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Optic nerve and retinal nerve fiber layer analyzers
in glaucoma
David S. Greenfield, MD
There is mounting evidence that retinal nerve fiber layer(RNFL) loss precedes detectable visual field loss in earlyglaucomatous optic neuropathy. However, examination andphotography of the RNFL is a difficult technique in manypatients, particularly older individuals, and eyes with smallpupils and media opacities. It is subjective, qualitative, variablyreproducible, and often unreliable. Furthermore, optic nervehead and RNFL photography is time consuming, operatordependent, has limited sensitivity and specificity, and requiresstorage space. Imaging technologies have emerged whichenable clinicians to perform accurate, objective, andquantitative measurements of the RNFL and optic nerve headtopography. There is good agreement between suchmeasurements and clinical estimates of optic nerve headstructure and visual function. The reproducibility of theseinstruments suggests that they have the potential to detectstructural change over time. This report will review thetechnological principles, reproducibility, sensitivity andspecificity, capacity to detect glaucomatous progression,and limitations of currently available ocular imagingtechnologies. Curr Opin Ophthalmol 2002, 13:68–76 © 2002 Lippincott
Williams & Wilkins, Inc.
Glaucoma is an optic neuropathy characterized by a typi-
cal pattern of visual field loss and optic nerve damage
resulting from retinal ganglion cell death caused by a
number of different disorders that affect the eye. Most,
but not all, of these disorders are associated with el-
evated intraocular pressure (IOP), which is the most im-
portant risk factor for glaucomatous damage. Although
clinical examination of the optic nerve head has been
considered to be the most sensitive test for detecting
glaucomatous damage, evidence suggests that examina-
tion of the retinal nerve fiber layer (RNFL) may provide
important diagnostic information [1-4]. Accurate and ob-
jective methods of detecting disc and RNFL abnormali-
ties, and their progression, would facilitate the diagnosis
and monitoring of glaucomatous optic neuropathy.
Clinical examination and photography of the RNFL is a
difficult technique in many patients, particularly older
individuals, those with small pupils, and subjects with
media opacities. It is subjective, qualitative, variably re-
producible, and often unreliable. In addition, optic nerve
head and RNFL photography is time consuming, opera-
tor dependent, has limited sensitivity and specificity,
and requires storage space. Recently, new technologies
have emerged which enable clinicians to perform accu-
rate, reproducible, objective, and quantitative measure-
ments of the retinal nerve fiber layer and optic nerve
head topography.
Confocal scanning laser ophthalmoscopy (CSLO), a
technology embodied in the Heidelberg Retinal
Tomograph (HRT, Heidelberg Engineering, Heidel-
berg, Germany), enables the operator to evaluate three-
dimensional characteristics of optic nerve head topogra-
phy quantitatively [5-8]. Thirty-two coronal sections of
the optic nerve head are acquired over a depth of ap-
proximately 3.5 millimeters, and a color-coded topo-
graphic map of the optic nerve head is generated.
Scanning laser polarimetry (SLP) is a technology embod-
ied in the GDx Nerve Fiber Analyzer (Laser Diagnostic
Technologies, Inc., San Diego, CA) employs a confocal
scanning laser ophthalmoscope and an integrated polar-
imeter. It evaluates the thickness of the RNFL by uti-
lizing the birefringent properties of the retinal ganglion
cell axons [9,10]. As polarized light passes through the
RNFL and is reflected back from the deeper layer, it
undergoes a phase shift. The change in polarization, re-
The Department of Ophthalmology, The University of Miami School of Medicine,Bascom Palmer Eye Institute, Miami, Florida, USA.
Correspondence to David S. Greenfield, MD, Bascom Palmer Eye Institute, 7108Fairway Drive, Suite 340, Palm Beach Gardens, FL, 33418; e-mail:dgreenfield@med.miami.edu
Current Opinion in Ophthalmology 2002, 13:68–76
Abbreviations
CSLO confocal scanning laser ophthalmoscopyHRT Heidelberg Retinal TomographIOP intraocular pressureOCT optical coherence tomographyRNFL retinal nerve fiber layerSLP scanning laser polarimetry
ISSN 1040–8738 © 2002 Lippincott Williams & Wilkins, Inc.
68
ferred to as retardation, is proportional to the thickness of
the birefringent medium, and is measured to give an
index of RNFL thickness.
Optical coherence tomography (OCT, Zeiss-Humphrey
Systems, Dublin, CA) is a noninvasive, noncontact,
transpupillary imaging technology that can image retinal
structures in vivo with a resolution of 10 to 17 microns
[11,12]. Cross-sectional images of the retina are produced
using the optical backscattering of light in a fashion
analogous to B-scan ultrasonography. The anatomic lay-
ers within the retina can be differentiated and retinal
thickness can be measured [13].
This report will review practical applications and prin-
ciples underlying these posterior segment-imaging tech-
nologies with emphasis upon strengths and limitations of
each technology.
Confocal scanning laser ophthalmoscopyTechnological principles
Confocal scanning laser ophthalmoscopy employs a 670 nm
diode laser beam as a light source and scans the retina in
x- and y- directions [14,15]. Light originating from the
illuminated area passes through a diaphragm (pinhole) in
a plane optically conjugate to the retina. Planes unfo-
cused at the aperture are blocked by the diaphragm and
do not reach the detector. Each image contains 256 x 256
pixels (picture-elements); each pixel represents the reti-
nal height at that location relative to the focal plane of
the eye. Image acquisition and processing takes approxi-
mately 1.6 seconds. Thirty-two coronal sections are ob-
tained progressing from anterior to the optic nerve head
through the retrolaminar portion of the nerve head. The
axial distance between two adjacent sections is 50 to
75 m generating an axial range of 1.5 to 3.5 mm.
A standard reference plane is established parallel to the
peripapillary retinal surface and is located 50 microns
posterior to the retinal surface along a circle concentric
with the optic disc margin in a temporal segment be-
tween 350° and 356°. Neural rim is defined as tissue
within the optic disc margin and above the reference
plane. Optic cup is defined as tissue within the disc
margin and below the reference plane.
The optic disc margin is outlined and a color-coded
depth map is created from a mean topographic image
using a software algorithm (Fig. 1). Stereometric param-
eters of optic nerve head topography are generated rela-
tive to the reference plane including rim area and vol-
ume, cup area and volume, cup-disc area ratio, mean
retinal nerve fiber layer thickness, and retinal nerve fiber
cross-sectional area. Parameters independent of the ref-
erence plane include mean and maximum cup depth,
height variation contour, and cup-shape measure. A nor-
mal retinal height variation diagram demonstrates a
“double-hump” pattern corresponding to the thicker
retinal ganglion cell axons along the superior and inferior
portions of the optic nerve head.
Reproducibility
Various investigators have reported high levels of repro-
ducibility using this technology [5,15,16] Brigatti et al. [7]
found that topographic variability correlated with the
steepness of the corresponding region. Greater variabil-
ity was found at the edge of the optic disc cup and along
blood vessels. Weinreb et al. [14] have determined that
measurement reproducibility is improved from 35.5 µm
to 25.7 µm when a series of three examinations are ob-
tained instead of a single image analysis. Based upon
these data, acquiring three images per eye and creation
of a mean topographic image is recommended. Finally,
Zangwill et al. [17] have shown that image reproducibil-
ity is improved with pupillary dilation, particularly in
eyes with small pupils and cataract.
Sensitivity and specificity
Various investigators have reported topographic differ-
ences between normal, ocular hypertensive, and glauco-
matous eyes. It is essential to emphasize that the char-
acteristics of the study population will influence the
discriminating power involved in differentiating glauco-
matous from nonglaucomatous eyes. Determination of
sensitivity and specificity parameters is fundamentally
linked to the severity of glaucomatous damage among
the cohort studied. For any given technology, an instru-
ment will appear to be more sensitive if it is used to
separate eyes with advanced glaucoma from normal sub-
jects compared with eyes with mild glaucoma.
Heidelberg Retinal Tomograph employs software with
various statistical analyses to discriminate normal from
Figure 1. Confocal scanning laser ophthalmoscopy
topographic map
A patient with moderate normal-tension glaucoma shows loss of the inferiorneuroretinal rim (green) and associated stereometric parameters. There is a focaldepression in the double-hump pattern of the height variation diagramcorresponding to the decreased inferotemporal quadrant height (below).
Optic nerve and retinal nerve fiber layer analyzers in glaucoma Greenfield 69
abnormal optic discs. These include a multivariate dis-
criminant analysis based upon rim volume, height varia-
tion contour, and cup shape measure adjusted by age
[18], ranked-segment distribution curves [19,20], and re-
gression analysis using a normative database of 80 normal
eyes from 80 white subjects with a mean age of 57 years
[21]. The confidence interval limits derived from the
later are used commercially to generate the Moorfield’s
Regression Classification Score (normal, borderline, or
outside normal limits). Wollstein et al. [21] reported a
84.3% sensitivity and a 96.3% specificity for separating
normal and early glaucomatous eyes by taking into ac-
count the relation between optic disc size and the rim
area or cup-to-disc area ratio. In a different study, Woll-
stein et al. [22•] determined that by taking into account
the optic disc size, HRT image analysis was superior in
sensitivity (84.3%) for detection of early glaucoma com-
pared with expert assessment of stereoscopic optic disc
photographs (70.6%).
The sensitivity and specificity of various HRT param-
eters has been investigated and varies widely ranging
from 62% to 94% and 74% to 96%, respectively [18,23–
27]. Wide variability in discriminating power may be ex-
plained in part by variable sample size, definitions of
glaucoma, and varying degrees of glaucomatous optic
nerve damage. A recent study by Miglior et al. [28•]
found fair to poor agreement (� statistic 0.28-0.48) be-
tween visual field examinations and HRT classifications
among a population of 359 eyes (55 normal, 209 with
OHT, and 95 with moderate POAG, average visual field
mean defect –7.6 dB) The sensitivity and specificity of
the HRT examination were, respectively, 80% and 65%,
using the Mikelberg multivariate discriminant analysis
[18], and 31 to 53% and 90 to 92%, using ranked-segment
distribution curve analysis [19,20].
Using various HRT summary data including the reflec-
tance image, double-hump graph, stereometric analyses,
and HRT classification using a multivariate discriminant
function [18] and ranked segment analysis [19,20],
Sanchez-Galeana [29•] evaluated the sensitivity and
specificity for discriminating between 50 normal eyes
and 39 eyes with early to moderate glaucoma (average
visual field mean defect –5 dB). Masked observers were
used to generate an HRT classification (normal, glauco-
matous, or undetermined) and similar classifications
were generated using other imaging technologies (see
below). Using these summary data collectively, investi-
gators reported a sensitivity and specificity for the HRT
ranging from 64 to 75% and 68 to 80%, respectively.
Detection of progression
Essential elements for change detection algorithms have
been previously reviewed [30]. An accepted gold stan-
dard must exist for establishing change. Surrogate mea-
surement parameters are necessary with little biological
variability and relevance in the course of the disease.
High instrument reproducibility is essential with known
limits of variability in normals and persons with disease.
Statistical criteria must be established for differentiating
biological change from test-retest variability. Finally,
multicenter prospective validation must be established
with comparisons against an accepted gold standard.
Confocal scanning laser ophthalmoscopy strategies for
change detection exist including serial analyses of global
and regional topographic indices (eg, cup-disc ratio, cup
volume, and cup-shape measure), and color-coded
(red/green) significance indicators of change relative to
baseline. Chauhan et al. [31••] have described a sophis-
ticated change analysis algorithm based upon a probabi-
listic approach using variability estimates that employs
clusters of 4 x 4 pixels to create superpixels. Three fol-
low-up images are compared with a baseline image, and
a change-probability map is created, characterized by ar-
eas with significant progression illustrated in red.
Strengths of this algorithm include the potential ability
to differentiate biological change from test-retest vari-
ability, however it has not been validated in prospective
clinical trials. Moreover, topographic measurements are
dependent upon intraocular pressure and postoperative
and diurnal changes in IOP have been reported to pro-
duce changes in optic disc topography thereby confound-
ing detection of progression.
Two reports have described HRT detection of change.
Chauhan et al. [31••] described significant topographic
change in one patient with progressive glaucomatous op-
tic disc cupping. Kamal et al. [32] reported topographic
disc changes in a cohort of thirteen ocular hyperten-
sive subjects converting to glaucoma before confirmed
visual changes. This study was limited, however, by
small sample size, reviewers unmasked to diagnosis,
absence of a control arm of OHT non-converters, and
inability to differentiate biological change from test-
retest variability.
LimitationsTechnological limitations exist which limit the discrimi-
nating power for disease detection. The use of a standard
reference plane and need for correct placement of the
disc margin by the operator can influence many of the
topographic outcome variables generated. Moreover,
considerable variability in optic disc morphology exists
among normal eyes. As currently configured, software
algorithms designed to classify subjects as normal or
glaucomatous are based upon dedicated normative data
of approximately 100 eyes which is insufficient for popu-
lation based screening. A uniform consensus regarding
the most appropriate summary measures remains to
be established.
There is evidence that disc topography is dependent
upon intraocular pressure [33] and cardiac pulsation [34].
70 Glaucoma
Postoperative [35,36 ] and diurnal [37] changes in IOP
may produce changes in optic disc topography thereby
confounding detection of glaucomatous progression. In
addition, CSLO cannot discern vessel shift or other non-
quantitative features (eg, pallor or disc hemorrhage)
often associated with progression. Finally, as with perim-
etry, short and long-term fluctuation exists and confi-
dence intervals need to be validated to interpret mea-
surements obtained.
Scanning laser polarimetryTechnological principles
Scanning laser polarimetry (SLP) is a technology that
provides quantitative assessment of the peripapillary
RNFL using a polarized diode laser light source (780
nm). The parallel arrangement of neurotubules within
the RNFL produces linear birefringence. Thus, changes
in the polarization state may be measured when light
passes through such tissue [9,10,38-40]. The change in
polarization of the scanning beam (retardation) is linearly
correlated to the thickness of the polarizing medium, and
is computed to give an index of RNFL thickness. A
polarization detection unit measures the retardation of
light emerging from the eye; 256 by 256 pixels (65,536)
are acquired in 0.7 seconds and a computer algorithm
calculates retardation at each retinal position.
An anterior segment compensator is incorporated within
the technology to neutralize the polarization effects of
the cornea and crystalline lens. It consists of a fixed re-
tarder to adjust for the corneal retardation and assumes
all individuals have a slow axis of corneal birefringence
15 degrees nasally downward and a magnitude of 60 nm
[41,42 ]. Recent studies have demonstrated that the mag-
nitude [43] and axis [44] of corneal polarization are vari-
able, and are strongly correlated with RNFL thickness
assessments obtained with SLP.
At least three images are acquired using a field of view of
15 x 15 degrees and a baseline retardation map is created.
Images may be obtained through an undilated pupil with
a minimum diameter of 2 mm. However, uniformity in
pupil size is essential when longitudinally evaluating
RNFL measurements.[45] The probability of obtaining
a satisfactory baseline image (mean pixel SD </= 8 µm)
improves from 62 to 98% if the number of scans available
for selection is increased from three to five.[40] The
retardation map represents a false color image with areas
of high retardation displayed in yellow and white, and
areas of low retardation displayed in blue (Fig. 2).
The operator outlines the optic disc margin, and a ten-
pixel-wide measurement ellipse is automatically gener-
ated, 1.75x greater than the disc diameter. A computer
algorithm automatically generates retardation mea-
surements throughout the peripapillary region and along
the measurement ellipse. Average quadrantic measure-
ments, measurement ratios (eg, superior/nasal,
superior/temporal), symmetry measurements between
superior and inferior quadrants, and modulation param-
eters (an indication of the difference between the thick-
est and thinnest parts of the RNFL) are generated. A
neural network number is also calculated which is
thought to reflect the likelihood of glaucoma on a scale of
0 to 100.
Reproducibility
Intraoperator measurement reproducibility has been
shown by Weinreb et al. [10] (mean coefficient of varia-
tion (CV) of 4.5%) and Chi et al. [46] (CV ranging from
3.59–10.20% for both normal and glaucomatous sub-
jects). Swanson et al. [47] found significant interoperator
variability with the NFA I, among 4 operators all of
whom only scanned each of the 11 subjects twice. The
primary source of error was attributed to the variability in
the criterion used for establishing intensity setting. This
problem was subsequently reduced in the NFA II with a
hardware modification to the light system.
Retinal nerve fiber layer thickness measurements using
the NFA II have been reported to have high levels of
measurement reproducibility [40,48]. Hoh et al. [40] de-
scribed excellent intraoperator reproducibility and found
that variability between operators can be minimized by
using a single measurement ellipse acquired from the
original baseline image. As investigators have reported
high levels of measurement variability adjacent to retinal
blood vessels [49,50], an automated blood vessel removal
algorithm has been incorporated in the third generation
device, GDx.
Sensitivity and specificity
As described with CSLO, there is a wide range in RNFL
thickness values among normal individuals and consid-
erable measurement overlap between normal and glau-
comatous eyes may exist. Determination of sensitivity
and specificity parameters is fundamentally linked to the
Figure 2. Scanning laser polarimetry image
A patient with moderate primary open-angle glaucoma shows reducedretardation within the superior arcuate retinal nerve fiber layer bundle. Tworetardation parameters were classified as abnormal (outside 95% confidencelimits, illustrated in red) and four parameters were classified as borderline(outside 90% confidence limits, illustrated in yellow).
Optic nerve and retinal nerve fiber layer analyzers in glaucoma Greenfield 71
severity of glaucomatous damage among the cohort stud-
ied [24]. Sensitivity and specificity values will be greater
in studies involving eyes with advanced glaucoma than
in studies involving eyes with mild to moderate glau-
coma. Tjon-Fo-Song and Lemij [38] evaluated the sen-
sitivity and specificity of the first generation device,
NFA I, for detecting glaucoma among a diverse group of
200 eyes with early to advanced glaucoma (average visual
field mean deviation –10.33 decibels) compared with a
normal population. The sensitivity and specificity was
reported to be 96 and 93%, respectively. Weinreb et al.[51] reported a sensitivity of 74% and specificity of 92%
using a newer version of SLP with a linear discriminant
function to label glaucomatous damage among a popula-
tion with early to moderate glaucoma. Garcia-Sánchez
et al. [52] found the sensitivity and specificity of the GDx
to be 78% and 86%, respectively. The most sensitive and
specific parameters in their study were ellipse modula-
tion, superior/nasal ratio, and maximum modulation.
In a cross-sectional study comparing OCT and SLP, Hoh
et al. [53] found that structural information generated
from both technologies was significantly correlated with
visual function in glaucomatous eyes (average visual field
mean deviation –7.7 decibels). However, retardation pa-
rameters providing summary measures of RNFL thick-
ness (eg, average thickness and integral measurements)
had a weaker correlation with visual field mean defect
(R = 0.17 to 0.27) than with constructed retardation pa-
rameters (eg, modulation scores, ratio parameters, and
number; R = 0.36 to –0.51). Bowd et al. [54] recently
reported that constructed SLP parameters (modulation,
ratio, number, and linear discriminant function values)
have the greatest discriminating power. This is ex-
plained by recent evidence [44] suggesting that interin-
dividual variability in corneal birefringence has falsely
broadened the normative database of RNFL thick-
ness assessments, and reduced the sensitivity and speci-
ficity of this technology. Correction for corneal polariza-
tion axis has been shown to significantly increase
the correlation between RNFL structural damage and
visual function, and significantly improve the discri-
minating power of SLP for detection of mild to moder-
ate glaucoma.
Garcia-Sanchez et al. [29] evaluated the sensitivity and
specificity of the HRT, GDx, and OCT summary data for
detection of early to moderate glaucoma (average visual
field mean defect –5.0 dB) among three masked reviewers
(see Table 1). For the GDx, sensitivity and specificity
ranged from 72 to 82% and 56 to 82%, respectively.
Detection of progression
Scanning laser polarimetry strategies for change detec-
tion exist including evaluation of change in absolute val-
ues of retardation measurements, change in quadrantic
RNFL thickness measurements, change in double-
hump RNFL thickness profile, and color-coded map of
RNFL thickness change relative to baseline. However,
as with OCT, statistical units of change probability are
absent limiting the ability to differentiate change from
measurement variability, and there has been no prospec-
tive validation of this algorithm
Two published reports have described SLP evidence of
change detection in eyes with non-glaucomatous optic
neuropathy. Colen et al. [55] described a patient with
acute nonarteritic anterior ischemic optic neuropathy
who developed progressive loss of retardation over a
5-week period corresponding to a dense altitudinal visual
field depression. Medeiros and Susanna [56] reported
progressive RNFL loss over a 90-day period in a patient
with traumatic optic neuropathy.
Limitations
Employment of a fixed corneal compensator has pro-
duced considerable measurement overlap among normal
and glaucomatous eyes. Variability in corneal polariza-
tion axis (CPA) [57••] and magnitude has been de-
Table 1. Comparison of scanning laser ophthalmoscopy, scanning laser polarimetry, and optical coherence tomography
GDx HRT OCT
Technological principle Birefringence SLO InterferometryPixels 65,000 65,000 50,000Pupillary dilation No No YesReproducibility (CV) 5%–10% [40] 5%–10% [67] 5%–10% [63]Parameters measured Peripapillary RNFL Optic Disc Topography Peripapillary RNFLNormative database 1200 eyes [68] 45, [19] 100 [19] or 112 [21] eyes 150 eyes*Sensitivity [29] 72%–82% 64%–75% 76%–79%Specificity [29] 56%–82% 68%–80% 68%–81%Change detection algorithm Yes Yes YesChange probability algorithm No Yes NoProspective validation of algorithm No No NoEvidence to detect change Yes [55, 56] Yes [31, 32] NoLimitations Fixed corneal compensator;
unable to differentiatevariability from progression
Universal reference plane;topography is dependentupon IOP
Sampling data limited to 100A-scans; unable to differentiatevariability fromprogression
SLO, scanning laser ophthalmoscopy; CV, coefficient of variation.*Personal communication (Zeiss-Humphrey Systems, Dublin, CA).
72 Glaucoma
scribed; there is evidence that CPA strongly effects peri-
papillary retardation measurements (Fig. 3).
Although, there is good one-year stability of CPA mea-
surements [58], long-term stability and the effect of in-
traocular and refractive surgery upon such measurements
remains unknown. Furthermore, anterior and posterior
segment pathology may produce spurious RNFL mea-
surements [59], and caution should be used when inter-
preting images in eyes with ocular surface disease, pre-
vious keratorefractive surgery, media opacification, and
extensive peripapillary atrophy.
Although a change analysis algorithm exists, statistical
units of probability are absent. Thus, biological change
cannot be differentiated from measurement variability.
Finally, prospective studies are necessary to validate
change analysis strategies.
Optical coherence tomographyTechnological principles
Optical coherence tomography (OCT, Zeiss-Humphrey
Systems, Inc., Dublin, CA) is a noninvasive, noncontact,
transpupillary imaging technology which can image reti-
nal structures in vivo with a resolution of 10 to 17 microns
[11,12]. Cross-sectional images of the retina are produced
using the optical backscattering of light in a fashion
analogous to B-scan ultrasonography. The anatomic lay-
ers within the retina can be differentiated and retinal
thickness can be measured [13].
Optical coherence tomography images are obtained us-
ing a transpupillary delivery of low coherence near-
infrared light (850nm) from a super-luminescent diode
laser [11–13,60]. Backscatter from the retina is captured
using the same delivery optics and resolved using a fiber-
optic interferometer set in a standard Michelson con-
figuration. Modulating the reference arm allows longitu-
dinal information to be extracted to the resolution as
defined by the low coherence super-luminescent diode.
Cross-sectional OCT images of the retina are con-
structed from the backscattering information provided
by 100 individual longitudinal A-scans. A digitized,
composite image of the 100 A-scans is produced on a
monitor with a false color scale representing the degree
of light backscattering from tissues at different depths
within the retina.
A minimum pupillary diameter of 5 mm is required to
obtain satisfactory OCT image quality. Images may be
acquired using either a linear or circular scanning beam.
Scanning acquisition time is approximately one second.
A circular scan of the RNFL is generally performed with
a diameter of 3.4 mm (Fig. 4) to avoid areas of peri-
papillary atrophy. Circular scans of this diameter contain
100 axial scans spaced 110 microns apart. This scan is
then converted into a radial image by an automated
“smoothing” technique. A computer algorithm identifies
and demarcates the signal corresponding to the RNFL,
and mean quadrantic and individual clock hours of
RNFL thickness measurements are calculated.
Reproducibility
Schuman et al. [61] evaluated the reproducibility of reti-
nal and RNFL thickness measurements using circular
scans around the optic nerve head in normal and glau-
comatous eyes. Scan diameters of 2.9, 3.4, and 4.5 mm
were evaluated and internal fixation was compared with
external fixation. Measurement SDs were approximately
10 to 20 µm for overall RNFL thickness, and 5 to 9 µm
for retinal thickness. The authors found a circle diameter
of 3.4 mm to be superior; internal fixation was signifi-
cantly less variable than external fixation. Baumann et al.[62] found that the mean coefficient of varation of retinal
thickness measurements at locations outside of 500 µm
from fixation in normal eyes was 10%. The authors used
an OCT prototype characterized by a 2.5 second scan
acquisition time. Recently, Blumenthal et al. [63] evalu-
ated the CV for mean RNFL thickness in normal and
glaucomatous eyes (6.9% and 11.8% respectively) using a
Figure 3. Peripapillary retinal nerve fiber layer retardation map
and thickness plot
Peripapillary retinal nerve fiber layer (RNFL) retardation map (A) andcorresponding RNFL thickness plot (B) in the right eyes of six normal individualswith different corneal polarization axis values (18°, 27°, 37°, 52°, 59°, 76° nasallydownward from top left to bottom right). Upper and lower margins in (B)represent 95% confidence intervals. Note that peripapillary retardation andmeasured RNFL thickness increase with increasing corneal polarization axis.(Reprinted with permission: Greenfield DS, Knighton RW: Stability of cornealpolarization axis measurements for scanning laser polarimetry. Ophthalmology2001, 108:1065–1069. Figure 3).
Optic nerve and retinal nerve fiber layer analyzers in glaucoma Greenfield 73
commercially available device capable of performing
scan acquisition times in one second.
Published series of peripapillary retinal nerve fiber layer
measurement using optical coherence tomography have
sampled 100 evenly-distributed points on a 360 degree
peripapillary circular scan. Ozden et al. [64] evaluated
whether a four-fold increase in sampling density im-
proves the reproducibility of OCT measurement.
Twenty-two eyes of 22 patients (normal subjects, 3 eyes;
ocular hypertension, 2 eyes; glaucoma, 17 eyes) were
evaluated. Optical coherence tomography scanning con-
sisted of three superior and inferior quadrantic scans
(100 sampling points/ quadrant) and three circular scans
(25 points/quadrant). Retinal nerve fiber layer thickness
measurements and CV were calculated for the superior
and inferior quadrants for each sampling density tech-
nique. Normal eyes showed no difference between the
25 point/quadrant and 100 point/quadrant scans, respec-
tively. Among glaucomatous eyes, however, the CV in
25-point/quadrant scans (25.9%) was significantly higher
than that in 100-point/quadrant scans (11.9%, p = 0.01).
Sensitivity and specificity
Cross-sectional studies have compared OCT with CSLO
[65] and SLP [53] in normal, ocular hypertensive, and
glaucomatous eyes. OCT was capable of differentiating
glaucomatous from non-glaucomatous eyes, and RNFL
thickness measurements using OCT correlated with re-
tardation measurements using SLP and topographic
measurements using CSLO.
Bowd et al. [54] compared the discriminating powers of
SLP, OCT, short-wavelength automated perimetry
(SWAP), frequency-doubling technology perimetry
(FDT) for detection of early glaucoma (average visual
field mean defect –4.0 dB). The largest area under the
receiver operator characteristic (ROC) curve was found
for OCT inferior quadrant thickness, followed by the
FDT number of total deviation plot points </= 5%, SLP
linear discriminant function, and SWAP pattern SD.
Zangwill et al. [66• ] compared the ability of OCT, HRT,
and GDx to discriminate between normal eyes and eyes
with early to moderate glaucomatous visual field loss. No
significant differences were found between area under
the ROC curve and the best parameter from each instru-
ment: OCT inferior RNFL thickness, HRT mean height
contour in the inferior nasal position, and GDx linear
discriminant function).
Garcia-Sanchez et al. [29] evaluated the sensitivity and
specificity of the HRT, GDx, and OCT summary
data for detection of early to moderate glaucoma (aver-
age visual field mean defect –5.0 dB) among three
masked reviewers (see Table 1). For the OCT, sensi-
tivity and specificity ranged from 76 to 79% and 68 to
81%, respectively.
Detection of progression
Change analysis software has only recently been intro-
duced; therefore no reports have described longitudinal
change in patients with disease progression. As presently
configured, this algorithm generates a serial analysis of
RNFL thickness measurements among two OCT im-
ages, however statistical units of change probability are
not provided. Thus, true biological change cannot be
differentiated from test-retest variability.
Limitations
Currently, no statistical units of change probability are
absent from the change analysis software, therefore one
cannot differentiate biological change from measure-
ment variability by performing serial analysis of abso-
lute RNFL thickness values. Pupillary dilation is re-
quired to obtain acceptable peripapillary measurement
scans. Finally, sampling is limited to 25 A-scans per
quadrant, which may limit the ability to detect localized
change [64].
ConclusionsRecent advances in ocular imaging technology provide a
means to obtain accurate, objective, quantitative, and
reproducible structural measurements of optic disc to-
pography and RNFL thickness. Current imaging sys-
tems can differentiate between normal eyes and eyes
with mild to moderate glaucomatous optic neuropathy.
Although conflicting data exists, sensitivity and specific-
ity values approximate 70 to 80% depending upon
sample size, definition of glaucoma, and severity of glau-
comatous damage. Any one technology will have limited
usefulness as a single test to diagnose glaucoma and at
the present juncture should not be used as an indepen-
dent diagnostic screening test. However, these instru-
Figure 4. Optical coherence tomography image of a normal
eye obtained using a 3.4 mm peripapillary measurement scan
The anterior and posterior limits of the retinal nerve fiber layer (RNFL) aredemarcated using a computer algorithm (arrows) and clock hour and quadranticRNFL thickness measurements are obtained.
74 Glaucoma
ments have considerable potential for use as adjunctive
measures of glaucomatous damage along with careful
clinical and perimetric examination.
There is no uniform agreement regarding the most ap-
propriate technology for the evaluation of structural
damage in eyes with glaucomatous optic neuropathy.
Furthermore, among proponents of any given technol-
ogy, there is no consensus on the most appropriate sum-
mary measure to represent ganglion cell loss. It is im-
portant to recognize that the parameter or technology
most useful in the detection of glaucomatous damage
may vary from individual to individual and may differ
from the parameter or technology most useful for de-
tection of glaucomatous change. The most appropriate
measure(s) of disease detection will unlikely be the
most sensitive indicator of glaucomatous change. At
the present time, limited information exists regarding
the relation between glaucomatous progression and
RNFL/topographic measures.
Currently available imaging technologies hold consider-
able promise for detection of glaucomatous change.
Methods for change detection exist but have not been
prospectively validated in large populations. Moreover,
new strategies for detection of progressive structural
change need to be validated against accepted measures
of structural (stereoscopic disc photography) and func-
tional (psychophysical) change. Statistical units of
change probability are essential to differentiate true bio-
logical change from variability (eg, microsaccades during
fixation, vessel pulsations, instrument or operator-
induced variability). A significant challenge to the inves-
tigator has been the reality that technology improves
with time. Rapidly evolving hardware and software re-
sults in alteration of baseline measurements. This has
produced instability in longitudinal data collection and
has limited, in part, our ability to critically evaluate the
efficacy of these instruments to detect structural change
over time. Presently, it is unclear whether automated
detection of structural change meets or exceeds current
standard of care measures.
In summary, each ocular imaging technology has specific
advantages and disadvantages. One instrument may not
be best for all purposes and all patients, and different
analysis strategies may not agree. Because measure-
ment reproducibility is high, each technology holds
promise for improving our ability to detect glaucoma-
tous change. As with perimetry, it is not recommended
that isolated clinical decisions be based solely upon
ocular imaging results. Clinical correlation should be
performed and treatment recommendations should
be individualized.
Acknowledgments
Supported in part by the New York Community Trust, New York, New York; TheKessel Foundation, Bergenfield, New Jersey; The Boyer Foundation, Melbourne,FL; and NIH Grant R01-EY08684, Bethesda, Maryland. The author has no propri-etary interest in any of the products or techniques described in this manuscript.
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76 Glaucoma
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