Download Retinal assessment using optical coherence tomography

ARTICLE IN PRESS
Progress in Retinal and Eye Research 25 (2006) 325–353
www.elsevier.com/locate/prer
Retinal assessment using optical coherence tomography$
Rogério A. Costaa,!, Mirian Skafb, Luiz A.S. Melo Jr.b, Daniela Caluccia, Jose A. Cardilloa,
Jarbas C. Castroc, David Huangd, Maciej Wojtkowskie
a
U.D.A.T.—Retina Diagnostic and Treatment Division, Hospital de Olhos de Araraquara, Rua Padre Duarte 989 ap 172, Araraquara, SP 14801 310, Brazil
b
Glaucoma Section, Hospital de Olhos de Araraquara, Araraquara, SP, Brazil
c
Instituto de Fı´sica de São Carlos—USP, São Carlos-SP, Brazil
d
Department of Ophthalmology, University of Southern California, Los Angeles, CA, USA
e
Institute of Physics, Nicolaus Copernicus University, Torun, Poland
Abstract
Over the 15 years since the original description, optical coherence tomography (OCT) has become one of the key diagnostic
technologies in the ophthalmic subspecialty areas of retinal diseases and glaucoma. The reason for the widespread adoption of this
technology originates from at least two properties of the OCT results: on the one hand, the results are accessible to the non-specialist
where microscopic retinal abnormalities are grossly and easily noticeable; on the other hand, results are reproducible and exceedingly
quantitative in the hands of the specialist. However, as in any other imaging technique in ophthalmology, some artifacts are expected to
occur. Understanding of the basic principles of image acquisition and data processing as well as recognition of OCT limitations are
crucial issues to using this equipment with cleverness.
Herein, we took a brief look in the past of OCT and have explained the key basic physical principles of this imaging technology. In
addition, each of the several steps encompassing a third generation OCT evaluation of retinal tissues has been addressed in details.
A comprehensive explanation about next generation OCT systems has also been provided and, to conclude, we have commented on the
future directions of this exceptional technique.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Artifacts; Cross-sectional; Fourier domain; Glaucoma; Interferometer; Macula; Macular map; Measurement; Nerve fiber layer; Optic disc;
Optical coherence tomography (OCT); Photoreceptor; Retinal boundary; Retinal thickness; Spectral
Contents
1.
2.
3.
History of optical coherence tomography (OCT): conception of the idea
Basic physical principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
OCT in clinical setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1. Retina (and retinal diseases) . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.1. Image acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.2. Qualitative analysis . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.3. Quantitative analysis . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2. RNFL and glaucoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1. RNFL thickness protocols . . . . . . . . . . . . . . . . . . . . . .
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Abbreviations: A-scan(s), axial scan(s); HRL, highly reflective layer; OCT, optical coherence tomography; RNFL, retinal nerve fiber layer; RPE, retinal
pigment epithelium; RTA, retinal thickness analyzer; SLD, superluminescent diode
$
Supported in part by Fundac- ão de Amparo à Pesquisa do Estado de São Paulo, FAPESP Grant no.: 98/14270-8, and by Grant no.: KBN
4T11E02322.
!Corresponding author. Tel./fax: +55 16 3331 1001.
E-mail address: [email protected] (R.A. Costa).
1350-9462/$ - see front matter r 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.preteyeres.2006.03.001
ARTICLE IN PRESS
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R.A. Costa et al. / Progress in Retinal and Eye Research 25 (2006) 325–353
3.2.2. Reproducibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.3. Diagnostic capability and progression evaluation . . . . . . . . . . . . .
3.2.4. Normative database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.5. Future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.6. Additional considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4. Next generation OCT devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1. Spectral OCT instrument using Fourier domain detection . . . . . . . . . . . . .
4.1.1. Standard-resolution retinal imaging with high-speed spectral OCT .
4.1.2. High-resolution retinal imaging with high-speed spectral OCT . . . .
4.2. Additional considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5. Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. History of optical coherence tomography (OCT):
conception of the idea
OCT was first developed by David Huang and colleagues
in James Fujimoto’s laboratory at the Massachusetts
Institute of Technology (MIT) and published in a 1991
Science article (Huang et al., 1991). The Fujimoto’s
laboratory was specialized in femtosecond lasers at the
time. These are lasers that emit pulses of only several tens
of femtosecond (million billionth of a second) and can be
used to measure the delay of light reflected from tissue
structures with near micron precision. Because femtosecond lasers were too bulky and expensive for routine
clinical use, Huang worked on an interferometer system
that could use a cheap and compact diode light source to
measure the time-of-flight of light with the same precision.
He realized then that this technique, called optical
coherence domain reflectometry, could be the basis of a
new imaging technology with unprecedented potential for
non-invasive imaging of retina and other tissues with
micron resolution. This new technique was coined optical
coherence tomography because it relied on measuring the
coherence of light reflected from tissue structures and
generates cross-sectional images, or tomographs.
The initial retinal OCT experiment that Huang conducted with Joel Schuman, an ophthalmologist then at
Harvard, took several hours to acquire a single image. To
improve the imaging speed, Fujimoto recruited Eric
Swanson, then working on optical communications at
MIT Lincoln Laboratory. With Swanson’s crucial assistance, it was first developed an efficient fiber-optic OCT
system that was fast enough for clinical testing (Swanson
et al., 1993). The first clinical tests of retinal scanning were
conducted by Carmen Puliafito’s group that was then at
the Massachusetts Eye and Ear Infirmary, Harvard
Medical School. The encouraging results lead to commercialization of the technology in the mid-1990s by Humphrey Instruments, Inc. (since acquired by Carl Zeiss
Meditec, Inc). The latest Zeiss Stratus OCT system (third
generation OCT or OCT3) is now used by thousands of
ophthalmologists for the management of macular diseases
and glaucoma.
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2. Basic physical principles
Clinical examination using the slit lamp has been used
for several years as the main instrument for retinal
structural assessment. Meanwhile, many other imaging
techniques have been developed to examine cross-sectional
retinal morphology. The confocal scanning laser ophthalmoscope (cSLO) forms retinal images by sequentially
collecting reflections from laterally and longitudinally
well-defined retinal volumes. Several cSLO images taken
with sequential focal depths can generate three-dimensional information on the distribution of retinal reflectivity
for topographic and tomographic assessments (Huang,
1999). The longitudinal resolution of a cSLO, however, is
limited to !300 mm due to the available numerical aperture
through the pupil and ocular aberrations (Bartsch and
Freeman, 1994). Cross-sectional measurements of the
retina can be achieved in the clinical setting as well by
the instrument coined retinal thickness analyzer (RTA).
The RTA employs the principle of optical triangulation to
provide direct measurement of the retinal thickness with an
estimated accuracy of 20–30 mm (Zeimer et al., 1989). The
instrument projects a narrow slit of 543 nm He–Ne laser
light onto the retina and calculates the distance between the
reflections that correspond to the vitreoretinal and
chorioretinal interfaces. Although recent advances in this
instrumentation have enabled rapid multiple optical
sectioning of neighboring retinal regions to generate a
retinal thickness map (Zeimer et al., 1996), information is
restricted to fundus (macular) regions of 2 " 2 mm and
limited qualitative data can be extracted from such imaging
methodology.
Optical coherence tomography (OCT) is based on the
imaging of reflected light. But unlike a simple camera
image that only has transverse dimensions (left/right,
up/down), it resolves depth. The depth resolution of OCT
is extremely fine, typically on the order of 0.01 mm or 0.4
thousandth of an inch. This provides cross-sectional views
(tomography) of internal tissue structures similar to tissue
sections under a microscope, without disturbing the tissue
as in histology. Thus, OCT has been described as a method
for non-invasive tissue ‘‘biopsy.’’
ARTICLE IN PRESS
R.A. Costa et al. / Progress in Retinal and Eye Research 25 (2006) 325–353
327
Fig. 1. The optical coherence tomography beam is scanned across the
retina (1). The delay of a superficial reflection (2) is shorter than that of
a deeper reflection (3). Reprinted by courtesy of Elsevier (Huang et al.,
in progress).
Fig. 3. An optical coherence tomography cross-sectional image (grayscale image) is built up from many A-scans (red plot lines). Reprinted by
courtesy of Elsevier (Huang et al., in progress).
Fig. 2. An axial scan (A-scan) of the retina. The amplitude of reflection on
a decibel (dB) scale is plotted against depth. Reprinted by courtesy of
Elsevier (Huang et al., in progress).
Ultrasound imaging and RADAR are also reflectometry-based imaging methods. Because OCT employs light,
several advantages are gained. The wavelength of light
(!0.001 mm) is shorter than that of ultrasound (!0.1 mm)
and radio wave (410 mm). Therefore the spatial resolution
of OCT is much higher. And unlike ultrasound imaging,
OCT does not require probe-tissue contact or an immersion fluid since light passes through the air–tissue interface
easily.
Because light travels very rapidly (3 " 108 m/s), it is not
possible to directly measure the time-of-flight delay on a
small spatial scale. The micron-scale resolution of OCT is
achieved by comparing the delays of sample reflections
with the known delay of a reference reflection in an
interferometer. The classic OCT system (Fig. 4) employs a
‘‘low-coherence’’ fiber-optic Michelson interferometer
(Huang et al., 1991). Interferometry measures the effect
of combining 2 light waves. Low coherence means that the
system employs a wide range of wavelengths. We will
explain the concepts of interferometry and coherence
separately.
The interferometer (Fig. 4) has source, sample, reference,
and detector arms all centered on a 50/50 fiber coupler.
Output of the superluminescent diode (SLD) light source is
launched into the source arm fiber and split by the coupler
into the sample and reference arms. Sample and reference
reflections are recombined at the coupler and produce
interference. This interferometric signal is converted from
light to electrical current by a photodetector, processed
electronically, and transferred to computer memory.
To understand how the Michelson interferometer works,
let us start with the simple case (Fig. 5) where the sample
arm reflection comes from a simple mirror surface and
the light source emits only one wavelength. Think of the
sample and reference reflections as 2 waves of light. The
coupler partially transfers theses waves to the detector arm,
In OCT, a beam of light (typically 800–1400 nm
wavelength in the near infrared) is scanned across
the tissue sample. The OCT system then collects the
reflected light and measures its time-of-flight delay. Light
reflected from deeper layers have longer propagation
delays than that reflected from more superficial layers
(Fig. 1). The amplitude of reflected light can be plotted
against delay (Fig. 2) to demonstrate tissue reflectivity at
successively deeper levels of tissue penetration along the
axis of beam propagation. This is called an axial scan
(A-scan). As the OCT probe beam is scanned across a
sample, many A-scans are acquired to form an image
(Fig. 3). A color or gray-scale is used to represent the signal
amplitude.
ARTICLE IN PRESS
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R.A. Costa et al. / Progress in Retinal and Eye Research 25 (2006) 325–353
Fig. 4. Schematic of the classic optical coherence tomography system.
Reprinted by courtesy of Elsevier (Huang et al., in progress).
Fig. 5. In a single-wavelength Michelson interferometer, varying the
reference delay produces a sinusoidal oscillation of optical power in the
detector arm. Reprinted by courtesy of Elsevier (Huang et al., in progress).
where they combine and produce an interference signal.
Interference can be thought of as the addition of the
amplitude of two waves. When the two waves are in phase
(lined up peak to peak), they interfere constructively,
forming a peak in the interference waveform. When the 2
waves are exactly out of phase (lined up peak to trough),
they interfere destructively, forming a trough in the
interference waveform. As the reference mirror is moved,
the phase of the reference wave changes, producing a
sinusoidal interference signal. As the reference mirror
moves through 12 cycle of the source wavelength, the
roundtrip delay of the reference wave varies by one
wavelength and the interference signal goes through one
cycle of sinusoidal oscillation.
To resolve the delay of sample reflections, the OCT
system uses a light source that has a wide range of
wavelengths (low coherence). When the interference signals
are added together over the range of wavelengths, the
interferometric oscillation fades as the delay mismatch
between the reference and sample reflections increases
(Fig. 6). To understand why this occurs, look carefully
at the phase relationship between the wavelength components shown schematically on the left panel of Fig. 6. When
the delay mismatch is near zero (center of waveforms), the
Fig. 6. Combining interference signals from a range of wavelengths (left)
produces a pulse (right). The width of this pulse determines the axial
resolution of optical coherence tomography. Reprinted by courtesy of
Elsevier (Huang et al., in progress).
interference signals from all wavelength components have
the same phase (peaks and troughs lined up) or are
‘‘coherent.’’ This adds up to large interferometric modulation (see large peaks and troughs in the center of the rightside waveform). When the mismatch is large (away from
the center of the waveforms), the interference waveforms
vary widely in phase over the wavelength range (peaks and
troughs not lined up) and add up to near a flat line. The
summed interference signal (Fig. 6, right) forms a wave
pulse. In an OCT system, the pulse is demodulated
electronically to extract the pulse envelope (shape of the
pulse without the sinusoidal oscillation). The width of the
pulse envelope is the coherence length, which determines
the axial resolution of the OCT system. The coherence
length is inversely proportional with the wavelength range
or ‘‘bandwidth.’’
When the OCT system is used to image an actual tissue
sample, there are many reflections at different depths. As
the reference mirror is scanned, each sample reflection gives
rise to a signal pulse when the reference delay matches it.
The plot of the demodulated interferometric signal is the
axial scan (Fig. 2) waveform, which represents amplitude
of reflection vs. depth.
All clinical commercial available OCT systems to date
employ SLD light sources. SLDs are similar to the diode
lasers inside the common compact disc (CD) player, but
are made to emit over a wider range of wavelengths. SLDs
are used because they are economical, compact, longlasting, and emit high quality beams that couples efficiently
with an optical fiber. The resolution of clinical OCT is
basically limited by the state of SLD technology. Early
retinal OCT systems typically employ SLDs emitting
around an 820 nm center wavelength over a bandwidth of
20 nm full-width half-maximum (FWHM) (Swanson et al.,
1993; Hee et al., 1995a). This limits the axial resolution to
roughly 15 mm FWHM in air and 11 mm in tissue. The
Stratus OCT System (Carl Zeiss Meditec, Inc., Dublin, CA,
USA) has 9–10 mm axial resolution in tissue.
ARTICLE IN PRESS
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329
3. OCT in clinical setting
3.1. Retina (and retinal diseases)
Definitive inclusion of OCT in the diagnostic arsenal of
the retina specialist occurred with the availability of third
generation devices. Indeed, OCT has turned out to be the
ancillary exam of choice to assist the diagnosis of several
chorioretinal diseases (Haouchine et al., 2004; Jorge et al.,
2004; Browning et al., 2004; Johnson, 2005; Niwa et al.,
2005; Sandhu and Talks, 2005; Catier et al., 2005; Costa
et al., 2005; Gaucher et al., 2005; Montero and RuizMoreno, 2005; Meirelles et al., 2005). Additionally, the role
of OCT to monitor morphologic retinal changes over time
has turned out to be apparent, particularly given the latest
concept of ‘‘disease modulation’’ associated with new
treatment modalities and the contemporary ‘‘pharmacological’’ era of alternative management of chorioretinal
diseases (Costa et al., 2002, 2003a–c; Campochiaro et al.,
2004; Michels et al., 2005; Eter and Spaide, 2005; Gross,
2005; Salinas-Alaman et al., 2005; Hillenkamp et al., 2005;
Sahni et al., 2005; Cardillo et al., 2005; Bonini-Filho et al.,
2005).
Two representative examples of drugs fitting in such
modern treatment concept might be triamcinolone and
pegaptanib. It has been demonstrated that disease control
using intravitreal drug injections may be preferable to
photothermal destruction of pathological tissues in some
instances. Borne out from several studies over the past
decade, this premise has been to a great extent based on the
results of OCT evaluation, which has provided incontestable evidence of favorable macular remodeling after
treatment. While the initial reports about the alternative
use of intravitreal injection of triamcinolone for the
treatment of macular edema of a variety of causes may
represent the launch of the concept of disease modulation
for the management of chorioretinal diseases (Jonas and
Sofker, 2001; Antcliff et al., 2001; Martidis et al., 2001,
2002; Jonas et al., 2002; Greenberg et al., 2002), the recent
FDA approval of pegaptanib (Macugens, Pfizer) for the
treatment of neovascular age-related macular degeneration
serves as the ultimate frontier that a new treatment era has
definitively began (Gragoudas et al., 2004; Doggrell, 2005).
Presently, several drugs and alternative laser treatments
for the management of macular diseases are under
evaluation in randomized clinical trials, and there is
growing common sense that OCT may be preferable to
angiographic studies to monitor the retinal response in
such setting, particularly because of the theoretical
possibility of quantitative analysis of the induced changes
in a micrometer scale (Fig. 7). However, as commonly seen
in other techniques of retinal imaging, one must bear in
mind that artifacts are expected to occur in the several steps
encompassing an OCT evaluation. Understanding of the
basic principles of image acquisition and data processing
as well as recognition of OCT limitations may help
us to use this imaging technique with cleverness. For
Fig. 7. Quantitative assessment by third generation optical coherence
tomography of morphologic retinal changes induced by treatments in a
patient with diffuse diabetic macular edema. (A) At baseline, retina is
diffusely thickened due to intra- and sub-retinal fluid. (B) Four weeks after
high-density grid laser photocoagulation, favorable macular remodeling is
disclosed by OCT. At the right side of the figure, quantitative analysis
(micrometer scale) of the changes in the average retinal thickness from
baseline in nine different macular sub-fields is disclosed.
scholarship purposes, we have divided this section into
3 parts: (a) image acquisition; (b) qualitative analysis; and
(c) quantitative analysis.
3.1.1. Image acquisition
Part of the artifacts generated during OCT data
processing may be attenuated given that optimal image
acquisition has been performed. For such, the examiner
should be aware of as well as should follow all guidelines
presented in the device’s user manual. In this segment,
some guidelines are emphasized and additional tips to
minimize bias generated by the examiner are presented.
3.1.1.1. Scanning centralization. When acquiring macular
scans for retinal thickness measurements (macular thickness
map and fast macular thickness map scan acquisition
protocols), it is imperative that the examiner centers all 6
scans at the fovea. This is relatively easy for cooperative
patients with relative good vision. However, the profile of
patients with chorioretinal diseases submitted to OCT
evaluation at our institution is quite different. In general,
patients are aged 50 or more, and have poor fixation due to
impaired visual acuity. Additionally, the examiner frequently faces a situation in which precise identification of
the foveal center is problematic because of distortions
of the macular architecture associated with the disease.
Therefore, the examiner not only must be capable to
identify the location of the fovea in abnormal maculas but
also has to be extremely serene to correctly place all 6 scans
at the presumed foveal center. While the former will be sole
dependent on examiner expertize, the latter task may be
facilitated by switching on the center line tool of the OCT3
software. Right-click anywhere in the scan acquisition
window and a vertical line appears in the center of the scan
image. This feature facilitates macular scans centralization
and shortens the acquisition time of optimal scans for
macular maps. To deactivate the center line, right-click
another time in the scan acquisition window (Fig. 8).
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3.1.1.2. Data verification and validation. Immediately at
the end of one scanning session for macular thickness maps
using either standard (512 A-scans/image) or fast (128
A-scans/image) acquisition protocols, some actions should
be performed by the examiner prior to data processing to
generate the macular maps. Initially, the examiner should
verify possible artifacts in the delineation of the retinal
boundaries. For such, each image (B-scan) should be
processed in separate using the retinal thickness (single eye)
analysis protocol and accuracy of automatic delineation
confirmed. If delineation errors were verified in any of the 6
B-scans, a new complete scanning session should be
performed (Fig. 9). Once adequate images have been
acquired, the examiner should then verify centralization of
the 6 scans (in respect to the foveal center). By means of
data processing using the retinal map (single eye) or retinal
Fig. 8. (A) During fundus scanning, right-click anywhere in the scan
acquisition window (arrowhead), and a vertical line appears in the center
of the scan image (B). This feature facilitates macular scans centralization
(C and D), and shortens the acquisition time of adequate scans for
macular maps.
thickness/volume (OU) analyze protocols, the software
automatically calculates the average (7SD) retinal thickness at the fovea, named ‘‘foveal thickness’’ or ‘‘foveal
height’’ (Fig. 10). The more central A-scan of each one of
the 6 B-scans acquired is used to calculate foveal height.
Since all 6 scans are to be centered at the same point
(fovea), in theory, in a perfect scan acquisition session, the
central A-scan should be the same for all 6 B-scans
(intersecting point). Therefore, in this hypothetical situation, the SD of the average foveal height is to be equal to
zero. Depending on the macular status, SD values higher
than 30 mm are highly suggestive that at least one of the 6
scans is not correctly centered at the fovea, and a new
complete scan acquisition session should be performed.
3.1.1.3. Manual raster scanning. At the end of a scanning
session for macular map, it is highly advisable to the
examiner to perform a manual raster scanning throughout
the macular area to minimize the chance of missing
morphological details in the adjacencies of the macular
Fig. 10. Checking of scans displacement in respect to the foveal center
(after verification of the automatic delineation of retinal boundaries
[Fig. 9]). (A) By using the retinal map (single eye) or retinal thickness/
volume (OU) analyze protocols, the software automatically calculates the
average (7SD) retinal thickness at the fovea, named ‘‘foveal thickness’’,
‘‘center’’ or ‘‘foveal height’’. In spite of delineation flaws observed in first
scanning (Scan 5—Fig. 9(A)), which induced a !10% difference in
average RT in two subfields (between red lines) (B), note that the SD of
the foveal thickness was o30 mm in both scanning acquisition sessions
(A and B), indicating good centralization of the 6 scans in both settings.
Fig. 9. Verifying in separate the automatic delineation of the retinal boundaries in each image (B-scan) to be used to macular maps. (A) At the end of one
scanning session for macular thickness maps, analysis of the automatic retinal boundaries delineation using the retinal thickness (single eye) analysis
protocol revealed one major delineation error in scan 5 (red dashed line/asterisk). (B) A new complete scanning session has solved the issue (red dashed
line/asterisk).
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Fig. 11. Manual raster scanning. (A) Perifoveal detachment of the
posterior hyaloid and presumed foveal split were seen (impending macular
hole); detailed raster scanning revealed that in fact the pseudocyst had
already extended posteriorly (A0 ), and there was an eccentric opening of its
roof (arrowhead) (stage 2 macular hole). (B) Incomplete vitreofoveal
separation and a tomographic appearance that gives the impression that a
lamellar hole is to be formed; however, detailed scanning demonstrates an
already established full-thickness macular hole (B0 ).
center. This maneuver enables an enhanced ‘‘view’’ of the
macular status. It is not rare to find new findings such as
abnormal vitreoretinal adhesions. The use of 8 mm in
length scans for manual raster scanning may also facilitate
the detection of vitreomacular adhesions (Fig. 11).
3.1.1.4. Scan review software tool. Occasionally during
scanning of ocular fundus, the examiner misses the exact
timing to freeze the desired image or some computer delay
occurs after the freeze button has been pressed, and the
subsequent tomogram is now frozen in the scan acquisition
window computer screen. By pressing the review button,
the examiner is allowed to retrieve all tomograms acquired
in that session (scan review window). If an optimal
tomogram exists amongst recovered images, it can be
selected and saved by the examiner (Fig. 12).
3.1.1.5. Bimanual technique. A simple change proposed
by one of the authors (D.C.) in the disposition of the
mouse within the device’s table may also facilitate
immensely OCT evaluation in patients with poor collaboration. By changing the mouse position to the left side of
the keyboard, the examiner will be able to control
simultaneously the alignment of the scanner unit (patient
module) with the right hand (joystick), and all the screen
settings (such as Z-offset, polarization, and fixation LED)
with the left hand (mouse). In addition, to shorten
acquisition time, the examiner may keep the freeze (with
or without flash) button of the scan acquisition window
pressed during scanning; when an optimal tomogram is
displayed in the screen, the image is rapidly frozen by just
releasing the button (Fig. 13). A short period of adaptation
may be needed until the examiner get used to this
alternative mouse disposition.
3.1.1.6. Additional considerations. The third generation
of OCT instruments offers basically two modes of image
acquisition for macular thickness measurements. In the fast
mode, each tomogram (B-scan) consists of 128 A-scans
Fig. 12. Review software tool. After activating the scanning mode (A), the
examiner may freeze the image at any desired time (B). By pressing the
review button (C), the examiner is allowed to retrieve all tomograms
acquired in that session (scan review window). If an optimal tomogram
exists amongst recovered images, it can be selected (D) and saved by the
examiner (E).
Fig. 13. Alternative mouse disposition within the table of third generation
OCT. The examiner may keep one of freeze (with or without flash) buttons
of the scan acquisition window pressed during scanning to speed up image
acquirement.
while in standard mode each tomogram consists of 512
A-scans. In both modes, a total of 6 tomograms oriented at
301 intervals are acquired. Topographic macular maps are
ultimately derived from each individual A-scan per OCT
study (768 A-scans in fast mode; 3072 A-scans in standard
mode) (Fig. 14). The equivalence of retinal maps generated
by standard and fast modes in clinical scenarios other
than diabetic macular edema remains to be determined.
Additionally one must bear in mind that, although
quite convenient for the patient and presumably less
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time-consuming for the examiner, the fast mode acquires
all six tomograms in sequence at one single scanning
session, increasing the chance for an undesirable misalign-
ment of one or more of the tomograms in relation to the
foveal center (Fig. 8(D)). Since macular maps are generally
used to evaluate possible changes in the macular status
over time, it is highly advisable to verify the capability of
the examiner to generate reproducible maps (Fig. 15).
3.1.2. Qualitative analysis
Third generation OCT is an established strategy that
improves first generations OCT technology and achieves
extraordinary in vivo visualization of retinal features and
disease. OCT3 exceeds first generations OCT imaging by
obtaining superior axial-image resolution and higher pixeldensity images, and therefore offers better recognition of
the intraretinal layers. Improved acquisition speed (400
A-scans/s) allows, within 1–2 s, the visualization of the
retinal morphology approaching a level of structural
differentiation obtainable only with histopathology (Fig. 16).
Fig. 14. Fast and standard macular thickness maps. (A) In the fast mode,
each tomogram (B-scan) consists of 128 A-scans while in standard mode
(B) each tomogram consists of 512 A-scans. In both modes, a total of 6
tomograms oriented at 301 intervals are acquired.
3.1.2.1. Defining inner and outer HRL. Ever since the
initial images obtained using first generation OCT became
available, several studies have focused on the precise
interpretation of retinal reflective signals and their correlation with retinal morphology. From the first generation
tomograms of normal retinas it was demonstrated that a
clear highly reflective layer (HRL) exists at the outer aspect
of the neuro-sensory retina. Based on clinical and
tomographical correlation studies, it had been suggested
that the outer most reflective layer might correspond
to a complex formed by the RPE and choriocapillaris,
and such layer was then coined ‘‘RPE-choriocapillaris
Fig. 15. (A–D) Four scanning sessions performed in 5-min intervals using the fast macular thickness map acquisition protocol in a patient with central
serous chorioretinopathy. (A0 –D0 ) Data processing revealed optimal centralization of the scans in all four scanning sessions and good correspondence of
topographic macular maps.
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Fig. 16. Differences in image quality related to A-scan density (normal
macula). Note that image ‘‘quality’’ is increases as the number of A-scans/
image multiplies (128 [A], 256 [B], and 512 [C]).
hyper-reflective complex’’. In 1998, Huang et al. first
proposed an alternative interpretation of such hyperreflective complex (Huang et al., 1998). Based on an
OCT study with histological and pathological correlation
in normal and rd chickens, they suggested that the outer
most hyper-reflective complex might correspond to photoreceptors’ inner and outer segments, RPE, and anterior
choroidal pigmentation (they termed it outer retina–choroid complex). At that time, they have also demonstrated
that in the most severely affected rd chickens, which lacked
photoreceptor layer, the total thickness of the outer most
hyper-reflective complex is reduced, suggesting missing the
highly reflective peak derived from the photoreceptor
IS/OS (Huang et al., 1998). Supportive data to Huang’s
hypothesis occurred as soon as third generation and
ultrahigh-resolution OCT clinical studies became available
(Montero et al., 2003; Drexler et al., 2003; Jorge et al.,
2004; Costa et al., 2004). The single outer hyper-reflective
layer seen by first generations OCT was then visualized as
two parallel, highly reflective (red/white) layers separated
from each other by one thin layer of moderate reflectivity
(green/yellow) at the level of the posterior boundary of the
retina (Fig. 17). The inner HRL, which most likely
corresponds to the junction between the inner and outer
segments of the photoreceptors, assumes a forward bowshaped configuration in the center of the macula consistent
with the well-known increase in length of the outer
segments of the cones in such region. The outer HRL,
which appeared approximately two times thicker than the
inner HRL, have been described to be equivalent to the
RPE-choriocapillaris hyper-reflective complex seen on first
generations OCT. However, the precise interpretation of
the outer HRL remains to be established. Is choriocapillaris signaling contributing to its formation? Such question
is to be answered as soon as additional ultrahigh-resolution
OCT data becomes available.
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Fig. 17. Third generation optical coherence tomography appearance of
one normal macula. (A) Two, well-defined, linear, highly reflective layers
(HRL) are seen at the outer aspect of the neural retina. (B) The inner HRL
(corresponding to the photoreceptors IS/OS junction) is thinner than the
outer, and is characterized by mild forward bow-shaped configuration at
the foveal center. The outer HRL may correspond to a hyper-reflective
complex formed by RPE [and choriocapillaris].
3.1.2.2. Outer retina. Particular analysis of the inner
HRL tomographic appearance has provided new insights
for better comprehension of diseases affecting the macula.
The integrity of the inner HRL has been correlated to some
extent with visual acuity. Eyes with vitreomacular traction
syndrome or macular edema and extraordinary good
visual acuity levels represent a good example of the
value of such particular analysis (Fig. 18A,B). In unilateral
resolved central serous chorioretinopathy as well as in eyes
presenting visual acuity deterioration due to photic
maculopathy the same rationale may be used (Eandi
et al., 2005; Jorge et al., 2004). Third generation OCT
evaluation has demonstrated abnormal reflectivity at the
level of the outer foveal retina, such as intense fragmentation or complete interruption of the inner HRL. It has been
suggested that visual acuity may be more severely distorted
in eyes presenting full-thickness involvement of the
photoreceptors reflective layer (Jorge et al., 2004). Analysis
of the inner HRL has also demonstrated usefulness in the
evaluation and better understanding of the outcomes of
operated macular holes. It has been demonstrated that in
spite of anatomical success and recovery of the macular
shape, the postoperative visual acuity and improvement of
visual acuity were not directly related to the morphological
results. Outer retinal features appear to be more important
to determine postoperative visual function as irregularities
at the level of the inner HRL after macular hole surgery
may prevent visual acuity improvement (Uemoto et al.,
2002; Kitaya et al., 2004; Villate et al., 2005) (Fig. 18C,D).
New and unexpected findings have also been demonstrated by studies using OCT in several hereditary
retinopathies (Aleman et al., 2002; Jacobson et al., 1998,
2000, 2003, 2004, 2005; Milam et al., 2003; Pianta et al.,
2003). These scientific results include: localization of the
missing photoreceptor component in retinitis pigmentosa
(Jacobson et al., 1998, 2000); prediction of sub-retinal
and sub-RPE deposits in cone-rod dystrophy and in Best
macular dystrophy (Aleman et al., 2002; Pianta et al.,
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Fig. 18. Tomographic appearance of outer foveal retina and visual acuity (VA). (A) Typical inner HRL appearance in normal macula (VA ¼ 20/20). (B)
Macular edema in branch retinal vein occlusion and VA ¼ 20/25; note at the fovea, the inner HRL is well preserved. Intense fragmentation of the inner
HRL in one patient with outer macular hole and VA ¼ 20/50$1 (C), and in patient with photic maculopathy and VA ¼ 20/60 (D).
Fig. 19. Vitreomacular status and diabetic macular edema. From
perifoveal posterior vitreous detachment (A and B) to vitreofoveal
traction (and increased foveal high) (C), and finally to spontaneous
complete vitreofoveal separation (and favorable macular remodeling).
2003); unexpected retinal lamination abnormalities (Jacobson et al., 2003, 2004); and, definition of the relationship
between outer nuclear layer thickness and visual function
(Jacobson et al., 2005).
3.1.2.3. Vitreoretinal interface. Unparalleled characterization of the vitreoretinal interface has been possible with
the advent of third generation OCT. Studies focused on the
analysis of the vitreomacular interface have led to new
insights about our understanding and management of
several maculopathies, such as idiopathic macular hole and
diabetic macular edema. For example, a high prevalence of
perifoveal posterior vitreous detachment with incomplete
vitreofoveal separation has been demonstrated in diabetic
patients with macular edema, suggesting a possible
additional role of the vitreomacular interface status in the
pathogenesis of diabetic macular edema (Gaucher et al.,
2005). Anecdotal reports of favorable macular remodeling
in eyes with diabetic macular edema after spontaneous
vitreofoveal separation, as well as in the early postNd:YAG laser capsulotomy period, may provide additional supportive data of the possible influence of the
vitreomacular interface status in such scenario (Watanabe
et al., 2000; Yamaguchi et al., 2003) (Fig. 19).
Fig. 20. Third generation optical coherence tomography evaluation of the
left eye of a 57-year-old woman with idiopathic full-thickness macular
hole in the right eye. (A) At presentation a full-thickness macular hole was
seen in patient’s right eye, and OCT3 scan of the left eye revealed complete
detachment of the posterior hyaloid in the macular region with hyperreflective signals in the plane of the detached posterior hyaloid over the
foveal region (arrow). Despite minimal irregularities of the inner foveal
contour, macular architecture was relatively well preserved at presentation, and visual acuity was 20/20. (B) Five months later, visual acuity
decreased to 20/25$2 and an epiretinal membrane (grade 1) was seen in her
left eye associated with the development of a full-thickness macular hole.
Oblique scans revealed complete interruption of the foveal retina of
approximately 99 mm associated with perifoveal intraretinal fluid accumulation and attenuation of the inner HRL suggesting edema of the outer
perifoveal neural retina. Tornambe’s ‘‘retinal hydration’’ theory may
explain macular hole formation in eyes presenting complete vitreofoveal
separation and associated disruption of the inner fovea.
Presently, there are more than 80 published OCT studies
about macular holes. Old concepts have been revisited and
new findings and conjectures, such as the influence of
oblique vitreofoveal tracional forces, the demonstration of
‘‘intrafoveal split’’ as well as the retinal ‘‘hydration’’
theory, have been possible due to enhanced appreciation
of the vitreomacular interface status and macular morphologic features in eyes with macular holes (Hee et al., 1995b;
Gaudric et al., 1999; Haouchine et al., 2001; Tornambe,
2003) (Fig. 20).
3.1.2.4. Additional considerations. An extraordinary qualitative analysis of the macular morphologic features has
been enabled by third generation OCT technology. However,
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et al., 1995; Puliafito et al., 1996; Zeimer et al., 1996;
Podoleanu et al., 1998; Bartsch and Freeman, 1994).
Indubitably, one of the most attractive features of third
generation OCT is the theoretical possibility of attaining
reproducible and accurate measurements of ocular fundus
tissues. In clinical settings, it has significant potential both
as a diagnostic tool and particularly as a way to monitor
objectively subtle retinal changes induced by therapeutic
interventions. Understanding of the basic principles of
automatic retinal thickness measurements by OCT3 as well
as recognition of the software limitations are crucial steps
to facilitating users to extract tomographic data as ‘‘real’’
as possible.
Fig. 21. Young patient with pathologic myopia complaining of distortion
and acute loss of vision. (A) At presentation OCT evaluation suggested the
presence of a ‘‘true’’ abnormal hyper-reflective formation (arrowheads)
such as choroidal neovascularization. (B) Six weeks latter, the macula
contour was practically normal. The patient had serohemorrhagic
complications related to one small lacquer crack located juxtafoveally,
without associated neovascularization.
one should bear in mind that optimal interpretation of
OCT3 findings in clinical setting is highly dependent on
adequate clinical correlation and, whenever suitable,
clinical and angiographical correlation may be preferable.
Third generation OCT evaluation in eyes presenting early
stages (grade 0 and 1) epiretinal membranes and in patients
with serohemorrhagic macular complications due to
choroidal neovascularization are good examples of entities
in which interpretation bias may occur in the absence of
clinical/clinical and angiographical correlation. The occurrence of ‘‘normal’’ cross sectional images (with no apparent
abnormal finding) is not rare in patients with early
stage epiretinal membranes. In the same view, one should
be caution in the interpretation of tomographic findings
in exudative maculopathies, given that outer retina edema
as well as blood may eventually simulate the tomographic appearance of one ‘‘virtually’’ abnormal formation
(Fig. 21).
Finally, an important aspect of OCT data that has been
available since the first generation technology, but is very
rarely studied, is the intensity changes resulting from intraretinal abnormalities in backscatter. In terms of future
work, this rich data source, which is available in each scan
performed nowadays, requires careful attention in the
future. Quantitative analysis of intra-retinal OCT intensity
changes have been demonstrated experimentally by Cideciyan et al. in dogs (Cideciyan et al., 2005). Also relevant to
this subject, is one of the very few clinical examples of
changes in intra-retinal light scattering, reported by Lerche
et al. (2001), including 20 patients with retinal venous
occlusive disease.
3.1.3. Quantitative analysis
Cross sectional retinal imaging provides a unique
opportunity to quantify the overall thickness of the retina
in vivo (Huang et al., 1991; Hee et al., 1995a; Schuman
3.1.3.1. Fundamentals of OCT automatic retinal thickness
measurement. At first moment, it is very difficult to
understand why the OCT3 software erroneously delineates
the retinal boundaries in an optimal tomogram as such
exemplified in Fig. 22. Initially, one should bear in mind
that automatic retinal thickness measurements are generated in essence by means of a ‘‘mathematical calculation’’
(algorithm). The algorithm identifies differences in the
image reflectance patterns in each A-scan (up to 512
A-scans in OCT 3) that compose one tomogram (B-scan),
and assumes that the distance between two relatively high
reflective structures represents the retinal thickness at that
A-scan. As a result, the OCT software locates the presumed
inner retina boundary at the vitreoretinal interface (first
high reflective structure) and the presumed outer retina
boundary at the retinal pigment epithelial-photoreceptor
outer segment interface (second high reflective structure).
The algorithm also compares the ‘‘shape’’ of one A-scan to
adjacent A-scans, once great differences in shape are not
Fig. 22. Automatic retinal thickness measurement. Although quite good
scans were acquired (blue-dashed box), the OCT 3 software algorithm was
not able to delineate correctly the outer retinal boundaries (red dashed
boxes, arrows).
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expected to occur in side-by-side A-scans. The software
then places a line on the inner vitreoretinal interface and
another on the retinal pigment epithelium (RPE)-outer
retinal interface and determines retinal thickness as the
distance between these lines at each measurement point
along the scan’s x-axis. Therefore, even in ‘‘fine-looking’’
B-scans, errors in retinal boundaries delineation may
occur.
3.1.3.2. Software delineation of outer neuro-sensory retinal
boundary. It was believed in the past that scans of normal
eyes did not have inner and outer retina boundaries
misidentification artifacts and only had artifact related to
examiner error. Therefore, under optimal scan acquisition,
measurement of the retinal thickness is expected to be
perfect, basically depending on the ability of the OCT 3
software to recognize both interfaces at each A-scan that
composes the tomogram. However, it has been recently
demonstrated that built-in OCT3 software has encountering severe problems in recognizing the outer boundaries of
the neurosensory retina in optimal OCT3 scans (Costa
et al., 2004). Of particular concern was the finding that
such recognition was invariably incorrect in normal eyes
(Costa et al., 2004). As explained above, the so-called
‘‘RPE-choriocapillaris reflective complex’’ seen in first
generations OCT now is disclosed as two well-defined
HRL at the level of the outer retina in the macular region
of healthy subjects in third generation tomograms; the
inner HRL corresponding to the junction of the inner and
outer segments of the photoreceptors while the outer one
most likely corresponding to the retinal pigment epithelium
or a reflective complex formed by RPE and choriocapillaris. A similar tomographic appearance has been also
evidenced in non-affected macular regions of patients with
selected eye diseases (idiopathic macular hole, central
serous chorioretinopathy, and macular edema), whereas
affected regions generally demonstrated a single-layer high
reflective appearance with disappearance of the inner HRL
(Costa et al., 2004).
The use of the OCT3 automated retinal thickness
measurement tool (software versions 1.0, 2.0, and 3.0)
has generating erroneous values due to incorrect interpretation of the inner HRL as the outer neural retina
boundary (Costa et al., 2004; Pons and Garcia-Valenzuela,
2005) (Fig. 23). Measurements using the automated tool of
the OCT3 software (version 3.0) in comparison to manual
caliper-assisted technique, in which the outer HRL was
interpreted as the outer boundary, demonstrated that a
significant difference existed in the generated values for
retinal thickness at specific macular regions in healthy
subjects caused by such misalignment. Manual caliperassisted retinal thickness measurements at specific macular
regions differed from those automatically generated by
9.9% from up to 38% (Costa et al., 2004).
3.1.3.3. Topographic macular maps. Built-in software of
third generation OCT performs measurements of macular
thickness using 6 intersecting 6-mm-long OCT images
oriented in a radial pattern centered on the fovea (Hee
et al., 1998). Six images of 512 A-scans (transverse pixels)
each can be acquired in approximately 8–10 s using
macular thickness map or radial lines acquisition protocols, or 6 images of 128 A-scans each can be acquired
in approximately 2 s using the fast macular thickness
map. The radial scanning protocol was designed to
concentrate measurements in the central fovea, where high
sampling density is most important. The 6 OCT images
are segmented to detect the retinal thickness, which is
displayed as a false-color topographic map divided into 9
regions: one central (central macular thickness [CMT])
plus 8 Early Treatment Diabetic Retinopathy Studyfashion sub-fields, and the average thickness value for
each region is displayed in separate. Because the radial
pattern of 6 OCT images samples the macular thickness
along clock hours, the retinal thickness in the wedges
between each image is interpolated. Therefore, this imaging
protocol may miss focal peculiarities in a span of o1 clock
hour, or 301. In addition, misidentification of retinal
Fig. 23. Automated retinal thickness measurement was obtained from corresponding A-scan at the fovea (left). Manual caliper-assisted measurement of
retinal thickness at the fovea using the automated delineation for the inner retinal boundary by the software as one point (inner caliper cross) and
positioning the outer caliper cross just above the outer HRL demonstrated a difference of 51 mm.
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boundaries in the 6 B-scans that are used to generate
retinal maps may interfere significantly in the average
retinal thickness value displayed for each sub-field and
CMT, as well as in values estimations for macular volume.
Of concern, is the fact that CMT values have been used as
the main tomographic outcome to monitor retinal changes
by therapeutic interventions. Because of particular morphologic foveal features, retinal thickness measurements at
this region are more sensible to the OCT3 software
measurement flaws (Costa et al., 2004). Recent data from
next generation OCT prototypes have been supportive to
our concerns about the automatic delineation of the ‘‘true’’
retinal boundaries by OCT software. Comparison of
retinal thickness maps obtained using OCT3 and 3D
OCT data from one high speed ultrahigh-resolution OCT
prototype, which enables differentiation of the junction
between the inner and outer segments of the photoreceptors (inner HRL) as a distinct feature from the RPE (outer
HRL), showed a 8–9% difference in retinal thickness
values for the 8 macular map sub-fields and up to 16%
for CMT, when the thickness map that measures the
retinal thickness as the distance from the inner interface of
the hyporeflective band corresponding to the RPE to
the vitreal retinal interface was disclosed (Wojtkowski
et al., 2005).
3.1.3.5. Additional considerations. Summing up, automatic OCT macular thickness is calculated by computer
image-processing algorithms with several notable flaws.
The most important flaw is that the software does not truly
measure the anatomic macular thickness due to its inability
to reliably discriminate the junction between the inner and
outer segments of the photoreceptors (inner HRL) from
the RPE, because both produce a high backscattering
signal. Therefore, macular thickness is actually measured
using the hyper-reflective layer corresponding to the
junction between the photoreceptor inner and outer
segment (inner HRL) as the outer retinal boundary,
effectively truncating the outer segments in most subjects.
Obviously, this is not an incapacitating limitation of the
methodology, but this issue should be stressed because one
may assume that these measurements are more anatomically meaningful than they truly are. By addressing these
issues, we intent to promote a better comprehension of the
actual limitations of the OCT3 software, and to assure
researchers’ as well as manufacture’s best efforts to
overcome them as fast as possible. Recognition of the
limitations of any particular device is the basic principle for
its use with cleverness.
3.1.3.4. Current third generation OCT software versions.
As recently clarified (Hee, 2005), the original macular
thickness algorithms (upon which the current OCT3
algorithms are based) were designed to determine the
inner and outer retinal boundaries in diabetic macular
edema, a condition leading to retinal thickening in
which intraretinal fluid accumulation and hard exudates
occur but the retinal pigment epithelium and inner limiting
membrane remain intact (Hee et al., 1998); in such
scenario, the inner HRL is frequently attenuated or
absent due to intraretinal edema, and the OCT3 software
correctly delineates the outer HRL as the outer boundary
(Costa et al., 2004; Costa, 2005). Additionally, we should
remember that the inner HRL was not so evident in first
generation OCT. The enhanced resolution offered by
OCT3 compared with first generations OCT provides
images displaying more complex internal features that,
paradoxically, require more refined boundary detection
algorithms.
Improved versions of the OCT3 software are constantly
under development. The new software version (4.0)
including innovative features to minimize problems during
image acquisition has been just recently released. Normative reference values for retinal thickness measurements of
the macula have also been included in such version.
However, one must bear in mind that misidentification of
the outer retinal boundary is still occurring in version 4.0,
and, of particular concern, that normative reference values
have been established according to OCT3 data in which the
outer retinal boundary was considered to be the inner
HRL, and not the outer HRL.
Interest in retinal nerve fiber layer (RNFL) analysis in
glaucoma has been recorded as early as 1972, when Hoyt
and Newman initially reported RNFL atrophy in patients
with glaucoma (Hoyt and Newman, 1972), thus suggesting
RNFL thinning as a possible sensitive indicator of
glaucomatous damage. When glaucomatous damage begins, ganglion cell degeneration can occur in either diffuse
or focal forms. Diffuse atrophy of the nerve fibers is more
difficult to assess especially in early stages of the disease,
but focal axonal degeneration causes characteristic changes
in the appearance of the RNFL and is more easily
recognized. Dark slits or grooves appear among the
arcuate bundles approaching the optic disc superiorly
or inferiorly (Hoyt et al., 1973; Sommer et al., 1991).
Abnormal RNFL appearance may be sufficient evidence to
initiate glaucoma therapy since at least 25–35% retinal
ganglion cell loss is lost before detection of abnormalities in
automated visual field testing (Kerrigan-Baumrind et al.,
2000). Therefore, evaluation of RNFL has gained growing
interest amongst glaucoma specialists in the past few
decades.
OCT is a relatively new technology that provides highresolution cross-sectional imaging of the RNFL. A built-in
algorithm automatically calculates the RNFL thickness
when interpreting data acquired using the several RNFL
scan acquisition protocols.
3.2. RNFL and glaucoma
3.2.1. RNFL thickness protocols
There are innumerous ways to study the RNFL with
OCT, but a fixed diameter circular scan around the optic
disc has been used as standard for most of the investigators.
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The most used glaucoma scan acquisition protocols are the
RNFL thickness (3.4) and the fast RNFL thickness (3.4).
The former enables the acquirement of three circular scans
of 3.46 mm diameter around the optic disc, which can then
be averaged. The fast protocol acquires three circle images
of lower resolution sequentially in one single-scan acquisition session (Fig. 24). While the RNFL thickness acquisition protocol is composed of one circle with 512
A-scans/image and requires 1.28 s of scanning time, the
fast RNFL thickness comprises three circles of 256 A-scans/
image and requires 1.92 s.
Proportional circle and the RNFL thickness (2.27 " disc)
acquisition protocols enable one to account for the
Fig. 24. (A) Fundus image and corresponding B-scan of the RNFL
thickness 3.4-mm (circle diameter) acquisition protocol in the regular
mode (512 A-scans/image). (B) Fundus image and corresponding B-scans
of the fast RNFL thickness 3.4-mm (circle diameter) acquisition protocol.
Three images of 256 A-scans each are captured ‘‘simultaneously’’
(consecutively, at same scanning session).
variability of the optic disc size by multiplying the optic
disc radius by a factor to determine the final diameter
of measurement scanning circle (Fig. 25), thus RNFL
measurements taking place further away from disc margin
in larger discs. Most investigators prefer fixed circles rather
than proportional circles to analyze the RNFL thickness.
RNFL thickness measurements are displayed by quadrant,
clock hour and overall mean.
Compared with first generations OCT systems, the third
generation OCT allows high-density scanning protocols,
which produces images with high transverse pixel density,
thus resulting in better image quality. However, increase in
the image acquisition time may lead to measurement
artifacts due to eye motion. In a study comparing fast
RNFL scan acquisition protocol (256 A-scans/image) with
RNFL measurement using images of 512 A-scans, Leung et
al. (2004) concluded that the latter (high-density protocol)
has provided better sensitivity and stronger correlation
with visual function.
3.2.2. Reproducibility
Schuman et al. (1996) have suggested the use of 3.4-mm
diameter circle as the standard for RNFL OCT evaluation
after a reproducibility study involving 11 normal volunteers and 10 glaucomatous patients. Each subject underwent five repetitions of a series of scans on five separate
occasions. Each series consisted of three circular scans
around the optic nerve head (diameters of 2.9, 3.4 and
4.5 mm). Reproducibility was better in a given eye on a
given visit than from visit to visit. In addition, the internal
fixation was superior to external fixation regarding
reproducibility. The 3.4-mm circle was then suggested for
future studies because reproducibility was significantly
better at this circle diameter than at 2.9 mm. Additionally,
the 3.4-mm circle allowed measurement of NFL in a
Fig. 25. Four different RNFL thickness circle acquisition protocols. (A) Fixed 3.4 mm diameter circle. (B–D) After determining the disc radius (!1 mm)
three additional protocols enable to tailor de measurement circle accordingly: (B) nerve head circle (measurement circle was chosen to be 400 mm after the
disc margin), (C) RNFL thickness (2.27 " disc), and (D) proportional circle (1.5 was chosen as the multiplication factor).
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thicker area than 4.5 mm, what potentially permits a higher
sensitivity to subtle NFL defects.
Other reproducibility studies have demonstrated that
OCT RNFL measurements are reproducible for both
normal and glaucomatous eyes (Blumenthal et al., 2000;
Carpineto et al., 2003; Paunescu et al., 2004; Budenz et al.,
2005). Blumenthal et al. (2000) evaluated the reproducibility of OCT RNFL measurements in normal and
glaucomatous patients for a prospective instrument validation study. Only a modest contribution to variability was
found for session (1%), visit (5%), and operator (2%).
Budenz et al. (2005) studying the reproducibility of
standard and fast RNLF thickness scans found that both
scan acquisition protocols yields reproducible and comparable measurements in glaucoma as well as in healthy
individuals. The nasal quadrant showed more variations in
the measurements than other sectors.
According to Paunescu et al. (2004), the best reproducibility for RNFL measurements was found for dilated eyes
and scanning rate of 256 A-scans per image acquired in the
fast mode when compared to high-density scanning (512
A-scans per image) acquired in the regular acquisition
mode. Although increased density may cause a reproducibility problem, higher-density scanning protocols have
provided better diagnostic sensitivity in glaucoma detection
and a stronger correlation with visual function according
to Leung et al. (2004).
3.2.3. Diagnostic capability and progression evaluation
According to Schuman et al. (1995), RNFL measurements by OCT demonstrate a high degree of correlation
with functional status, as measured by visual field
examination. Neither cupping of the optic disc nor neural
rim area were as strongly associated with visual field loss as
was RNFL thickness in that study. RNFL, especially in the
inferior quadrant, was significantly thinner in glaucomatous
eyes than in normal eyes. Finally, it was found a decrease in
RNFL thickness with aging, even when controlling for
factors associated with the diagnosis of glaucoma.
In a retrospective observational case series study that
included 29 glaucoma patients, RNFL thickness measured
with OCT was topographically correlated with glaucomatous visual field defects measured with short-wavelength
automated perimetry (SWAP) (Sanchez-Galeana et al.,
2004). In a paper by Pieroth et al. (1999), OCT-enabled
focal defects detection with a sensitivity of 65% and a
specificity of 81%. OCT analysis of RNFL thickness in
eyes with focal defects showed good structural and
functional correlation with clinical parameters and allowed
identification of focal defects in the RNFL in early stages
of glaucoma (Fig. 26). By evaluating 64 eyes of glaucoma
or glaucoma-suspect individuals, Wollstein et al. (2005a)
have shown a greater likelihood of detection of glaucomatous progression by the OCT in comparison to standard
automated perimetry.
In another study, the mean RNFL thickness of 28 ocular
hypertensive eyes was compared with age-matched 30
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normal and 29 glaucomatous eyes using 3.4-mm diameter
scans (Bowd et al., 2000). Average RNFL thickness in
temporal, superior, nasal, inferior quadrants and total
average were obtained. Mean RNFL was significantly
thinner in ocular hypertensive eyes than in normal eyes,
more specifically in the inferior and nasal quadrants.
RNFL was significantly thinner in glaucomatous eyes than
in ocular hypertensive and normal eyes (total RNFL and
all quadrants).
In a study published in 2001, Bowd et al. (2001)
compared the abilities of scanning laser polarimetry
(SLP), OCT, SWAP, and frequency-doubling technology
perimetry (FDT) to discriminate between healthy eyes and
those with early glaucoma, classified based on standard
automated perimetry and optic disc appearance. In general,
areas under the receiver operating characteristics (ROC)
curve were largest for OCT parameters, followed by FDT,
SLP, and SWAP, regardless of the definition of glaucoma
used. The most sensitive OCT and FDT parameters tended
to be more sensitive than the most sensitive SWAP and
SLP parameters at the specificities investigated, regardless
of diagnostic criteria. Medeiros et al. (2004) using the
current commercial available versions of SLP (GDx-VCC),
third generation OCT, and Heidelberg retina tomograph
(HRT II), have demonstrated similar sensitivity results
among the best parameters of each equipment.
OCT RNFL thickness decreases with increasing RNFL
damage detected with red-free photography and visual field
(Soliman et al., 2002). The global average OCT RNFL
thickness correlated significantly with the photographic
total RNFL score. This study suggests the validity of OCT
measurements and its potential advantage for detection of
early cases of glaucoma. Leung et al. (2005a) published a
study evaluating the relationship between structure and
function in glaucoma. In this study, the Advanced
Glaucoma Intervention Study and the Collaborative Initial
Glaucoma Treatment Study scores as well as, the mean
deviation in decibel an unlogged 1/Lambert were used as
measures of visual function. Better correlations were
demonstrated between OCT RNLF measurements and
visual function than between GDx-VCC measurements
and visual function.
The RNFL thickness has also been measured in children
(Mrugacz and Bakunowicz-Lazarczyk, 2005; Hess et al.,
2005). In a study including 26 normal eyes and 26
glaucomatous eyes, Mrugacz and Bakunowicz-Lazarczyk
(2005) found that the mean RNFL thickness as well as the
inferior quadrant measurements was statistically thinner in
children with glaucoma than in healthy ones. In another
study, Hess et al. (2005) showed that both macular and
RNFL thickness were thinner in glaucomatous in comparison with healthy children.
OCT was used to measure macular and nerve fiber
layer thickness and to analyze their correlation with
each other and with glaucoma status (Guedes et al.,
2003). Both macular and RNFL thickness as measured by
OCT showed statistically significant correlations with
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Fig. 26. Fundus photography showing localized RNFL defects (arrows) in both eyes, which could also be identified by OCT using the RNFL thickness
average protocol (with normative data analysis). Glaucomatous damage was mild in the right eye, and moderate in the left eye.
glaucoma, although RNFL thickness showed a stronger
association than macular thickness.
Ishikawa et al. (2005) developed a software algorithm to
obtain automated segmentation measurements of retinal
layers in the macula. Four retinal layers were obtained and
the algorithm was capable to discriminate between
glaucomatous and normal eyes. In three layers (macular
nerve fiber layer, inner retinal complex, and outer retinal
complex), the measurements were statistically significantly
thinner in glaucomatous eyes than in normal eyes.
In another study involving macular measurements,
Leung et al. (2005b) found macular thickness measurements significantly reduced in glaucomatous patients.
However, peripapillary RNFL thickness measurements
provided greater power to discriminate between normal,
glaucoma-suspect and glaucoma eyes than macular
measurements. Wollstein et al. (2005b) also found the
RNFL measurement to provide better discrimination
between glaucomatous and normal individuals than
macular measurement. In another report, Wollstein et al.
(2004) show that the peripapillary RNFL measurements
have higher sensitivity and specificity than macular
measurements. New strategies to evaluate macular
thickness in relation to glaucoma detection, including
macular symmetry testing (Bagga et al., 2005), are under
development.
More recently, investigators have been trying to increase
the sensitivity and specificity of the OCT by adding
measurement information that this device provides rather
than analyzing isolated parameters (Medeiros et al., 2005;
Huang and Chen, 2005; Chen and Huang, 2005; Burgansky-Eliash et al., 2005). Medeiros et al. (2005) combining
selected optic nerve head and RNFL parameters obtained
larger area under ROC curve than using single parameters.
Huang and Chen (2005) compared several automated
classifiers to differentiate normal from glaucomatous eyes.
In this study, the Mahalanobis space showed better results
than linear discriminant analysis and artificial neural
network. In another study by Chen and Huang (2005), 21
parameters (optic nerve head and RNFL) were combined
to obtain a linear discriminant function. The use of linear
discriminant analysis increased the discrimination power
to differentiate glaucomatous and healthy individuals
in that study. Five classifier methods to discriminate
between glaucoma and healthy subjects were studied by
Burgansky-Eliash et al. (2005). In this study, the classifier
methods studied were linear discriminant analysis, support
vector machine, recursive partitioning and regression tree,
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generalized linear model and generalized additive model.
The largest area under ROC curve was obtained using
support vector machine, and the best discrimination
between advanced and early glaucoma was provided by
the generalized additive model.
3.2.4. Normative database
In spite of the good reproducibility and potential to
detect glaucomatous damage, the format of data presentation by initial versions of third generation OCT software
and absence of a normative reference restricted OCT
RNFL data interpretation and its use in clinical setting as a
routinely diagnostic tool. To address such particular issues,
a normative RNFL database to analyze patient’s data has
been made available within the last software package
(version 4.0) of third generation OCT systems. Nevertheless, normative reference analysis software for glaucoma
applications is not fully developed, and there is a scarcity of
age, refractive error, and mainly, race-specific normative
data upon which to compare eyes. The normative database
is based on 3.4-mm diameter circular scan measurements.
This might represent a potential source of error since a
fixed diameter does not account for the distance between
the measurement circle and the optic disc margin.
Considering the progressive decrease of the RNFL thickness with increasing distance from disc margin (Varma
et al, 1996), the disc size may interfere in RNFL thickness
measurements (Fig. 27). By using third generation OCT,
Savini et al. (2005) have demonstrated that RNFL
thickness increased significantly with an increase in optic
disc size, and this can be due to a shorter distance between
the scan and optic disc margin. New strategies have to be
developed to better evaluate RNFL thickness.
These ideas are in accordance with the findings of
Carpineto et al. (2003). These authors studied glaucomatous patients and a gender- and age-matched group of
normal subjects with three different circle diameter nerve
head programs: R ¼ 1.73 mm (3.4-mm diameter circle)
as well as 1.5R and 2.0R (optic nerve head scanning is
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performed after positioning an aiming circle whose
dimension can be adjusted to the optic disc size, and the
actual scan radius is greater than the aiming circle radius
by the designated R). For each option, variance components and intraclass correlation coefficients were determined. The total variance increased with circle diameter
and the intersubject standard deviation showed a tendency
to increase with radius in both groups. The RNFL
thickness decreased with increasing circle radius. Multiple
regression for intraclass correlation coefficient of RNFL
thickness showed that intraclass correlation coefficient was
higher for normal eyes and for scan protocol 1.5R than for
R ¼ 1:73 and 2.0R. The 1.5R option allowed RNFL
measurements in a thicker area than R ¼ 1:73 and 2.0R.
3.2.5. Future directions
By the use of the 3.4-mm circle scan acquisition protocol,
Williams et al. (2002) have defined a parameter called NFL
(50), which is the RNFL thickness value at which there is a
50% likelihood of a visual field defect with either
automated standard or FDT perimetries. RNFL layer
thickness analysis using this parameter demonstrated that
OCT might be clinically useful in identifying subjects who
have visual field loss. However, the positive predictive
value suggested that OCT might need higher resolution and
better reproducibility to enhance its sensitivity and
specificity for population screening.
Increase of the axial resolution may be needed to
improve OCT efficacy in detecting and following glaucomatous loss, but it is quite likely that refinements in the
actual software algorithm may be sufficient to increase the
specificity and sensitivity of this technology. According to
Jones et al. (2001), OCT measurements close to disc margin
underestimate RNFL thickness in approximately 37%. In
a study performed by Skaf et al. (2005), the OCT algorithm
to determine RNFL thickness is incorrect close to disc
margin up to approximately 400 mm resulting in underestimated RNFL measurements. This might happen
because retinal nerve fibers have a different orientation
Fig. 27. Fixed 3.4-mm circle and large optic discs. The measurement is performed closer to disc margin and values for RNFL thickness tend to be
overestimated.
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close to disc margin (fibers curve to form the optic nerve)
and/or the software may not be prepared with proper
landmarks for this region.
3.2.6. Additional considerations
OCT has demonstrated good reproducibility of measurements and capability to detect early glaucomatous damage.
A normative database has been incorporated to the last
version of the commercial available third generation OCT
system. Nevertheless, while the 3.4-mm fixed circle around
the optic disc remains as the standard protocol to analyze
RNFL thickness, improvement of the database is demanding. Some other new features such as disc size compensation as well as new measurement landmarks and scan
positions may be needed. The belief that optimized
acquisition protocols and an improved algorithm for
RNFL measurements, coupled with the current axial
resolution of third generation OCT systems, can offer an
extraordinary tool to glaucoma diagnostic and follow-up
seems quite reasonable.
Third generation OCT has superior resolution (o10 mm)
compared with other instruments currently available for
the same purpose. Some next generation ultrahigh-resolution OCT prototypes have even more axial resolution
(!2–3 mm) (Wollstein et al., 2005c). In addition, the
possibility to associate the ultrahigh-resolution with a
spectral/Fourier domain detection enables a dramatic
increase in image acquisition speed (Wojtkowski et al.,
2005) and potentially eliminates the motion problem
previously associated to high-density images.
4. Next generation OCT devices
Significant progress in the field of OCT retinal imaging
has been made since the third generation of OCT
instruments was introduced by Zeiss Meditec in 2002.
Since then a new instrument, which combines OCT with
scanning laser ophthalmoscopy has been introduced by
OTI in 2004 (Podoleanu et al., 2004). Also a new way of
scanning has been used in OCT instrumentation for threedimensional imaging presented by Laser Diagnostic
Technologies (Hitzenberger et al., 2003). Novel tools and
OCT measurement techniques have been developed in
research laboratories. Some of them may have significant
impact on the OCT retinal-imaging field in the future. The
most important developments are probably new light
sources enabling imaging with sub-micron axial resolution
(Drexler et al., 1999, 2001, 2003; Kowalevicz et al., 2002;
Fujimoto, 2003) and a novel high-speed OCT technique
called spectral OCT (Fercher et al., 1995; Hausler and
Linduer, 1998; Wojtkowski et al., 2002b). Spectral OCT is
based on ‘‘Fourier domain’’ detection, which allows
increasing the measurement speed more than 50 times
comparing to commercial OCT instrument (Nassif et al.,
2004; Wojtkowski et al., 2003).
In principle OCT is able to provide three-dimensional
information about the retinal morphology similar to other
tomographic methods including CT and MRI. However,
the speeds of commercially available third generation OCT
and combined SLO-OCT OTI instruments are insufficient
to measure full sets of three-dimensional data having a
large number of pixels per image in vivo. The highest
reported speeds for retinal OCT systems based on standard
OCT detection have been achieved by transverse scanning
with an acousto-optic modulator generating a highly stable
carrier frequency (Hitzenberger et al., 2003). This system
(Hitzenberger et al., 2003) can acquire cross-sectional
images of the retina almost five times faster than OCT 3.
The demonstrated system enables three-dimensional data
acquisition with a fundus field of view up to 151, 64 points
per axial scan, and 256 lines per cross-sectional image.
Such a low number of pixels prevents exact analysis of
cross-sectional information. In order to design threedimensional OCT instruments capable of collecting crosssectional images with pixel counts similar to third
generation OCT, the acquisition speed should be increased
by at least 50 times compared to the commercial unit. This
can be realized only by a significant redesign of the OCT
system. A recently demonstrated development is the novel
application of Fourier domain detection to OCT technology (Hausler and Linduer, 1998; Wojtkowski et al., 2002b).
This new method significantly improves the speed and
sensitivity of OCT instruments (Choma et al., 2003a;
de Boer et al., 2003; Leitgeb et al., 2003a).
One of the most important considerations for OCT
instruments imaging the laminar structure of the retina is
the axial image resolution. This parameter is determined by
the spectral bandwidth of the light source used in the OCT
instrument (Drexler, 2004; Fercher et al., 2003). In order to
improve the axial resolution, new broad bandwidth light
sources have been constructed and applied to OCT systems
(Drexler, 2004; Drexler et al., 1999). Application of these
light sources to the novel high speed OCT instruments
based on Fourier domain detection can provide a very
powerful tool for ophthalmic diagnostics in the future.
4.1. Spectral OCT instrument using Fourier domain
detection
Recently developed Fourier domain OCT imaging
techniques dramatically improve the sensitivity and imaging speed of OCT (Choma et al., 2003a; de Boer et al.,
2003; Leitgeb et al., 2003a). In Fourier domain OCT the
axial structure of an object (optical A-scan) is retrieved
from the interferometric signal detected as a function of the
optical frequency (spectral fringe pattern). Fourier domain
OCT detection can be performed in two complementary
ways: Spectral OCT (SOCT) using a spectrometer with a
multi-channel detector (Fercher et al., 1995) or Swept
Source OCT using a rapidly tunable laser source (Chinn
et al., 1997; Lexer et al., 1997; Yun et al., 2003). Spectral
OCT and swept source OCT are especially promising for
ultrahigh-resolution imaging because they overcome the
imaging speed limitations of standard OCT. Therefore, it is
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possible to use these techniques to form three-dimensional
maps of the macula and the optic disc (Nassif et al., 2004;
Wojtkowski et al., 2004a). In addition, the advantage of
providing direct access to the spectral fringe pattern
enables a wide range of novel applications. Direct access
to the spectral information and phase of the interference
fringes permits measurement of absorption (Leitgeb et al.,
2000), numerical compensation of dispersion (Cense et al.,
2004; Wojtkowski et al., 2004b), and numerical resolution
improvement (Szkulmowski et al., 2005). It was also
demonstrated that SOCT measurements have the advantage of high phase stability, which causes minimum
detectable flow velocity. This is 25 times less than what
has been measured using standard OCT and results in
100 mm/s–5 mm/s of measurable flow velocities (Leitgeb
et al., 2003b, 2004b; White et al., 2003).
The first ophthalmic application of single-scan spectral
OCT was the measurement of eye length (Fercher et al.,
1995). Demonstration of biomedical OCT imaging of
human skin in vivo using Fourier domain detection was
presented in 1996 (Hausler and Linduer, 1998). The first
retinal and anterior chamber imaging using spectral OCT
was reported in 2002 (Wojtkowski et al., 2002b). Continuation of this work resulted in the demonstration of the
first high-speed retinal imaging obtained using a spectral
OCT system with 10 mm axial resolution and acquisition
time of 8 ms for a 128 transverse pixel image (Wojtkowski
et al., 2003). Application of the line scan CCD camera,
enabling high acquisition speeds of up to 29,000 axial scans
per second (Nassif et al., 2004). This represents an
approximately 70 " improvement in imaging speed compared to third generation OCT, which only operates at 400
axial scans per second.
One of the first experiments with combined Fourier
domain and ultrahigh-resolution OCT was performed in
2003, and examples of ophthalmic imaging with 3 mm axial
resolution were published in 2004 (Wojtkowski et al.,
2004a). Other groups have also recently demonstrated
ultrahigh-resolution imaging using SOCT. A resolution of
3.5 mm in the retina was achieved at acquisition rates of
15,000 axial scans per second (Cense et al., 2004). An image
resolution of 2.5 mm was demonstrated at 10,000 axial
scans per second (Leitgeb et al., 2004a). The best axial
resolution in the retina to date, 2.1 mm, was achieved using
high-speed acquisition rates of 16,000 axial scans per
second by the group at MIT (Wojtkowski et al., 2004b).
The first demonstration of ophthalmic ranging by swept
source OCT was done in 1997 (Lexer et al., 1997).
Recently, a group from Wellman Laboratories demonstrated a new high speed tunable laser operating with a
central wavelength of 1310 nm enabling imaging at the rate
of 15,600 A-scans per second (Yun et al., 2003). The
absorption of water at 1310 nm prevents the application of
this laser to retinal imaging. A swept source OCT system
using 800 nm wavelength suitable for retinal imaging has
not been reported to date. Therefore, in this contribution,
the potential of the new Fourier domain OCT detection for
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retinal imaging will be demonstrated by a spectral OCT
instrument.
4.1.1. Standard-resolution retinal imaging with high-speed
spectral OCT
The measurement speed of a third generation OCT
instrument is less than 400 axial scans per second.
Therefore, this instrument needs more than 1 s (approximately 1.92 s) to acquire an OCT image with 512 optical
A-scans. One-second measurements by regular OCT
suffer from motion artifacts in the obtained cross-sectional
images (Fig. 28). These artifacts can be corrected
by automated numerical alignment of adjacent optical
A-scans. This procedure can generate errors in the presence
of discontinuities in the retinal structure caused by
pathological changes, or that are naturally existent in the
region of the optic disc. Also, these methods ‘‘flatten’’
cross-sectional images and information about the true
topography of the retina is automatically lost. Fig. 28
shows a comparison of cross-sectional images of normal
macula taken by standard third generation OCT and the
new spectral OCT instrument based on Fourier domain
detection. In both cases the axial resolution is 10 mm. The
motion artifacts in the presented third generation OCT
image required numerical correction whereas the spectral
OCT cross-sectional image, measured in only 0.17 s, did
not require any motion correction. The speed advantage of
the spectral OCT instrument enables the acquisition of
cross-sectional images with many more optical A-scans.
The cross-sectional image of the macula presented in
Fig. 28(c) is reconstructed from 4000 A-scans. An increased
number of A-scans and a slightly increased transverse
resolution can dramatically improve the quality of SOCT
images. Fig. 29(a) shows the cross sectional SOCT image of
the retinal ‘‘panorama’’ measured horizontally from the
fovea to the inferior part of the optic disc. Fig. 29(b) shows
another cross-sectional image taken across the fovea of the
same subject. Both of these images are reconstructed from
2500 A-scans with an axial resolution of 10 mm. Here the
nerve fiber layer, ganglion cell layer, inner and outer
plexiform layers, inner and outer nuclear layer, external
limiting membrane, junction between the photoreceptor
inner and outer segments, and retinal pigment epithelium
are all well visualized and delineated more clearly than in
standard third generation OCT.
Another important advantage of high-speed imaging is
the possibility of real time observation of cross-sectional
images measured in vivo. This makes it more comfortable
for the operator and can shorten the total examination
time. It is also possible to choose the region of interest and
the scanning range during the examination, which can help
in imaging small focal pathologic changes present outside
the macula or optic disc regions. Furthermore, the realtime imaging performed by the spectral OCT instrument
enables observation of dynamic changes present in the
retina. In Fig. 30 the set of real-time spectral OCT crosssectional images of the peripheral part of the human optic
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Fig. 28. Comparison of standard-resolution third generation optical coherence tomography (OCT) (Stratus OCT) and spectral OCT images. (A) Stratus
OCT image of macula contains 512 axial scans (A-scans) and was acquired in 1.3 s with axial resolution of 10 micrometers. (B) Stratus OCT image after
numerical correction of motion artifacts. (C) spectral OCT image of macula contains 4000 A-scans and was acquired in 0.17 s with axial resolution of
10 mm.
disc is presented. Each frame consists of 128 A-scans with
512 samples per A-scan. The exposure time is 32 ms per
A-scan. The transverse scan was performed superiorly to
the optic disc cup area in order to examine blood vessels.
The region indicated by the arrow in the last frame varies
during the measurement, whereas the rest of the image is
stable. This is most likely caused by a pulsation of the
blood vessels.
The most important advantage of high-speed imaging
with spectral OCT is that this technique enables threedimensional data collection similar to other tomographic
techniques. Standard third generation OCT devices use
specific imaging protocols in order to obtain quantitative
information about full retinal thickness, retinal nerve fiber
layer thickness, and optic nerve head parameters. Spectral
OCT instruments enable the acquisition of all this
information with the use of one scanning protocol—the
raster scan, which provides three-dimensional volumetric
data of retinal structure (Nassif et al., 2004; Wojtkowski
et al., 2004a). Additionally, raster scanning simplifies
data processing and reconstruction of cross-sectional
images rendered with arbitrary orientations. For spectral
OCT, raster scanning also can provide combined profilometric and cross-sectional information that is important
for quantitative analysis of optic nerve head parameters
or nerve fiber layer thickness. Fig. 31 shows examples of
the imaging and processing of three-dimensional retinal
data. In Fig. 31(a), the volume rendering of the optic
disc region is shown. Using software similar to that used
for MRI enables segmentation of specific intraretinal
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Fig. 29. Standard-resolution spectral optical coherence tomography retinal imaging with high quality: (A) cross-sectional image of the retinal
‘‘panorama’’ measured horizontally from temporal to nasal along the fovea to the inferior part of the optic disc, (B) cross-sectional image of the fovea
measured in the same eye. Both images contain 2500 axial scans. Red square shows approximately the region where the bottom image was taken.
layers from the three-dimensional data set (Fig. 31(b)).
Three-dimensional imaging also has the advantage of
reconstructing fundus view (Wojtkowski et al., 2004a)
similar to this obtained by scanning laser ophthalmoscopy.
The OCT fundus image is generated by summing the
reflectivities of successive layers along the axial direction.
The SOCT fundus image enables precise registration of
OCT cross-sections with fundus photography. Fig. 32
shows the fundus image created from a three-dimensional
data set acquired using standard-resolution spectral OCT.
The pattern created by the blood vessels is clearly visible
and can be used to correlate the OCT data with the fundus
photograph.
4.1.2. High-resolution retinal imaging with high-speed
spectral OCT
The first demonstration of ultrahigh-resolution retinal
imaging with 3-mm resolution using a standard OCT system
was demonstrated in 1999 by Drexler et al. This represents a
factor of five- to ten- fold resolution improvement over
standard third generation OCT instruments, which has
10 mm axial resolution. This technology has already been
implemented in two clinical systems constructed at MIT
(Drexler et al., 2001; Ko et al., 2005) and the University of
Vienna (Drexler et al., 2003). Both of these systems use
femtosecond titanium:sapphire (Ti:Sa) lasers as light sources.
Clinical results obtained with these instruments demonstrate
that ultrahigh-resolution OCT can greatly improve the
visualization of retinal architectural morphology, and
promise to improve the accuracy of quantitative morphometric measurements. Ultrahigh-resolution OCT enables
the detection of individual retinal layers such as the ganglion
cell layer, inner and outer nuclear and plexiform layers,
as well as the photoreceptor and RPE morphology,
which are difficult to visualize with standard-resolution
OCT (Drexler et al., 1999, 2001, 2003; Ko et al., 2004). In
contrast to commercially available OCT instruments,
ultrahigh-resolution OCT can reveal changes in retinal
morphology associated with retinal disease, such as photoreceptor integrity or impairment (Drexler et al., 2003;
Ko et al., 2004).
Ultrahigh-resolution OCT has not yet been commercialized because of the high cost of femtosecond lasers. The
recent introduction of compact broadband semiconductor
light sources will enable widespread use of ultrahighresolution OCT instruments. The cost of the broadband
superluminescent diode is approximately 5 times lower
than the cost of the full Ti:Sa laser system. These light
sources are based on two or more superluminescent diode
modules combined by single mode fiber couplers. The
application of broadband semiconductor light sources to
OCT ophthalmic imaging has been demonstrated in 2004
(Ko et al., 2004). The high-quality retinal images obtained
by a spectral OCT system using combined superluminescent diode modules has been also presented in 2004 (Cense
et al., 2004).
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Fig. 30. Real-time spectral optical coherence tomography observation of dynamic processes in the retina: (A) the set of cross-sectional images measured
with 8 frames per second; (B) cross-sectional image of optic disc region with indicated region of interest.
Fig. 33 shows the cross-sectional SOCT images of the
macula and optic disc measured with a high axial
resolution of 4.5 mm. The delineation of retinal layers in
the presented image is much clearer than that of standardresolution imaging. The improvement is especially visible
in the retinal pigment epithelium, ganglion cell layer, and
photoreceptor layer. The high number of collected A-scans
helps to decrease the noise level and improves the
continuity of retinal layers. The performance of automated
segmentation algorithms for thickness measurements and
layer identification can also be improved. The collection of
three-dimensional ultrahigh-resolution SOCT data enables
the quantitative analysis of all major retinal layers,
including photoreceptor layer details such as the external
limiting membrane (ELM), junction between the inner and
outer segments (IS/OS), and the RPE. Fig. 34 shows an
example of the full thickness retinal map and a thickness
map of the part of the photoreceptor layer from IS/OS to
RPE. This analysis has great potential in objective
measurements of progression in various macular diseases.
Simultaneous increase of the coverage and resolution,
guaranteed by three-dimensional ultrahigh-resolution highspeed SOCT, will enable analysis of small focal pathological changes that can be missed by standard OCT
techniques. This can effectively improve the capability of
OCT technology to diagnose early pathological changes
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Fig. 31. Three-dimensional spectral optical coherence tomography imaging with standard resolution: (A) volume rendering of optic disc region,
(B) segmentation of intraretinal layers in macular region; NFL-nerve fiber layer, OPL-outer plexiform layer, IS/OS-junction between inner and outer
segments of photoreceptors, and RPE- retinal pigment epithelium.
Fig. 32. Three-dimensional spectral optical coherence tomography (OCT) imaging with standard resolution: (A) fundus view (400 horizontal points, 300
vertical points) reconstructed from the spectral OCT data contains 300 cross-sectional images; (B) two cross-sectional images from the three-dimensional
set of data. The location of each cross-sectional image is perfectly registered relative to the fundus view.
and can help in understanding the pathogenesis of retinal
diseases.
4.2. Additional considerations
Combined ultrahigh resolution and Fourier domain
detection techniques can give unprecedented improvement
of the capability of OCT systems for retinal imaging.
However, the advantages of the new spectral OCT
technique cannot be easily realized as a commercial clinical
instrument. Technical problems still exist, which impede
the introduction of spectral OCT instruments to ophthal-
mology clinics. For example, images obtained by SOCT
can suffer from coherent noise artifacts and conjugate
images (Wojtkowski et al., 2002a, b), which decrease the
effective axial measurement range and can lead to
misinterpretation of resultant tomographic images. These
artifacts cause ‘‘folding’’ of the OCT cross-sectional image
if the optical distance of the structure to be imaged is
higher than the effective measurement range. It has been
shown that these unwanted effects can be eliminated by
phase-shifting methods (Choma et al., 2003b; Targowski
et al., 2004, 2005; Wojtkowski et al., 2002a). These
techniques require the collection of multiple signals from
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Fig. 33. High-resolution spectral optical coherence tomography imaging: (A) cross-sectional image of macula, and (B) cross-sectional image of optic disc.
Both images contain 10.000 axial scans and were acquired in 0.43 s with axial resolution of 4.5 mm.
the same region taken with an additional selected phase
shift in the reference arm, with the condition that the object
is stationary between the measurements to within a fraction
of micrometer. The latter condition makes these phaseshifting methods hard to apply for clinical practice.
Another unsolved problem in spectral OCT is the drop of
sensitivity with increase of imaging depth (Hausler and
Linduer, 1998; Wojtkowski et al., 2002b). This effect is
especially significant in ultrahigh-resolution SOCT imaging
where the digitalization must be much finer than in
standard-resolution OCT. This problem is fundamentally
associated with the detection performed by a spectrometer
(Hausler and Linduer, 1998) and it is much less severe in
swept source OCT (Yun et al., 2003). Also the swept source
OCT gives more flexibility in controlling of the axial scan
parameters, which are fixed in spectral OCT (Wojtkowski
et al., 2004b). The future of the clinical application of
Fourier domain detection to retinal imaging will depend
on how the problems mentioned above will be solved,
as well as on the development of high-speed tunable laser
technology, which will enable the application of swept
source OCT to retinal imaging.
5. Concluding remarks
The introduction of OCT in ophthalmology represents a
definitive change in the way doctors understand and treat
several diseases affecting the retina. It is quite likely as well,
that the role of OCT as a method to diagnose and manage
glaucoma will be further defined in the near future.
Understanding of the basic principles in which OCT relays
on is essential to understand its actual limitations and to
use this technology with wisdom. We have already learned
a lot with data provided by first generations of OCT, and
there is much more to learn with forthcoming data from
numerous ongoing studies worldwide that, presently, are
using third generation OCT systems. A huge leap forward
in improving OCT imaging performance is expected to
occur within the next few years (or should we say months?)
with the commercial availability of next generation OCT
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Fig. 34. Three-dimensional high-resolution, spectral optical coherence tomography imaging: (A) reconstruction of the OCT fundus view, (B) crosssectional image with delineated automatically segmented layers, (C) full retinal thickness map, and (D) thickness map of outer segments of photoreceptors;
ILM-inner limiting membrane, IS/OS-junction between inner and outer segments of photoreceptors, and RPE-retinal pigment epithelium.
devices. One should say that three-dimensional, highspeed, ultrahigh-resolution retinal assessment is just
‘‘around the corner’’.
Acknowledgments
M.W. thanks Prof. Andrzej Kowalczyk and members of
Medical Physics Group from Nicolaus Copernicus University in Torun especially to Iwona Gorczynska and Anna
Szkulmowska, and Prof. James G. Fujimoto from Massachusetts Institute of Technology, Cambridge, MA, USA
and members of his group: Vikas Sharma, Aurea Zare,
Vivek Srinivasan, Tony Ko and Mariana Carvalho. R.A.C.
and M.W. includes special thank to Yijun Huang, and to
Robert Huber and Robert Zawadzki, respectively, for
creative discussions.
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