. Glaucoma was detected in 32 of the 40 eyes, for a sensitivity of 80%.
At a specificity of 90% or greater, statistically significant differences
were found between the sensitivity of photography and parameters with a sensitivity
of 55% or lower (P<.001). Specificity was not
reported for stereophotography because normal appearance of the optic disc,
based on clinical examination, was part of the inclusion criteria for normal
subjects.
COMMENT
This study is unique because it compares the discriminating ability
of 3 instruments (HRT, GDx, and OCT) and stereophotography in 1 study population.
Our results did not find significant differences between the ability to detect
early to moderate glaucomatous visual field loss among the best parameters
of the 3 instruments as measured by the area under the ROC curve. However,
fewer GDx parameters had areas under the ROC curve of 0.81 or greater than
did parameters from the OCT or HRT. At a fixed specificity of at least 90%,
GDx number (sensitivity = 41%) was found to be significantly lower than the
best HRT and OCT individual parameters, OCT thickness at the 5-o'clock position
(sensitivity = 71%), and HRT mean height contour in the nasal inferior region
(sensitivity = 63%). The 3 instruments did not correctly identify the same
glaucomatous eyes, suggesting that each instrument may be measuring different
characteristics. Qualitative evaluation of stereophotographs had a high sensitivity
(80%) for detecting glaucoma.
These results confirm other investigators' results9-10,12-13,15, 22, 27-30
that report considerable overlap between HRT, GDx, and OCT measurements in
normal and glaucomatous eyes. In part, this is due to the large range in the
number of nerve fibers and axons across the normal population (660 000-1.5
million31-33)
and the variability in the appearance of the healthy eye. This limits the
ability of any instrument to differentiate perfectly between normal and glaucomatous
eyes.
Despite limitations, these instruments provide information that can
help differentiate between healthy and glaucomatous eyes. Several investigators
have provided estimates of the sensitivity and specificity for detecting glaucoma
with imaging instruments.9-10,12-13,15, 19-20,22, 27, 30, 34-37
Using the HRT classification developed by Mikelberg et al, sensitivity
and specificity estimates range from 74% and 88%38
to 87% and 84%.10 In the present study, we
reported lower sensitivity and specificity values of 42% and 90% for the same
parameter. When specificity is relaxed to 85%, sensitivity increases to 56%,
but it is still lower than that reported by Mikelberg et al10
and Iester et al.38
Using parameters available from the Nerve Fiber Analyzer 1 scanning
laser polarimeter, Tjon-Fo-Sang et al22 reported
sensitivity and specificity values of 96% and 93%. These values may be high
because of the inclusion of patients with advanced glaucoma likely increasing
the difference in RNFL measurements between patients and normal subjects.
More recently, sensitivity and specificity estimates using the GDx have ranged
from 64% sensitivity and 77% specificity using the GDx number, to 74% sensitivity
and 92% specificity using a linear discriminant function.15
Using the same discriminant function in a similar population, our estimates
of sensitivity and specificity were 49% and 92%. The GDx and HRT linear discriminant
functions were developed on subjects from our center with age, ethnic, and
glaucoma severity characteristics similar to the current study. Therefore,
these linear discriminant functions may perform better in our population than
in others.
Using OCT parameters, estimates of sensitivity and specificity in the
current study were better than those reported for detecting focal defects:
65% and 85%, respectively.1 For comparison
at a similar level of specificity, our best estimates using the inferior temporal
thickness at the 5-o'clock position measurement were higher, with a sensitivity
of 76% and a specificity of 86%. Differences between these values may be attributed
to the possibility that detecting focal defects is more difficult than detecting
glaucoma because of the limited number of data points available with the OCT.
Although information is limited, our stereophotography results have
confirmed those of previous reports that qualitative assessment of photographs
can detect glaucoma at least as well as quantitative techniques.39-40 O'Connor et al39
compared qualitative observer assessment of stereoscopic color disc and monochromatic
nerve fiber layer photographs with quantitative planimetric measurements of
the disc rim area and nerve fiber layer height. They found that the total
proportion of correct diagnoses for the presence or absence of visual field
loss was greatest for the qualitative evaluations of the optic disc (82%)
and nerve fiber layer (74%). Nakla et al40
found that qualitative assessment of stereophotographs could discriminate
between normal and glaucomatous eyes as well as HRT and OCT measurements.
There are several possible explanations for the discrepancies in the
literature in estimates of sensitivity and specificity and ROC areas. Differences
in reported estimates of the discriminating ability between instruments may
be due to differences in the characteristics and severity of glaucoma in the
study population. Not all of the variation in sensitivities and specificities
can, however, be attributed to differences in the severity of glaucoma in
the patients studied. Estimates of the area under the ROC curve for the HRT
parameter cup shape were higher in a study conducted by Uchida et al,30 which included patients with early to moderate glaucoma,
than in one by Iester et al36 that included
some patients with advanced glaucoma (0.93 and 0.81, respectively). In the
present study of patients with early to moderate visual field damage, ROC
area for this parameter was 0.78. Evidently, differences among studies cannot
be attributed to severity of glaucoma alone. Other characteristics such as
the pattern of glaucoma damage, age, and race, as well as differences in image
acquisition and processing, are likely to influence comparison across studies.
Broadway et al37 reported that detection of
glaucoma varied by pattern of damage; the HRT classification was better at
detecting focal ischemic discs (sensitivity = 93%) than senile sclerotic discs
(sensitivity = 67%). By comparing instruments in the same study population,
observed differences are not confounded by differences between study populations.
Limitations of this study include its relatively small sample size and
differences in mean age between the normal and glaucoma groups. Age differences
were accounted for by including age as a variable in the models. We also found
similar results when separately evaluating the areas under the ROC curve in
participants younger and older than 60 years. Because there is no evidence
that one instrument has superior discriminating ability in one age group over
another, the difference in age is likely to affect the discriminating ability
of each instrument in a similar manner. Despite the relatively small sample
size, significant differences in mean parameter measurements between study
groups were found. However, our inability to find significant differences
in the area under the ROC curve for the best parameters of each method may
be partly due to the sample size of this study.
Longitudinal studies are under way to determine whether these instruments
can improve our ability to detect glaucoma and monitor its progression. Detection
of subtle changes in optic disc topography or the RNFL may also be important
for assessing structural end points in clinical trials of neuroprotective
therapies for treating glaucoma.41-42
In conclusion, qualitative assessment of stereophotographs and measurements
from the OCT and HRT generally had greater sensitivities than measurements
from the GDx. However, the area under the ROC curve was similar among the
best parameters from each instrument. This illustrates the importance of considering
area under the ROC curve in relationship to various levels of sensitivity
and specificity. At particular levels of specificity, certain instruments
or parameters may perform better than at other levels.
AUTHOR INFORMATION
Accepted for publication December 1, 2000.
This study was supported in part by grant EY11008 from the National
Institutes of Health (Dr Zangwill), Bethesda, Md, and the Foundation for Eye
Research (Drs Blumenthal and Vasile), Rancho Santa Fe, Calif.
Presented in part at the Annual Association for Research in Vision and
Ophthalmology Meeting, Ft Lauderdale, Fla, May 14, 1999.
Corresponding author and reprints: Linda M. Zangwill, PhD, Glaucoma
Center, Department of Ophthalmology, University of California–San Diego,
La Jolla, CA 92093-0946.
From the Glaucoma Center and Diagnostic Imaging Laboratory, Department
of Ophthalmology (Drs Zangwill, Bowd, Blumenthal, Sánchez-Galeana,
Vasile, and Weinreb and Ms Williams), and the Department of Family and Preventive
Medicine (Dr Berry), University of California–San Diego, La Jolla. None
of the authors had a proprietary interest in any of the products mentioned
in this article at the time the research was completed. J. Williams is now
employed by Heidelberg Engineering.
REFERENCES
| |
1. Pieroth L, Schuman JS, Hertzmark E, et al. Evaluation of focal defects of the nerve fiber layer using optical
coherence tomography. Ophthalmology. 1999;106:570-579.
FULL TEXT
|
ISI
| PUBMED
2. Sommer A, Pollack I, Maumenee AE. Optic disc parameters and onset of glaucomatous field loss. Arch Ophthalmol. 1979;97:1444-1448.
FREE FULL TEXT
3. Sommer A, Miller NR, Pollack I, Maumenee AE, George T. The nerve fiber layer in the diagnosis of glaucoma. Arch Ophthalmol. 1977;95:2149-2156.
FREE FULL TEXT
4. Quigley HA, Addicks EM, Green WR. Optic nerve damage in human glaucoma. Arch Ophthalmol. 1982;100:135-146.
FREE FULL TEXT
5. Sommer A, Katz J, Quigley HA, et al. Clinical detectable nerve fiber atrophy precedes the onset of glaucomatous
field loss. Arch Ophthalmol. 1991;109:77-83.
FREE FULL TEXT
6. Zeyen TG, Caprioli J. Progression of disc and field damage in early glaucoma. Arch Ophthalmol. 1993;111:62-65.
FREE FULL TEXT
7. Pederson JE, Anderson DR. The mode of progressive disc cupping in ocular hypertension and glaucoma. Arch Ophthalmol. 1980;98:490-495.
FREE FULL TEXT
8. Quigley HA, Addicks EM, Green WR, Maumenee AE. Optic nerve damage in human glaucoma. Arch Ophthalmol. 1981;99:635-649.
FREE FULL TEXT
9. Bathija R, Zangwill L, Berry CC, Sample PA, Weinreb RN. Detection of early glaucomatous structural damage with confocal scanning
laser tomography. J Glaucoma. 1998;7:121-127.
ISI
| PUBMED
10. Mikelberg FS, Parfitt CM, Swindale NV, Graham SL, Drance SM, Gosine R. Ability of the Heidelberg Retina Tomograph to detect early glaucomatous
visual field loss. J Glaucoma. 1995;4:242-247.
11. Weinreb RN, Shakiba S, Zangwill L. Scanning laser polarimetry to measure the nerve fiber layer of normal
and glaucomatous eyes. Am J Ophthalmol. 1995;119:627-636.
ISI
| PUBMED
12. Choplin NT, Lundy DC, Dreher AW. Differentiating patients with glaucoma from glaucoma suspects and normal
subjects by nerve fiber layer assessment with scanning laser polarimetry. Ophthalmology. 1998;105:2068-2076.
FULL TEXT
|
ISI
| PUBMED
13. Schuman JS, Hee MR, Puliafito CA, et al. Quantification of nerve fiber layer thickness in normal and glaucomatous
eyes using optical coherence tomography. Arch Ophthalmol. 1995;113:586-596.
FREE FULL TEXT
14. Bowd C, Weinreb RN, Williams JM, Zangwill LM. The retinal nerve fiber layer thickness in ocular hypertensive, normal,
and glaucomatous eyes with optical coherence tomography. Arch Ophthalmol. 2000;118:22-26.
FREE FULL TEXT
15. Weinreb RN, Zangwill LM, Berry CC, Bathija R, Sample PA. Detection of glaucoma with scanning laser polarimetry. Arch Ophthalmol. 1998;116:1583-1590.
FREE FULL TEXT
16. Phelps CE, Hutson A. Estimating diagnostic test accuracy using a "fuzzy gold standard." Med Decis Making. 1995;15:44-57.
FREE FULL TEXT
17. Weinreb RN, Lusky M, Bartsch DU, Morsman D. Effect of repetitive imaging on topographic measurements of the optic
nerve head. Arch Ophthalmol. 1993;111:636-638.
FREE FULL TEXT
18. Mikelberg FS, Wijsman K, Schulzer M. Reproducibility of topographic parameters obtained with the Heidelberg
Retina Tomograph. J Glaucoma. 1993;2:101-103.
19. Wollstein G, Garway-Heath DF, Hitchings RA. Identification of early glaucoma cases with the scanning laser ophthalmoscope. Ophthalmology. 1998;105:1557-1563.
FULL TEXT
|
ISI
| PUBMED
20. Iester M, Swindale NV, Mikelberg FS. Sector-based analysis of optic nerve head shape parameters and visual
field indices in healthy and glaucomatous eyes. J Glaucoma. 1997;6:370-376.
PUBMED
21. Poinoosawmy D, Fontana L, Wu JX, Fitzke FW, Hitchings RA. Variation of nerve fibre thickness measurements with age and ethnicity
by scanning laser polarimetry. Br J Ophthalmol. 1997;81:350-354.
FREE FULL TEXT
22. Tjon-Fo-Sang MJ, Lemij HG. The sensitivity and specificity of nerve fiber layer measurements in
glaucoma as determined with scanning laser polarimetry. Am J Ophthalmol. 1997;123:62-69.
ISI
| PUBMED
23. Zangwill LM, Williams JM, Berry CC, Knauer S, Weinreb RN. Comparison of optical coherence tomography and nerve fiber layer photography
for detection of nerve fiber layer damage in glaucoma. Ophthalmology. 2000;107:1309-1315.
FULL TEXT
|
ISI
| PUBMED
24. Blumenthal E, Williams J, Weinreb R, Berry C, Girkin C, Zangwill L. Reproducibility of nerve fiber layer thickness measurements by use
of optical coherence tomography. Ophthalmology. 2000;107:2278-2282.
FULL TEXT
|
ISI
| PUBMED
25. Schuman JS, Pedut-Kloizman T, Hertzmark E, et al. Reproducibility of nerve fiber layer thickness measurements using optical
coherence tomography. Ophthalmology. 1996;103:1889-1898.
ISI
| PUBMED
26. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating
characteristic curves. Biometrics. 1988;44:837-845.
FULL TEXT
|
ISI
| PUBMED
27. Schuman JS, Hee MR, Arya AV, et al. Optical coherence tomography: a new tool for glaucoma diagnosis. Curr Opin Ophthalmol. 1995;6:89-95.
PUBMED
28. Schuman JS. Optical Coherence Tomography for imaging and quantitation of the nerve
fiber layer thickness. In: Schuman JS, ed. Imaging in Glaucoma.
Thorofare, NJ: Slack Inc; 1996:95-130.
29. Zangwill L, Knauer S, Williams JM, Weinreb RN. Retinal nerve fiber layer assessment by scanning laser polarimetry,
optical coherence tomography and retinal nerve fiber layer photography. In: Lemij HG, Schuman JS, eds. The Shape of Glaucoma,
Quantitative Neural Imaging Techniques. The Hague, the Netherlands:
Kugler Publications; 2000.
30. Uchida H, Brigatti L, Caprioli J. Detection of structural damage from glaucoma with confocal laser image
analysis. Invest Ophthalmol Vis Sci. 1996;37:2393-2401.
FREE FULL TEXT
31. Jonas JB, Muller-Bergh JA, Schlotzer-Schrehardt UM, Naumann GO. Histomorphometry of the human optic nerve. Invest Ophthalmol Vis Sci. 1990;31:736-744.
FREE FULL TEXT
32. Mikelberg FS, Drance SM, Schulzer M, Yidegiligne HM, Weis MM. The normal human optic nerve. Ophthalmology. 1989;96:1325-1328.
ISI
| PUBMED
33. Repka MX, Quigley HA. The effect of age on normal human optic nerve fiber number and diameter. Ophthalmology. 1989;96:26-32.
ISI
| PUBMED
34. Brigatti L, Hoffman D, Caprioli J. Neural networks to identify glaucoma with structural and functional
measurements. Am J Ophthalmol. 1996;121:511-521.
ISI
| PUBMED
35. Caprioli J, Park HJ, Ugurlu S, Hoffman D. Slope of the peripapillary nerve fiber layer surface in glaucoma. Invest Ophthalmol Vis Sci. 1998;39:2321-2328.
FREE FULL TEXT
36. Iester M, Mikelberg FS, Swindale NV, Drance SM. ROC analysis of Heidelberg Retina Tomograph optic disc shape measures
in glaucoma. Can J Ophthalmol. 1997;32:382-388.
ISI
| PUBMED
37. Broadway DC, Drance SM, Parfitt CM, Mikelberg FS. The ability of scanning laser ophthalmoscopy to identify various glaucomatous
optic disk appearances. Am J Ophthalmol. 1998;125:593-604.
FULL TEXT
|
ISI
| PUBMED
38. Iester M, Mikelberg FS, Drance SM. The effect of optic disc size on diagnostic precision with the Heidelberg
retina tomograph. Ophthalmology. 1997;104:545-548.
ISI
| PUBMED
39. O'Connor DJ, Zeyen T, Caprioli J. Comparisons of methods to detect glaucomatous optic nerve damage. Ophthalmology. 1993;100:1498-1503.
ISI
| PUBMED
40. Nakla M, Nduaguba C, Rozier M, Joudeh M, Hoffman D, Caprioli J. Comparison of imaging techniques to detect glaucomatous optic nerve
damage[abstract]. Invest Ophthalmol Vis Sci. 1999;40 (suppl):S397.
41. Weinreb RN, Zangwill LM. Imaging technologies for assessing neuroprotection in glaucomatous
optic neuropathy. Eur J Ophthalmol. 1999;9(suppl 1):S40-S43.
42. Weinreb RN, Levin LA. Is neuroprotection a viable therapy for glaucoma? Arch Ophthalmol. 1999;117:1540-1544.
FREE FULL TEXT
 CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati  Twitter
What's this?
RELATED ARTICLES
Early Detection of Moderate Glaucoma: Redefining Clinical Care in 2001
Paul P. Lee
Arch Ophthalmol. 2001;119(7):1069-1070.
EXTRACT
| FULL TEXT
Archives of Ophthalmology Reader's Choice: Continuing Medical Education
Arch Ophthalmol. 2001;119(7):1092.
FULL TEXT
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
|
Retrobulbar Optic Nerve Diameter Measured by High-Speed Magnetic Resonance Imaging as a Biomarker for Axonal Loss in Glaucomatous Optic Atrophy
Lagreze et al.
IOVS 2009;50:4223-4228.
ABSTRACT
| FULL TEXT
Optic Disc Progression in Glaucoma: Comparison of Confocal Scanning Laser Tomography to Optic Disc Photographs in a Prospective Study
Chauhan et al.
IOVS 2009;50:1682-1691.
ABSTRACT
| FULL TEXT
Corneal biomechanics, thickness and optic disc morphology in children with optic disc tilt
Lim et al.
Br J Ophthalmol 2008;92:1461-1466.
ABSTRACT
| FULL TEXT
An unexpectedly low Stratus optical coherence tomography false-positive rate in the non-nasal quadrants of Asian eyes: indirect evidence of differing retinal nerve fibre layer thickness profiles according to ethnicity
Kim et al.
Br J Ophthalmol 2008;92:735-739.
ABSTRACT
| FULL TEXT
Heidelberg Retina Tomograph 3 machine learning classifiers for glaucoma detection
Townsend et al.
Br J Ophthalmol 2008;92:814-818.
ABSTRACT
| FULL TEXT
Logistic Regression Analysis for Early Glaucoma Diagnosis Using Optical Coherence Tomography
Ferreras et al.
Arch Ophthalmol 2008;126:465-470.
ABSTRACT
| FULL TEXT
Practical recommendations for measuring rates of visual field change in glaucoma
Chauhan et al.
Br J Ophthalmol 2008;92:569-573.
ABSTRACT
| FULL TEXT
Bayesian Machine Learning Classifiers for Combining Structural and Functional Measurements to Classify Healthy and Glaucomatous Eyes
Bowd et al.
IOVS 2008;49:945-953.
ABSTRACT
| FULL TEXT
Impact of Diabetic Retinopathy on Quantitative Retinal Nerve Fiber Layer Measurement and Glaucoma Screening
Takahashi and Chihara
IOVS 2008;49:687-692.
ABSTRACT
| FULL TEXT
The use of the retinal nerve fiber layer thickness measurement in determining the effects of cardiopulmonary bypass procedures on the optic nerve
Buyukates et al.
Perfusion 2007;22:401-406.
ABSTRACT
The Effect of Disc Size and Severity of Disease on the Diagnostic Accuracy of the Heidelberg Retina Tomograph Glaucoma Probability Score
Zangwill et al.
IOVS 2007;48:2653-2660.
ABSTRACT
| FULL TEXT
Scanning Laser Polarimetry with Enhanced Corneal Compensation and Optical Coherence Tomography in Normal and Glaucomatous Eyes
Sehi et al.
IOVS 2007;48:2099-2104.
ABSTRACT
| FULL TEXT
Ability of Stratus OCT to Identify Localized Retinal Nerve Fiber Layer Defects in Patients with Normal Standard Automated Perimetry Results
Kim et al.
IOVS 2007;48:1635-1641.
ABSTRACT
| FULL TEXT
The Effects of Study Design and Spectrum Bias on the Evaluation of Diagnostic Accuracy of Confocal Scanning Laser Ophthalmoscopy in Glaucoma
Medeiros et al.
IOVS 2007;48:214-222.
ABSTRACT
| FULL TEXT
Discrimination between Glaucomatous and Nonglaucomatous Eyes Using Quantitative Imaging Devices and Subjective Optic Nerve Head Assessment.
DeLeon-Ortega et al.
IOVS 2006;47:3374-3380.
ABSTRACT
| FULL TEXT
The quality of reporting of diagnostic accuracy studies in glaucoma using the heidelberg retina tomograph.
Shunmugam and Azuara-Blanco
IOVS 2006;47:2317-2323.
ABSTRACT
| FULL TEXT
Diagnostic Capability of Optical Coherence Tomography in Evaluating the Degree of Glaucomatous Retinal Nerve Fiber Damage
Sihota et al.
IOVS 2006;47:2006-2010.
ABSTRACT
| FULL TEXT
Influence of disease severity and optic disc size on the diagnostic performance of imaging instruments in glaucoma.
Medeiros et al.
IOVS 2006;47:1008-1015.
ABSTRACT
| FULL TEXT
Detection of psychophysical and structural injury in eyes with glaucomatous optic neuropathy and normal standard automated perimetry.
Bagga et al.
Arch Ophthalmol 2006;124:169-176.
ABSTRACT
| FULL TEXT
Development and Comparison of Automated Classifiers for Glaucoma Diagnosis Using Stratus Optical Coherence Tomography
Huang and Chen
IOVS 2005;46:4121-4129.
ABSTRACT
| FULL TEXT
Optical Coherence Tomography Machine Learning Classifiers for Glaucoma Detection: A Preliminary Study
Burgansky-Eliash et al.
IOVS 2005;46:4147-4152.
ABSTRACT
| FULL TEXT
Differences in Visual Function and Optic Nerve Structure Between Healthy Eyes of Blacks and Whites
Racette et al.
Arch Ophthalmol 2005;123:1547-1553.
ABSTRACT
| FULL TEXT
Baseline Topographic Optic Disc Measurements Are Associated With the Development of Primary Open-Angle Glaucoma: The Confocal Scanning Laser Ophthalmoscopy Ancillary Study to the Ocular Hypertension Treatment Study
Zangwill et al.
Arch Ophthalmol 2005;123:1188-1197.
ABSTRACT
| FULL TEXT
Comparability of Retinal Nerve Fiber Layer Thickness Measurements of Optical Coherence Tomography Instruments
Bourne et al.
IOVS 2005;46:1280-1285.
ABSTRACT
| FULL TEXT
Optical Coherence Tomography Longitudinal Evaluation of Retinal Nerve Fiber Layer Thickness in Glaucoma
Wollstein et al.
Arch Ophthalmol 2005;123:464-470.
ABSTRACT
| FULL TEXT
Heidelberg Retina Tomograph Measurements of the Optic Disc and Parapapillary Retina for Detecting Glaucoma Analyzed by Machine Learning Classifiers
Zangwill et al.
IOVS 2004;45:3144-3151.
ABSTRACT
| FULL TEXT
Confocal Scanning Laser Ophthalmoscopy Classifiers and Stereophotograph Evaluation for Prediction of Visual Field Abnormalities in Glaucoma-Suspect Eyes
Bowd et al.
IOVS 2004;45:2255-2262.
ABSTRACT
| FULL TEXT
Comparison of the GDx VCC Scanning Laser Polarimeter, HRT II Confocal Scanning Laser Ophthalmoscope, and Stratus OCT Optical Coherence Tomograph for the Detection of Glaucoma
Medeiros et al.
Arch Ophthalmol 2004;122:827-837.
ABSTRACT
| FULL TEXT
Quantifying Retinal Nerve Fiber Layer Thickness Histologically: A Novel Approach to Sectioning of the Retina
Blumenthal
IOVS 2004;45:1404-1409.
ABSTRACT
| FULL TEXT
Comparison of Scanning Laser Polarimetry Using Variable Corneal Compensation and Retinal Nerve Fiber Layer Photography for Detection of Glaucoma
Medeiros et al.
Arch Ophthalmol 2004;122:698-704.
ABSTRACT
| FULL TEXT
Fourier Analysis of Optical Coherence Tomography and Scanning Laser Polarimetry Retinal Nerve Fiber Layer Measurements in the Diagnosis of Glaucoma
Essock et al.
Arch Ophthalmol 2003;121:1238-1245.
ABSTRACT
| FULL TEXT
Racial Differences in the Association between Optic Disc Topography and Early Glaucoma
Girkin et al.
IOVS 2003;44:3382-3387.
ABSTRACT
| FULL TEXT
Evaluation of Heredity as a Determinant of Retinal Nerve Fiber Layer Thickness as Measured by Optical Coherence Tomography
Hougaard et al.
IOVS 2003;44:3011-3016.
ABSTRACT
| FULL TEXT
Fourier Analysis of Scanning Laser Polarimetry Measurements with Variable Corneal Compensation in Glaucoma
Medeiros et al.
IOVS 2003;44:2606-2612.
ABSTRACT
| FULL TEXT
Comparison of algorithms for detection of localised nerve fibre layer defects using scanning laser polarimetry
Medeiros and Susanna
Br J Ophthalmol 2003;87:413-419.
ABSTRACT
| FULL TEXT
Acutance, an objective measure of retinal nerve fibre image clarity
Choong et al.
Br J Ophthalmol 2003;87:322-326.
ABSTRACT
| FULL TEXT
Glaucoma Detection Using Scanning Laser Polarimetry With Variable Corneal Polarization Compensation
Weinreb et al.
Arch Ophthalmol 2003;121:218-224.
ABSTRACT
| FULL TEXT
Macular Thickness Changes in Glaucomatous Optic Neuropathy Detected Using Optical Coherence Tomography
Greenfield et al.
Arch Ophthalmol 2003;121:41-46.
ABSTRACT
| FULL TEXT
Comparing Neural Networks and Linear Discriminant Functions for Glaucoma Detection Using Confocal Scanning Laser Ophthalmoscopy of the Optic Disc
Bowd et al.
IOVS 2002;43:3444-3454.
ABSTRACT
| FULL TEXT
A few remarks about glaucoma
Wegner
Br J Ophthalmol 2002;86:836-837.
FULL TEXT
Measurement of the Magnitude and Axis of Corneal Polarization With Scanning Laser Polarimetry
Weinreb et al.
Arch Ophthalmol 2002;120:901-906.
ABSTRACT
| FULL TEXT
Optic disc cup slope and visual field indices in normal, ocular hypertensive and early glaucomatous eyes
Cullinane et al.
Br J Ophthalmol 2002;86:555-559.
ABSTRACT
| FULL TEXT
Early Detection of Moderate Glaucoma: Redefining Clinical Care in 2001
Lee
Arch Ophthalmol 2001;119:1069-1070.
FULL TEXT
|
