| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
From the Bascom Palmer Eye Institute, University of Miami School of Medicine, Miami, Florida.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionConclusionsReferences |
|---|
METHODS. The Mueller calculus was used to model the polarization optics of SLP. A birefringent retinal structure (RNFL or macula) was represented as a circularly symmetric linear retarder with a radial slow axis. The birefringent cornea and a corneal compensator within the SLP instrument were represented as fixed linear retarders. The model provided images of the radial retarder that were compared with retardance images obtained by SLP of the macula in eight normal subjects. Theoretical and experimental images were quantified with circular profiles around the center of the radial retarder or macula. Experimental retardance profiles were varied by tilting the subject’s head to rotate the corneal axis. The SLP model was fit to the experimental profiles by nonlinear least-squares curve fitting.
RESULTS. The combined retarder formed by the cornea and corneal compensator induced bow-tie patterns in images of the radial retarder. Macular SLP images exhibited similar patterns. Retardance profiles could be characterized by three parameters: modulation, mean, and axis. The SLP model fit the experimental profiles very well (r2 = 0.8–0.9).
CONCLUSIONS. The SLP model provided a quantitative framework within which to interpret SLP studies. Modulation-based parameters were generally more sensitive to retinal birefringence than mean-based parameters. Corneal birefringence is an important source of variance in SLP, especially for mean-based parameters. The theory developed for this study may guide improvements in clinical SLP.
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionsReferences |
|---|
The RNFL exhibits substantial linear birefringence with the slow axis parallel to the direction of nerve fiber bundles (approximately radial around the optic disc)8 9 and retardance that correlates well with RNFL thickness.10 This birefringence probably results from form birefringence of closely spaced cylindrical structures.11 The normal RNFL thickness in humans at the location of typical SLP scans may range from 130 to 250 µm.12 Two current estimates of RNFL birefringence are 0.1 nm/µm in fixed macaque retina (calculated from Fig. 5 of Reference 10 ) and 0.23 nm/µm in ex vivo rat retina.13 Estimating with these two values results in double-pass RNFL retardances of 25 to 50 nm and 60 to 120 nm, respectively. Because fixation decreases the RNFL birefringence,13 the actual values in normal human subjects are likely to be closer to the higher estimate.
|
Additional evidence that corneal birefringence complicates SLP measurements comes from SLP images of the macula. Henle’s fiber layer, long parallel photoreceptor axons extending radially from the fovea, imparts substantial radial birefringence to the macula28 29 30 with an estimated double-pass retardance of approximately 30 nm (measured at 1.25° and 2.9° from the fovea at a wavelength of 568 nm).29 (This birefringence is distinct from the dichroism at short wavelengths associated with Haidinger’s brush.17 28 ) Henle’s fiber layer is more circularly symmetric than the RNFL, yet SLP images of the macula show distinct "bow-tie" or "double-hump" patterns that do not correspond to the underlying anatomy.19
This study was designed to gain a quantitative understanding of the role of corneal birefringence in SLP measurements, first by analyzing the interaction of corneal compensation and the cornea over a wide range of corneal birefringence, next by incorporating corneal compensation into a theoretical model of SLP of a radial retarder, and finally by experimentally testing the model with SLP measurements of the birefringent macula in normal subjects. The model produced bow-tie patterns similar to those in macular images. The theoretical and experimental patterns were quantified with circular profiles around their centers. The variation of theoretical profiles with corneal axis was then compared with the variation of experimental profiles obtained while tilting the subject’s head to rotate the corneal axis. This study found that the SLP model fit the experimental profiles very well and that it could explain many results from other, previously published studies of SLP.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionsReferences |
|---|
) and retardance (
) is
 | (1) |
),
C4 is cos(4),
S2 is sin(2), and
S4 is sin(4).
In this article, retardance is expressed as a difference in optical
path length (units of are in nanometers). It is understood that
before a value for was used in equation 1
, it was converted to a
phase difference at 780 nm. Subscripts on and identify the
optical component to which they refer. It was frequently necessary,
both for convenience and for consistency with the existing literature,
to describe the slow axis of a retarder. These cases are denoted with a
superscript s; thus, for example, Cs denotes the
slow axis of the cornea, and a C of
Cs + 90° was used in equation 1
. All axis
orientations are relative to the horizontal nasal meridian, as viewed
by an observer facing the eye, with ND taken as negative.
Model of SLP
The analysis of SLP used the model in Figure 1
. In SLP, images of the ocular fundus are formed by scanning the beam of
a near-infrared laser (780 nm) in a raster pattern.7
The
ellipsometer (E) measures at each image point the total retardance in
the optical path, by detecting the ellipticity induced in a linearly
polarized input beam.7
In the model, the measuring beam
passed through three linear retarders: the corneal compensator (CC),
the cornea (C), and a uniform radial retarder (R) that represented
birefringent regions in the retina (e.g., peripapillary RNFL or
macula). The slow axis of R was oriented radially, and distance around
R was measured from the horizontal nasal meridian by angle ß. At each
point, therefore, the fast axis of R was R =
ß + 90°. Radial variation in retardance was not analyzed. The
measuring beam was reflected at a deeper layer and traveled back
through the three retarders to the ellipsometer. Reflection from the
ocular fundus exhibits a high degree of polarization
preservation,9
and the reflector in the model
(polarization-preserving reflector [PPR]) was assumed to preserve
completely the polarization state of the incident beam, except for a
180° phase change due to the reversal in direction. This phase change
reversed the sign of the azimuth and the handedness of the reflected
polarization.33
Each optical component in the model
experienced a double pass of the measuring beam. A component that had
axis in the incident beam had axis - in the reflected beam and
the relative orientation of the component axis to the polarization
azimuth was maintained. Because the ellipsometer was insensitive to
handedness, a double pass with reflection was equivalent to a single
pass through the components of the model followed by the components in
reverse order. Thus, an image of R was described by a profile around
its center derived from
 | (2) |
 | (3) |
is 780 nm.
|
Macular birefringence was imaged with a commercially available SLP nerve fiber analyzer (GDx; Laser Diagnostic Technologies, Inc., San Diego, CA). The GDx imaged the fundus with a 256 x 256-pixel raster scan that covered an area of 15° x 15° in visual angle. To obtain macular images, the instrument was aligned on the cornea and pupil as usual, and the subject was instructed to fixate the center of the red rectangle formed by the 780-nm scanning laser. To achieve stable but tilted head position, the usual head-and-chin rest was replaced with one that pivoted in the plane of the subject’s face and gave support to the side of the subject’s head.
For each scan, the GDx provided two images of the fundus, a reflectance image (intended as a means to judge scan quality) that showed retinal blood vessels at high contrast and a retardance image that provided the data from which perifoveal profiles were extracted. Reflectance images were cropped from the GDx screen display. Retardance images were written to a file by a software routine provided with the instrument. Subsequent image and data processing was performed on computer (Matlab software; The MathWorks, Natick, MA).
The amount of head tilt was difficult to control and, because of
compensatory torsional eye movements,34
did not
necessarily correspond to the rotation of the corneal axis.
Fortunately, the reflectance images provided a means to determine the
rotation of the eye. Using one image as a reference, the rotation and
translation of all other images were determined by registration with
triple invariant image descriptors,35
followed by manual
adjustment. Images were registered to within 1 pixel of translation and
0.5° of rotation. The average rotation of images obtained with the
usual instrument headrest was used to define the vertical head
position. The corneal rotation was assumed to be equal to the fundus
rotation and was added to the corneal axis at vertical to provide a
value of C for the particular image.
For each retardance image, a perifoveal profile was extracted from an annular region with an inner radius of 1.8° and an outer radius of 2.2° (1.3 mm in diameter in an emmetropic eye), a region that corresponded approximately to the peak of macular birefringence, as observed in GDx images. The center of the annulus was determined from several retardance images with pronounced macular bow-tie patterns by manually placing a cursor in the middle of the saddle-shaped center of the bow tie. Contour lines superimposed on the image aided this placement. When corrected for translation and rotation and superimposed on the reference image, the selected points clustered close to the region in the reflectance image judged to be the anatomic fovea. The centroid of the cluster was used as the annulus center in all images. At each of 128 angular steps around the annulus, the pixel values across its width were averaged to produce a profile value.
In each subject, the SLP model was fit to the perifoveal profiles by nonlinear least-squares curve fitting (routine LSQCURVEFIT of the Matlab Optimization Toolbox, ver. 2.0; MathWorks)—that is, the set of measured profiles was fit by a set of calculated profiles that minimized the square of the difference between the two sets. Standard errors of the parameters were calculated from the Jacobian of the curve fit.36
To provide a comparison to values obtained by fitting the SLP model, in six subjects corneal birefringence was also measured with a corneal polarimeter described elsewhere.18 Briefly, the polarimeter provided a view of the fourth Purkinje image of a 585-nm light through crossed polarizers and a variable retarder. The Purkinje image was extinguished by adjusting the fast axis and retardance of the retarder to match the slow axis and retardance of the cornea, and the corneal parameters were read from calibrated dials. The other two subjects were not available for corneal polarimetry, but their corneal axes, measured in an earlier study, were included.19
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionsReferences |
|---|
 | (4) |
CRs) and retardance
(CR) of CR were used to characterize the
effects of corneal compensation. (Although shown in Fig. 1 as
1/2CR, the system formed by a single pass through CC and C is
not strictly a retarder, but is equivalent to a retarder followed by a
rotator.37
The rotations cancel in the symmetric chain of
linear retarders in equation 4
, and MCR is
the Mueller matrix of a linear retarder.)
MCC was calculated from equation 1 , where
CC is 60 nm and CC is
-15°.
The behavior of CR as a function of Cs, calculated
directly from equation 4
for realistic values of
C,16
18
is shown in Figure 2
. For all corneas, CR declined to a minimum
where the slow axis of C and the fast axis of CC were parallel
(Cs = CC = -15°; Fig. 2A
). The minimum value was CR =
2|CC - C|. For
C = CC = 60 nm, this
minimum was zero—that is, CC exactly canceled C, but for
C 
CC the minimum
could reach values comparable to the retardances of the macula or RNFL.
The behavior of CRs was more complex (Fig. 2B)
,
Nearly any CRs could be produced by some combination
of Cs and C, although in
actual corneas some values of CRs were more common
than others (see the Discussion section).
|
T(ß) in
equation 3 . Some results are displayed in Figure 3
as retardance images and profiles. The patterns can be understood as an
interaction between R and CR. As R varied with
ß, CR alternately added and subtracted with
the double-pass radial retardance (2R) to
produce the bow-tie pattern seen in the images. The bright arms of the
bow tie (i.e., the peaks of the profile) occurred where
R and CR were
aligned. The profile modulation depended on the relative values of
R and CR. The
peak-to-peak amplitude (Ap-p) of the
modulation was
 | (5) |
R = 0) there was no modulation of the
profile; it was constant at a value equal to
CR (flat dashed lines in Fig. 3
).
|
Cs of these measures for
five values of C and three values of
R. Modulation (Fig. 4 , top row) varied nearly
linearly with R except near
Cs = -15°. Near Cs =
CC = -15°, especially for corneas with
2C 
2CC = 120 nm,
the modulation exhibited a dip toward 0. On the slope of this dip, the
modulation did not change with R, except at
very low values (e.g., Fig. 3B
and the corresponding points labeled b
in Fig. 4
). The mean retardance (Fig. 4
, middle row) increased with the
difference between Cs and
CC, resulting in a minimum at
Cs = -15°. The height of the minimum increased
with the difference between 2C and
2CC. In the region of the minimum, the mean
varied with R, but away from the minimum the
mean was much less sensitive than the modulation to changes in
R. The variation with Cs of
the bow-tie bright axis (Fig. 4
, bottom row) was the same as that of
CRs in Figure 2B
, because maximum total retardance
occurred when the slow axes of R and CR were aligned. The variation of
bow-tie axis with Cs did not depend on
R. The bright axis of the bow tie was
approximately vertical over a wide range of corneal parameters, but for
2C > 120 nm and Cs >
-15° the bow-tie axis lay closer to horizontal.
|
C) remained constant; the corneal axis
(Cs) was varied by tilting the subject’s head. Three examples of macular retardance images and perifoveal profiles are shown in Figure 5 . Pronounced bow-tie patterns, similar to those in Figure 3 but with retardance that varied with distance from the center, were apparent in this subject for head tilts to either side of vertical (images A and C). Near vertical, there was only weak modulation of the macular retardance (image B). The bow-tie patterns were quantitatively evaluated by means of perifoveal profiles (left column) obtained from the annular region of maximum modulation. Each profile was approximated by a simpler, smooth profile synthesized from terms 0, 2, and 4 of its Fourier series (i.e., the mean and first two even harmonics for a total of five independent coefficients per profile). To aid the comparison of data to theory, the three parameters used in Figure 4 to characterize the theoretical profiles—Ap-p, mean level, and bow-tie orientation—were derived from the synthesized profile. In each subject the data fitted by the model consisted of 19 to 45 perifoveal profiles acquired with various amounts of fundus tilt.
To fit the corneal compensation model to the head tilt data, two
additional properties of the GDx were taken into account. First, the
output of the GDx was in arbitrary units, which we termed GDx units
(GU), and we added as a parameter the scale factor s
required to convert GU to retardance in nanometers. Second, the
retardance values in GDx images never approached zero (as they can in
theory). We hypothesized a "noise floor," a minimum value
determined by instrumental factors and by random variation in the raw
images from which retardance was calculated. This concept was
introduced into the model by means of the arbitrary transfer function
shown in Figure 6A
, which had the form (Tn +
Fn)1/n,
where F was the noise floor and n controlled the
sharpness of the transition between F and the line of
equality. A value of n = 3 gave a good balance between
an unrealistic clipping of the troughs of some fitted profiles and a
rapid approach to equality. Thus, the SLP model fitted to the data was
 | (6) |
T(ß) through
equations 2 and 3 : macular retardance (R),
corneal retardance (C), and corneal axis at
vertical head position.
|
|
|
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionsReferences |
|---|
C = 21–138 nm, measured with the corneal
polarimeter) spanned more than 85% of normal values, including one
unusually low value.18
Unfortunately, no subjects with
corneas in the upper 10% of the normal retardance range were available
to test the model. The range of corneal axes (Cs =
-8° to -40°) included more than 75% of normal
eyes.18
The range of radial retardance was limited
(2R = 42–53 nm, as provided by the fit to
macular retardance) and could not be measured independently. The
corneal axes determined by the model were statistically identical with
those determined by polarimetry (P < 0.002). In six
subjects, the corneal retardance determined by the model did not
correspond well to that measured with the corneal polarimeter. This is
consistent with a report that corneal retardance measured with a
modified GDx, although well-correlated with retardance measured with
the corneal polarimeter, is not the same.20
Wavelength
(780 nm vs. 585 nm) and the area of cornea measured are both possible
reasons for the difference, but require further investigation. It was
encouraging that the SLP model fit the experimental profiles very well
and elicited confidence that the model provided a framework for
understanding clinical SLP. An ideal imaging polarimeter should portray accurately the spatial distribution of specimen retardance. For example, the ideal image of R in Figure 1 should have uniform brightness and a profile that is flat and equal to the double-pass retardance. The model showed, however, that the birefringent C and the CC combined to produce bow-tie patterns in the images and double-hump patterns in the retardance profiles. Clearly, a clinical SLP retardance pattern does not necessarily (or even usually) match the retinal retardance pattern. Nevertheless, the model showed that SLP images encode clinically useful information about retinal retardance.
The SLP model assumes that the retinal structure imaged is a uniform
radial retarder (Fig. 1R)
. This assumption fits macular anatomy very
well, but it does not apply quite as well to the RNFL. Two properties
of the peripapillary RNFL clearly differ from R. First,
Rs ß for the RNFL. Nerve fiber bundles are
only approximately radial as they emanate from the optic nerve head.
They are crowded toward the temporal direction and spread apart
nasally.38
39
40
When introduced into the model, this should
distort the symmetry of a vertical bow tie by broadening the temporal
trough, narrowing the nasal trough, and moving the peaks to the nasal
side of vertical. Exactly these features are present in actual RNFL
profiles obtained clinically.41
42
Second, the RNFL
does not have uniform thickness; hence, R is
not a constant. The peripapillary RNFL is thinner temporally and
nasally and thicker superiorly and inferiorly.12
This RNFL
anatomy elevates the retinal surface into a double-hump pattern that is
apparent in scanning laser tomography43
and optical
coherence tomography (OCT),44
and most observers expect to
see a double hump in SLP profiles of the RNFL. Although these
differences are important for a detailed interpretation of RNFL
retardance patterns, to develop a global picture of the information
provided by SLP, it is useful to ignore the differences and maintain
the concept of the RNFL as a uniform radial retarder.
Compensation of Normal Corneas
The practical consequences of corneal compensation were explored
by calculating the properties of CR for the untilted corneas of a
population of normal subjects. Birefringence values, measured at 585 nm
in each of the two corneas of 73 normal subjects,18
were
inserted into equation 4
for two situations, with corneal compensation
as used in SLP and without corneal compensation (i.e., with the cornea
alone). Although corneal retardance at 585 nm and at the SLP wavelength
of 780 nm may not be the same, the two are well
correlated,20
and the calculation provides useful insight.
Recall that the bow-tie patterns in SLP images of R (Fig. 3)
were
induced by CR, with the bright arms of a bow tie lined up with the slow
axis of CR and the mean and modulation determined by
CR and R. The results
of the calculation are plotted in Figure 8
, which shows CR and CRs in
polar coordinates. In polar coordinates, a line connecting a point to
the origin has the same orientation as CRs and a
length equal to CR. Thus, the clusters of
points in Figure 8
provide a sense of the population variability that
CR introduces into SLP images of a radial retarder.
|
CR was low). Extreme
cases, however, (e.g., the stars in Fig. 4 and in Fig. 8B
) could induce
a strong horizontal bow tie that could overwhelm the anatomic pattern
of the RNFL.20
The addition of CC also decreased the
median of CR in the 146 corneas from 86 (Fig. 8A)
to 56 nm (Fig. 8B)
.
Relation of the SLP Model to Clinical Studies of the RNFL
The chief clinical application of SLP is the assessment of the
peripapillary RNFL, a birefringent structure with retardance that
varies directly with its thickness.10
In part because
commercial SLP instruments have used "thickness" as the name for
the displayed output variable, papers in the literature frequently
state or imply that the quantity measured is (or is proportional to)
the actual anatomic thickness of the RNFL. The model and data show that
this is a misconception. Except occasionally, when corneal
birefringence is well compensated (Cs
CC = -15°; 2C
2CC = 120 nm), the peripapillary retardance
image produced by SLP cannot be the same as the spatial distribution of
RNFL thickness and, indeed, a direct comparison of the two variables in
a macaque showed only moderate correlation.45
(The
measurements that originally demonstrated proportionality between
retardance and thickness were made on fixed tissue without the
cornea.10
)
The model described herein suggests that the ability of SLP to measure
loss of RNFL and thereby detect eyes with glaucoma resides mostly in
the bow-tie pattern that CR induces in the radial retardance of the
peripapillary RNFL. Figure 4
illustrates the characteristics of this
pattern over a wide range of corneal and retinal birefringences.
Because the distributions of Cs and
C in the normal population and the CC designed
into SLP instruments usually combine to produce a vertical bow tie
(Fig. 8B) , only two parameters, modulation and mean, are required to
characterize most patterns. The behavior of these parameters in Figure 4
is complex but, with important exceptions, generally the modulation
is more sensitive to R (the variable of
interest) and the mean is more sensitive to Cs.
The predicted sensitivity to R of profile
modulation is borne out by a number of clinical studies that correlate
SLP parameters to measures of visual field loss (mean deviation,
corrected-pattern SD) that can serve as surrogates for decreases in
thickness, or to the actual RNFL thickness as measured by OCT. Hoh et
al.46
found that the modulation-based GDx parameters
Maximum Modulation and Ellipse Modulation are better than the
mean-based parameters Ellipse Average and Total Integral at
discriminating between normal and glaucomatous eyes, are better
correlated with visual field loss and are also better correlated with
RNFL thickness obtained by OCT. Sinai et al.47
use sectors
of SLP output to form two parameters, peak-to-trough amplitude
(modulation-based) and average thickness (mean-based). The
modulation-based parameter discriminates between the normal and
glaucomatous condition and is significantly correlated with mean
deviation; the mean-based parameter has neither attribute. Chen et
al.48
form SLP measures from retardances in different
quadrants: sums (mean-based), ratios to the nasal value, and modulation
in the same sense as used herein. (Ratios are complex, containing
modulation- and mean-based information in both the numerator and
denominator.) Modulation is significantly correlated with visual field
loss, ratios are correlated less but still significantly, and sums are
not well correlated. Similarly, Weinreb et al.49
form
ratios of inferior and superior retardance to temporal retardance that
are correlated with visual field loss of the corresponding hemifields.
The SLP model explains two problematic cases presented by Hoh et
al.50
In one case with absolute glaucoma, "SLP
demonstrated moderate retardation" but the "characteristic
‘double-hump’ pattern ... was absent".50
When
2R is 0 nm in Figure 3
(i.e., the RNFL is
absent), the profile is flat (no modulation) with a value equal to
CR. If such a patient has a cornea that
produces a substantial value for CR, the
mean-based parameters can have apparently normal values, but the
modulation-based parameters should be small. In the second case, "SLP
demonstrated an apparent 90° rotation of nerve fiber distribution,"
a phenomenon that occurs in approximately 1% of
patients.50
This patient probably possessed a cornea
similar to that represented by the stars in Figures 4
and 8
, a highly
birefringent cornea with its slow axis aligned near
CC. With such a cornea, the resultant large
CR with CRs 0° could
overwhelm the vertical double-hump of RNFL anatomy to produce the
observed horizontal pattern.
The SLP model also explains most of the results of a study that is
conceptually similar to the head-tilt experiment of Figures 5 6
and 7
, except that Cs varied across a population rather
than within an individual. Greenfield et al.19
report SLP
of the RNFL and macula from normal subjects in whom they had also
measured Cs. For both RNFL and macula the GDx
parameters related to the mean—Average Thickness, Ellipse Average,
Superior Average, Inferior Average, Superior Integral, and Total
Integral—show a strong linear correlation with Cs
(r2 = 0.6–0.8) from +4° to -76°.
(Note that Greenfield et al. express nasally downward angles as
positive, the opposite to this study.) It is clear from their figures
that the correlation is even stronger when the data are limited to axes
more nasally downward than -15°.19
51
The profile mean
in Figure 4
(middle row) showed exactly this behavior for all values of
C; the mean increased as the difference
between Cs and CC
increased. Unlike the model and the results for subjects 1 and 3 in
Figure 7
, the data of Greenfield et al., do not increase for
Cs nasally upward from -15°, but there are only
five subjects covering a 20° range. A coincidental combination of
retardances and axes could have easily obscured the small increase
expected. In contrast to parameters related to the mean, the
correlation with Cs of GDx parameters related to
modulation—Inferior Ratio, Superior/Nasal, Maximum Modulation, and
Ellipse Modulation—is weak in the RNFL
(r2 = 0.13–0.24) and absent in the
macula.19
The difference between RNFL and macula follows
directly from the modulation curves produced by the SLP model (Fig. 4
,
top row). Except for a narrow range of corneal parameters, the
modulation curve for a 2R of 30 nm (similar to
macula) did not vary with C. The curve for a
2R of 90 nm (similar to RNFL), however, showed
a broader range of variation with its minimum at -15°.
|
Conclusions |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionsReferences |
|---|
The SLP model also reveals the strengths of SLP for assessing the RNFL.
First, the model shows that SLP should be sensitive to RNFL
birefringence, the variable it was designed to detect. The induction of
a double-hump pattern requires the presence of RNFL birefringence, and
loss of this birefringence produces a decline in SLP measurements,
especially in parameters based on profile modulation. Second, SLP
should be reproducible, because corneal birefringence is
stable.27
If the RNFL is always imaged through the same
corneal location, the effects modeled in the current study are the same
for every measurement. Observed changes can then be attributed to
change in R. Reproducibility, of course, is
key to detecting progression of RNFL damage. Finally, the model shows
that SLP measurements depend on the cornea in a predictable way. It may
be possible to correct for this dependence with auxiliary information
obtained by measuring the cornea,52
imaging the
macula,53
54
or both.20
|
Acknowledgements |
|---|
|
Footnotes |
|---|
Submitted for publication May 29, 2001; revised September 25, 2001; accepted October 8, 2001.
Commercial relationships policy: R (RWK, DSG), C (X-RH).
The publication costs of this article were defrayed in part by page
charge payment. This article must therefore be marked
"advertisement" in accordance with 18 U.S.C. 
1734
solely to indicate this fact.
Corresponding author: Robert W. Knighton, Department of Ophthalmology, University of Miami School of Medicine, 1638 NW 10th Avenue, Miami, FL 33136; rknighton{at}med.miami.edu
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionsReferences |
|---|
This article has been cited by other articles:
|
|
 |
|
  S Morishita, T Tanabe, S Yu, M Hangai, T Ojima, H Aikawa, and N Yoshimura Retinal nerve fibre layer assessment in myopic glaucomatous eyes: comparison of GDx variable corneal compensation with GDx enhanced corneal compensation Br. J. Ophthalmol., October 1, 2008; 92(10): 1377 - 1381. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S Michels, M Pircher, W Geitzenauer, C Simader, E Gotzinger, O Findl, U Schmidt-Erfurth, and C K Hitzenberger Value of polarisation-sensitive optical coherence tomography in diseases affecting the retinal pigment epithelium Br. J. Ophthalmol., February 1, 2008; 92(2): 204 - 209. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Sehi, S. Ume, D. S. Greenfield, and Advanced Imaging in Glaucoma Study Group Scanning Laser Polarimetry with Enhanced Corneal Compensation and Optical Coherence Tomography in Normal and Glaucomatous Eyes Invest. Ophthalmol. Vis. Sci., May 1, 2007; 48(5): 2099 - 2104. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 H. V. Danesh-Meyer, S. C. Carroll, J. Y. F. Ku, J. Hsiang, B. Gaskin, G. G. Gamble, and P. J. Savino Correlation of Retinal Nerve Fiber Layer Measured by Scanning Laser Polarimeter to Visual Field in Ischemic Optic Neuropathy Arch Ophthalmol, December 1, 2006; 124(12): 1720 - 1726. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M Sehi, D C Guaqueta, and D S Greenfield An enhancement module to improve the atypical birefringence pattern using scanning laser polarimetry with variable corneal compensation Br. J. Ophthalmol., June 1, 2006; 90(6): 749 - 753. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. A. Medeiros, L. M. Zangwill, C. Bowd, K. Mohammadi, and R. N. Weinreb Comparison of Scanning Laser Polarimetry Using Variable Corneal Compensation and Retinal Nerve Fiber Layer Photography for Detection of Glaucoma Arch Ophthalmol, May 1, 2004; 122(5): 698 - 704. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. J. Reus and H. G. Lemij The Relationship between Standard Automated Perimetry and GDx VCC Measurements Invest. Ophthalmol. Vis. Sci., March 1, 2004; 45(3): 840 - 845. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G Hollo, A Katsanos, P Kothy, A Kerek, and I Suveges Influence of LASIK on scanning laser polarimetric measurement of the retinal nerve fibre layer with fixed angle and customised corneal polarisation compensation Br. J. Ophthalmol., October 1, 2003; 87(10): 1241 - 1246. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. A. Burns, A. E. Elsner, M. B. Mellem-Kairala, and R. B. Simmons Improved Contrast of Subretinal Structures using Polarization Analysis Invest. Ophthalmol. Vis. Sci., September 1, 2003; 44(9): 4061 - 4068. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. A. Medeiros, L. M. Zangwill, C. Bowd, A. S. Bernd, and R. N. Weinreb Fourier Analysis of Scanning Laser Polarimetry Measurements with Variable Corneal Compensation in Glaucoma Invest. Ophthalmol. Vis. Sci., June 1, 2003; 44(6): 2606 - 2612. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. Bagga, D. S. Greenfield, and R. W. Knighton Scanning Laser Polarimetry with Variable Corneal Compensation: Identification and Correction for Corneal Birefringence in Eyes with Macular Disease Invest. Ophthalmol. Vis. Sci., May 1, 2003; 44(5): 1969 - 1976. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
