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C L I N I C A L
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Macular Thickness Measurements in Normal
Eyes Using Spectral Domain Optical
Coherence Tomography
John E. Legarreta, BFA; Giovanni Gregori, PhD; Omar S. Punjabi, MD; Robert W. Knighton, PhD;
Geeta A. Lalwani, MD; Carmen A. Puliafito, MD, MBA
BACKGROUND AND OBJECTIVE: Knowledge
of the macular thickness in a normal population is important for the evaluation of pathological macular change.
The purpose of this study was to define and measure macular thickness in normal eyes using spectral domain optical coherence tomography (OCT).
ments were calculated point wise and averaged on standard regions. For patients scanned with both systems,
the thickness measurements from HD-OCT were approximately 50 µm larger than those from StratusOCT.
The difference between the two measurements decreased
somewhat with eccentricity.
PATIENTS AND METHODS: Fifty eyes from 50 normal subjects (29 men and 21 women, aged 22 to 68 years)
were scanned with a prototype Cirrus HD-OCT system (5
µm axial resolution) (Carl Zeiss Meditec, Inc.). The proprietary Cirrus segmentation algorithm was used to produce
retinal thickness maps, which were then averaged over 9
regions defined by a circular target centered at the true fovea location. The macular thickness of 13 subjects scanned
with both HD-OCT and StratusOCT were compared.
CONCLUSION: Using HD-OCT, it is possible to acquire retinal data sets containing an unprecedented number of data points. Furthermore, it is possible to use OCT
fundus images to evaluate the scan quality and to center
the measurement at the fovea. These advantages, together
with good automated segmentation, can produce more
accurate retinal thickness measurements. Incorporation of
the photoreceptor layer in the measurements is anatomically meaningful and may be significant in evaluating various retinal pathologies and visual acuity outcomes.
RESULTS: After centering the fovea, the mean and
standard deviation values for retinal thickness measure-
[Ophthalmic Surg Lasers Imaging 2008;39:S43-S49.]
INTRODUCTION
From the Department of Ophthalmology, Bascom Palmer Eye Institute,
University of Miami Miller School of Medicine, Miami, Florida.
Accepted for publication April 11, 2008.
Presented as a poster at the Association for Research in Vision and Ophthalmology annual meeting, May 8, 2007, Fort Lauderdale, Florida.
Supported in part by Research to Prevent Blindness, Inc., New York, New
York. Research funding provided in part by a grant from Carl Zeiss Meditec,
Inc. (JEL, GG, OSP, RWK, CAP) and NIH Grant P30EY014801.
Dr. Puliafito is a Research and Clinical Consultant for Carl Zeiss Meditec,
Inc. Dr. Puliafito did not participate in the editorial review of this manuscript.
Dr. Knighton is the principal investigator on a research agreement with
Carl Zeiss Meditec, Inc., to improve spectral domain optical coherence tomography for ophthalmic diagnosis.
Address correspondence to Giovanni Gregori, PhD, Bascom Palmer Eye
Institute, University of Miami Miller School of Medicine, 1638 NW 10th
Avenue, Miami, FL 33136.
Because macular thickness has been found to significantly correlate with visual acuity,1 knowledge of
normal population thickness would be essential for
studying and evaluating macular thickening due to
various ocular pathologies. Optical coherence tomography (OCT) is a noninvasive technology that enables
clinicians to detect and monitor subtle changes in
macular thickening.2-7 Several studies have reported
normative macular thickness data obtained using the
StratusOCT (Carl Zeiss Meditec, Inc., Dublin, CA)
commercial system.8,9
MACULAR THICKNESS MEASUREMENTS WITH SD-OCT · Legarreta et al.
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Figure 1. (Left) Fundus photograph with white box indicating scanning area of the Cirrus HD-OCT B-scans. (Right) Fundus photograph
showing the six radial line scanning pattern of StratusOCT.
Recent advances in OCT technology have led to
the development of faster, more sensitive OCT scanning systems, known as spectral domain OCT (SDOCT). SD-OCT systems are capable of acquiring large,
volumetric data sets in a short time frame.10,11 Several
commercial versions of SD-OCT instruments are currently entering the marketplace. For the current study,
we used a prototype Cirrus HD-OCT instrument from
Carl Zeiss Meditec, Inc. that has an axial resolution of
approximately 5 µm and is capable of acquiring approximately 27,000 A-scans per second. Compared to
StratusOCT, where six 6-mm B-scans are acquired in a
radial pattern centered on the patient’s fixation point,
HD-OCT can acquire up to 200 six-mm B-scans in a
cube pattern centered on the patient’s fixation point or
an operator-selected point in one scan set (Fig. 1).
One important feature of SD-OCT raster scans is
that fundus-like images can be reconstructed from the
data sets.12 These OCT fundus images can be obtained
as soon as the scan is acquired and serve as a useful tool
for screening the image quality by determining whether
eye movements occurred during the scan. B-scans are
automatically registered to the fundus-like images,13 allowing for accurate spatial correlations of the SD-OCT
images (Fig. 2). These capabilities solve the greatest
problems associated with StratusOCT retinal thickness maps: the lack of precise correspondence between
the B-scans and the retinal topography, the difficulties
accounting for eye motions, and the substantial need
for data interpolation. Unstable fixation and imprecise
targeting can lead to inaccuracies in calculating retinal
thickness measurements.14
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The SD-OCT volumetric data set can be analyzed using specialized segmentation algorithms that
automatically identify the boundaries between specific
retinal layers. This information can be used to generate surface maps and thickness maps of the retina.
The maps can be used for qualitative and quantitative
analysis (Fig. 2).
With the increasing use of SD-OCT by ophthalmologists, it would be critical to measure macular
thickness in healthy individuals, not only to provide
normative data, but also to compare these values with
the current OCT system. The purpose of this study
was to define and measure macular thickness in normal
eyes using the Cirrus HD-OCT system.
PATIENTS AND METHODS
A prospective study was performed at Bascom
Palmer Eye Institute after approval from the institutional review board at the University of Miami was
obtained. This study was compliant with the Health
Insurance Portability and Accountability Act of 1996.
A written informed consent was administered to all
subjects before any research scans were obtained.
Fifty pairs of eyes from 50 normal subjects were
scanned with the Cirrus HD-OCT. For this study, we
used a scan pattern composed of 200 ⫻ 200 A-scans
(the second factor denotes the number of B-scans, the
first factor denotes the number of A-scans per B-scan),
which covers uniformly a 6 ⫻ 6 mm square on the
retina. The depth of each scan is 2 mm. Each subject
had both eyes scanned during image acquisition. How-
OPHTHALMIC SURGERY, LASERS & IMAGING · JULY/AUGUST 2008 · VOL 39, NO 4 (SUPPLEMENT)
Figure 2. (Upper left) Reconstructed SDOCT fundus image indicating the location
of the B-scan in the upper right panel.
(Upper right) B-scan of normal fovea with
segmentation boundaries. (Bottom left)
Enlarged portion indicating placement
of segmentation boundaries on internal
limiting membrane (ILM) and retinal pigment epithelium, respectively. The IS/OS
arrow points to the inner segment/outer
segment junction of the photoreceptors.
(Bottom middle) Two-dimensional retinal
thickness map. (Bottom right) Segmented
surface map of ILM and retinal pigment
epithelium retinal layers.
TABLE 1
Mean ± Standard Deviation Macular Thickness
in 50 Normal Eyes Using Cirrus HD-OCT
HD-OCT
StratusOCTa
258.2 ± 23.5
212 ± 20
Superior
326.6 ± 18.9
255 ± 17
Inferior
326.0 ± 24.4
260 ± 15
Temporal
312.6 ± 17.1
251 ± 13
Nasal
328.6 ± 18.3
267 ± 16
Superior
282.5 ± 14.9
239 ± 16
Inferior
270.9 ± 13.9
210 ± 13
Temporal
266.3 ± 17.7
210 ± 14
Nasal
295.5 ± 17.0
246 ± 14
Parameter
Fovea (500 µm)
Inner ring
(1.5-mm radius)
Outer ring
(3-mm radius)
OCT = optical coherence tomography.
a
As reported by Chan et al.22
The Cirrus HD-OCT and Stratus OCT systems are manufactured
by Carl Zeiss Meditec, Inc., Dublin, CA.
ever, for the purpose of thickness measurements, only
the right eye of each participant was included.
Of the subjects, 29 were men and 21 were women. Their ages ranged between 20 and 68 years. Subjects were excluded from the study if they had any
known ocular disease. After image acquisition, two
retina specialists carefully reviewed these scans for abnormalities. Thirteen individuals (selected randomly)
were also scanned with StratusOCT and the retinal
thickness measurements were directly compared to
the results on HD-OCT. StratusOCT data were also
collected in these eyes using the “radial lines” protocol, which consists of six radial scans with the center
approximately on the fovea.
The Cirrus HD-OCT measures macular thickness using a proprietary algorithm developed at the
Bascom Palmer Eye Institute by the second author.
This algorithm detects the internal limiting membrane as the inner retinal boundary and the anterior
surface of the retinal pigment epithelium as the outer
retinal boundary. Once the boundaries are segmented, false-color three-dimensional and two-dimensional thickness maps are generated. Macular thickness
measurements were obtained in nine regions, which
were similar to those in the Early Treatment Diabetic
Retinopathy Study.15 The central circle has a diameter
of 1 mm. The inner circle has a diameter of 3 mm
and is divided into four quadrants. The outer circle
has a diameter of 6 mm and is also divided into four
quadrants. Thickness values obtained from retinal
segmentation are averaged to give the mean thickness
in each quadrant.
One of the major advantages of the SD-OCT technology is that retinal features can be localized precisely
in the OCT data set a posteriori. This means that it is
not necessary to rely on the patient’s ability to fixate
or the operator’s ability to center a scan properly. To
obtain optimal thickness measurements, the first author reviewed each data set and localized the true fovea
position. These coordinates were used to determine the
center of the measurements region for the two-dimensional thickness map.
The StratusOCT mapping software was used to
create a two-dimensional retinal thickness map for
MACULAR THICKNESS MEASUREMENTS WITH SD-OCT · Legarreta et al.
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TABLE 2
Mean ± Standard Deviation Macular Thickness in 13 Normal Eyes Comparing
HD-OCT Versus StratusOCT
Parameter
HD-OCT
StratusOCT
Difference
266.2 ± 22.7
203.9 ± 20.0
62.3 ± 7.3
Superior
327.6 ± 12.7
274.9 ± 14.6
52.7 ± 5.8
Inferior
324.2 ± 12.8
269.0 ± 15.6
55.2 ± 6.7
Temporal
315.2 ± 14.3
259.4 ± 13.8
55.8 ± 7.8
Nasal
331.0 ± 12.2
275.2 ± 15.9
55.8 ± 6.8
281.4 ± 11.3
236.0 ± 13.2
45.4 ± 8.3
Fovea (500 µm)
Inner ring (3-mm radius)
Outer ring (6-mm radius)
Superior
Inferior
268.3 ± 8.2
216.7 ± 13.9
51.6 ± 9.9
Temporal
263.5 ± 12.2
215.3 ± 10.5
48.2 ± 6.6
Nasal
296.7 ± 11.8
248.9 ± 14.7
47.8 ± 7.5
OCT = optical coherence tomography.
The Cirrus HD-OCT and StratusOCT systems are manufactured by Carl Zeiss Meditec, Inc., Dublin, CA.
mm diameter of the center and the thickness decreased
between the 3- to 6-mm diameter outside the center.
StratusOCT scans were also taken of 13 eyes of
13 individuals randomly selected from our population.
The mean and standard deviation for macular thickness were calculated and tabulated in Table 2. The results clearly show that the HD-OCT measurements
are consistently larger than those obtained with StratusOCT. As we discuss later, this difference was expected
and is due to the inclusion of the outer segments of the
photoreceptors in the HD-OCT measurements. Although the difference between the two instruments decreases somewhat with eccentricity, the measurements
are tightly correlated (Fig. 3).
Figure 3. The Cirrus HD-OCT and StratusOCT measurements in
all nine target zones are graphed together for the 13 patients when
they were available. They are very well correlated (R2 = 0.92).
subjects scanned with the machine. These measurements were then correlated with the results obtained
with the HD-OCT.
RESULTS
The mean and standard deviation for macular thickness were calculated and tabulated in Table 1. Similar to
previous studies, thickness values were lowest in the fovea center. Macular thickness was highest within the 3-
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DISCUSSION
A novel feature of SD-OCT is the ability to generate a reconstructed fundus image by summing along
the A-lines. Compared to StratusOCT, where six radial
line scans are presumed to be taken in or around the
fovea, individual B-scans on HD-OCT are registered
to the reconstructed fundus image (Fig. 2), allowing
for accurate spatial localization.
The HD-OCT fundus image is also useful for image
quality control, allowing for an immediate assessment of
any image artifacts or eye movements present in the data
set at the time of acquisition. Because of the large num-
OPHTHALMIC SURGERY, LASERS & IMAGING · JULY/AUGUST 2008 · VOL 39, NO 4 (SUPPLEMENT)
ber of B-scans acquired in a single scan set, subtle eye
movements in the horizontal direction can cause discontinuity in the fundus image. This can be minimized by
reviewing fundus images after scan acquisition and discarding those scans showing significant eye movements.
There are two major differences between the way
in which macular thickness measurements are calculated
in StratusOCT and HD-OCT. The first difference is
the scan geometry and the second is the segmentation
algorithm. On StratusOCT, both patient fixation and
the operator’s aiming accuracy are crucial for generating
accurate thickness measurements.16 The mapping software takes the six radial lines centered on the fovea and
spaced 30° apart, interpolates data between the scans,
and generates a thickness map. Unfortunately, regardless
of the StratusOCT scan protocol (fast vs standard), it is
difficult to judge whether the scans actually intersect at
the fovea and, if they do not, it is not possible to estimate
the error introduced. Eye movements can complicate the
matter and they are basically impossible to detect.
The combination of issues affecting image quality with well-known segmentation problems often
makes it difficult to judge the accuracy of a StratusOCT thickness map.17-19 Even when all of the radial
lines perfectly intersect at the fovea, it is necessary to
rely on interpolation to estimate the retinal thickness
between the scans. The result is a massive loss of detail
and is highly dependent on the assumed symmetry of
the eye to be correct.
With the large quantity of volumetric data acquired
by HD-OCT, the area within the scanning box is uniformly imaged, eliminating the need for interpolation.
Retinal thickness maps are more accurate and detailed
because they are generated using a much larger set of
actual data points. Moreover, scan acquisition is not as
dependent on patient fixation because of the large retinal area covered, and the operator can manually move
the scan window while looking at the retinal scanning
laser ophthalmoscope image. Despite the best efforts
of a trained operator, the OCT data sets will often not
be centered at the fovea. However, the true position of
the fovea in the 6 ⫻ 6 mm scanning box can be determined a posteriori examining the data set (Fig. 4).
Because of the uniform sampling over the scan
region, the center of the measurement target can be
easily moved to the true fovea position. In extreme
circumstances, as illustrated in Figure 5 (which is not
representative of the data used in this article), manual
selection of the fovea position results in the placement
of the outer ring of the thickness map outside the range
of data points collected in the scanning region. In this
case, the result is the average retinal thickness of only
the region of the quadrant overlapping the scanning
box. Although the accuracy of thickness values in the
outer rings may suffer because of centration problems,
it should be pointed out that, except in extreme cases,
they are still based on considerably more sample points
than StratusOCT measurements.
For the scans analyzed in this article, some of the
outer ring quadrants could fall outside of the scanning
region, but the central retinal thickness and the thickness values for the inner ring quadrants were all properly aligned and fully accounted for in the retinal thickness measurements. Although at this time the Cirrus
HD-OCT algorithm has not been independently validated, the authors checked the results on the data sets
presented here and no recognizable errors were found.
It should be stressed again that the software we used
selects a different outer boundary for the calculation of
retinal thickness than StratusOCT. In StratusOCT, the
segmentation mapping software selects the inner segment/outer segment (IS/OS) junction as the outer retinal boundary. Our HD-OCT segmentation algorithm
selects the inner boundary of the retinal pigment epithelium layer as the outer retinal boundary (Fig. 5).
This difference allows our HD-OCT measurements to incorporate the full thickness of the photoreceptor layer in macular thickness measurements.20,21
This difference will, of course, give rise to larger retinal
measurements from the HD-OCT algorithm. More importantly, our measurements are more meaningful from
an anatomical point of view because the retinal pigment
epithelium is a more stable marker than the IS/OS junction. Furthermore, including the thickness of the photoreceptor layer in retinal thickness measurements could
be useful when comparing normal and pathological eyes
with photoreceptor layer disruption.22
Our results show that macular thickness in
HD-OCT was approximately 50 µm thicker than the
corresponding StratusOCT values because of the inclusion of the photoreceptor layer in the measurements
(Tables 1 and 2). It should also be noted that the difference between HD-OCT and StratusOCT measurements decreases somewhat as we move away from the
fovea. This is consistent with published measurements
of the length of the photoreceptors’ outer segments.23
MACULAR THICKNESS MEASUREMENTS WITH SD-OCT · Legarreta et al.
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Figure 4. (Upper left) SD-OCT B-scan
through normal fovea. (Upper right)
SD-OCT fundus image indicating position of B-scan. (Middle) Thickness
map with improperly centered fovea
and the corresponding thickness values. (Bottom) Thickness map centered on the fovea. Thickness values
differ dramatically.
Figure 5. (Top) StratusOCT horizontal, radial
line B-scan of a normal eye. The arrow indicates the outer boundary selection of the segmentation algorithm on StratusOCT. (Bottom)
SD-OCT B-scan corresponding to a similar
location of the StratusOCT B-scan. The arrow
indicates outer boundary selection of the segmentation algorithm.
The eccentricity effect is fairly small and the measurements on the two instruments are highly correlated
(Fig. 3) when considered in their totality. In first approximation, it could be concluded that a conversion
factor of approximately 50 µm could be applied to
compare the two sets of measurements.
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When dealing with macular thickness measurements, an accurate boundary selection is important
for accurate thickness values. Poor image quality can
lead to algorithm failures. The HD-OCT allows for
an immediate assessment of image quality, and the
higher resolution should enable algorithms to more
OPHTHALMIC SURGERY, LASERS & IMAGING · JULY/AUGUST 2008 · VOL 39, NO 4 (SUPPLEMENT)
accurately detect retinal boundaries. The amount of
data in HD-OCT images leads to more accurate and
detailed macular thickness maps. The ability to center the measurements accurately on the true fovea
should reduce the variance of a normative database
and therefore allow for better comparisons, both dynamically on a given patient and cross-sectionally
over a population. This may prove to be useful in
comparing and following thickness measurements in
patients having macular disease.
REFERENCES
1. Nussenblatt RB, Kaufman SC, Palestine AG, et al.
Macular thickening and visual acuity: measurements
in patients with cystoid macular edema. Ophthalmology. 1987;94:1134-1139.
2. Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography. Science. 1991;254:1178-1181.
3. Hee MR, Izatt JA, Swanson EA, et al. Optical coherence tomography of the human retina. Arch Ophthalmol. 1995;113:325-332.
4. Puliafito CA, Hee MR, Lin CP, et al. Imaging of macular diseases with optical coherence tomography. Ophthalmology. 1995;102:217-229.
5. Hee MR, Puliafito CA, Wong C, et al. Optical coherence tomography of central serous chorioretinopathy.
Am J Ophthalmol. 1995;120:65-74.
6. Hee MR, Puliafito CA, Wong C, et al. Quantitative assessment of macular edema with optical coherence tomography. Arch Ophthalmol. 1995;113:1019-1029.
7. Hee MR, Puliafito CA, Wong C, et al. Optical coherence tomography of macular holes. Ophthalmology.
1995;102:748-756.
8. Paunescu LA, Schuman JS, Price LL, et al. Reproducibility of nerve fiber thickness, macular thickness, and
optic nerve head measurements using StratusOCT.
Invest Ophthalmol Vis Sci. 2004;45:1716-1724.
9. Chan A, Duker JS, Ko TH, Fujimoto JG, Schuman JS.
Normal macular thickness measurements in healthy
eyes using Stratus optical coherence tomography.
Arch Ophthalmol. 2006;124:193-198.
10. Wojtkowski M, Srinivasan V, Ko T, Fujimoto J, Kowalczyk A, Duker J. Ultrahigh-resolution, high-speed,
Fourier domain optical coherence tomography and
methods for dispersion compensation. Opt Express.
2004;12:2404-2422.
11. Leitgeb R, Drexler W, Unterhuber A, et al. Ultrahigh
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
MACULAR THICKNESS MEASUREMENTS WITH SD-OCT · Legarreta et al.
resolution Fourier domain optical coherence tomography. Opt Express. 2004;12:2156-2165.
Jiao S, Knighton RW, Huang X, Gregori G, Puliafito
CA. Simultaneous acquisition of sectional and fundus
ophthalmic images with spectral-domain optical coherence tomography. Opt Express. 2005;13:444-452.
Jiao S, Wu C, Knighton RW, Gregori G, Puliafito
CA. Registration of high-density cross sectional images to the fundus image in spectral-domain ophthalmic optical coherence tomography. Opt Express.
2006;14:3368-3376.
Massin P, Vicaut E, Haouchine B, Erginay A, Paques
M, Gaudric A. Reproducibility of retinal mapping
using optical coherence tomography. Arch Ophthalmol. 2001;119:1135-1142.
Early Treatment Diabetic Retinopathy Study Research
Group. Early Treatment Diabetic Retinopathy Study
design and baseline patient characteristics. ETDRS
Report No. 7. Ophthalmology. 1991;98:741-756.
Polito A, Borrello MD, Isola M, Zemella N, Bandello
F. Repeatability and reproducibility of fast macular
thickness mapping with Stratus optical coherence tomography. Arch Ophthalmol. 2005;123:1330-1337.
Ray R, Stinnett SS, Jaffe GJ. Evaluation of image artifact produced by optical coherence tomography of
retinal pathology. Am J Ophthalmol. 2005;1:18-29.
Hee M. Artifacts in optical coherence tomography topographic maps. Am J Ophthalmol. 2005;139:154-155.
Sadda SR, Wu Z, Walsh A, et al. Errors in retinal
thickness measurements obtained by optical coherence
tomography. Ophthalmology. 2006;113:285-293.
Costa RA, Calucci D, Skaf M, et al. Optical coherence tomography 3: Automatic delineation of the
outer neural retinal boundary and its influence on
retinal thickness measurements. Invest Ophthalmol
Vis Sci. 2004;45:2399-2406.
Pons M, Garcia-Valenzuela E. Redefining the limit
of the outer retina in optical coherence tomography
scans. Ophthalmology. 2005;112:1079-1085.
Chan A, Duker JS, Ishikawa H, Ko TH, Schuman JS,
Fujimoto JG. Quantification of photoreceptor layer
thickness in normal eyes using optical coherence tomography. Retina. 2006;26:655-660.
Srinivasan VJ, Monson BK, Wojtowski M, et al.
Characterization of outer retinal morphology
with high-speed, ultrahigh resolution optical coherence tomography. Invest Ophthalmol Vis Sci.
2008;49:1571-1579.
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