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194 9 Tissue Viability Imaging
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197
10
Optical Microangiography: Theory and Application
Ruikang K. Wang and Hrebesh M. Subhash
10.1
Introduction
In physiology, the term microvascular blood perfusion refers to the process involved
in the nutritive blood delivery to the tissue’s capillary bed, which is vital for
homeostasis, and thereby thesurvival of an organ.Noninvasive and chronic imaging
of blood flow within microcirculatory tissue beds is required in many basic research
and clinical circumstances including cancer diagnosis and therapy, arteriosclerosis,
therapeutic angiogenesis, vasospastic conditions, reconstructive surgery and also
the for development and implementation of antivascular strategies. Over the past
decade, a number of emerging technologies have become available for the study of
microvascular blood flow, including photoelectric plethysmography [1, 2] thermal
[3] and radioisotope [4, 5] clearance, orthogonal polarization spectral imaging [6, 7],
videophotometric capillaroscopy [8, 9], and Doppler ultrasound [10]. Some of these
methods traumatize the tissue, which may seriously disturb the microcirculation;
others have practical limitations in clinical use. None of these methods, however,
have fulfilled the requirements of being noninvasiveness and applicable to a
large number of tissues as well as offering the possibility of recording the tissue
perfusion continuously or visualizing the results in terms of three-dimensional
perfusion maps. Methods for clinical studies of the blood flow in small vessels
should therefore preferably be noninvasive, versatile, and easy to use.
In general, microvasculature imaging is a challenging task because of the
requirement of relatively high spatiotemporal resolution and sensitivity to image
small diameter of the blood vessels. Most of the available methods that fulfill
these conditions are based on optical measurement technologies such as intravital
confocal microscopy, laser Doppler technique, infrared thermography, optical
intrinsic signal imaging, photoacoustic imaging (PAI) and phase-resolved Doppler
optical coherence tomography(PRDOCT), and so on. Intravital confocal microscopy
uses a fluorescence microscope to image various molecular and cellular processes
in vivo with high resolution. However, intravital microscopy is a time-consuming
invasive procedure, and the imaging depth is limited to a few hundred microns
in highly scattering specimens [11–13]. The laser Doppler technique uses the
Microcirculation Imaging, First Edition. Edited by Martin J. Leahy.
2012 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2012 by Wiley-VCH Verlag GmbH & Co. KGaA.
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198 10 Optical Microangiography: Theory and Application
frequency shift produced by the Doppler effect to measure blood flow. This
technique is capable of noninvasive and continuous recording of blood perfusion
in tissue. A major limitation of laser Doppler technique is its inability to image
tissue deeper than 1 mm [14, 15]. Moreover, laser Doppler is not able to measure
flow in absolute units (i.e., milliliters per minute), thus it often uses the arbitrary
unit of flux, which is the product of concentration of moving blood cells and
the mean velocity of those blood cells. Infrared thermography graphically depicts
temperature gradients over a given body surface area. Generally, an increase in
the blood flow can be related to a rise in temperature due to increased metabolic
activity in the highly vascular region [16, 17]. This approach has lower sensitivity
because a number of physiological changes involved with increased blood flow do
not necessarily indicate pathology [16]. Infrared thermography is generally used
in conjunction with other imaging techniques such as laser Doppler technique
and mammography [16]. Optical intrinsic signal imaging is another imaging
modality with very high spatial and temporal resolution, but which is limited to
superficial two-dimensional mapping and is invasive in nature [18]. PAI, based
on thermoacoustic phenomena resulting from the strong light absorption of
blood and the subsequent thermoelastic expansion, has been reported to map
vascular structures deep within the brain of small animals [19, 20]. However,
the spatial (∼100 µm) resolution of this approach is limited by the viscoelastic
filtering of higher acoustic frequencies by the tissue. Moreover, obtaining blood
flow information is difficult, if not impossible, with this method. PRDOCT is an
alternative low-coherence interferometric (LCI) technique to extract depth-resolved
velocity information of blood flow in functional vessels within the tissue beds.
Although this method is of high resolution and high sensitivity to the blood flow,
its imaging performance is greatly deteriorated by the characteristic texture pattern
artifact, which is caused by optical heterogeneity of the sample [21], and the phase
instability that is caused by the sample motion as well as system noise artifacts [22].
Optical microangiography (OMAG) [23] is a recently developed imaging method,
capable of resolving 3D distribution of dynamic blood perfusion at the capillary level
within microcirculatory beds in vivo. The imaging contrast of blood perfusion is
based on the endogenous light scattering from the moving blood erythrocytes in the
blood vessels; thus no exogenous contrasting agents are necessary. This is achieved
by efficient separation of the moving scattering elements from the static scattering
ones within tissue through the OMAG hardware associated with mathematical
analysis of the optical scattering signals emerging from an illuminated tissue
sample. The basic principle of OMAG is based on Fourier domain optical coherence
tomography (FDOCT) [24], an LCI technique, which is now becoming a noninvasive
clinical tool for high-resolution ophthalmic imaging of the human eye.
10.2
Optical Coherence Tomography
The development of OMAG has its origin in FDOCT, which is a variant of
optical coherence tomography (OCT), a well-established LCI technique for imaging
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10.2 Optical Coherence Tomography 199
biological tissues. LCI is a powerful technique for measuring the magnitude and
echo-time delay of backscattered light with very high sensitivity, which was first
described by Sir Isaac Newton. In principle, OCT is an optical analog to clinical
ultrasound. In OCT, the temporally gated optical pulse remitted from scattering
sites within the sample is localized by LCI [25– 30]. This is typically achieved with a
Michelson interferometer. The sample rests in one arm of the interferometer, and
a scanning reference optical delay line is in the other arm. In LCI, light interferes
at the detector only when light reflected from the sample has an optical path length
that matches with that of light reflected from the scanning reference mirror (RM).
A single scan of the RM thus provides a one-dimensional depth reflectivity profile
of the sample. Two-dimensional cross-sectional images are formed by laterally
scanning the incident probe beam across the sample. The reconstructed OCT
image is essentially a map of the changes of reflectivity that occurs at internal
interfaces, similar to the discontinuities in acoustic impedance in ultrasound
images.
10.2.1
Principle of OCT
A schematic of a time domain fiber optics based OCT setup is shown in Figure 10.1.
The OCT system comprises a broadband light source emitting light of high spatial
and low temporal coherence, which is coupled into a 2 × 2 fiber optics based
Michelson interferometer. The Michelson interferometer divides the light beam
and directs it into two arms of the interferometer. The sample arm beam directs
into the object to be analyzed. It usually contains collimating optics, enabling
formation of a narrow beam, which penetrates the object. In order to reconstruct
two-dimensional cross-sectional images of the object, the beam is galvanometrically
scanned across the sample surface. Light backscattered or reflected from the various
structures returns to the interferometer and is brought to interference with light
reflected back from the RM, which scans back and forth through the required
depth of imaging. The standard fiber-optics Michelson interferometer is not the
most efficient design for practical implementation, because a major disadvantage
of this configuration is that the DC signal and intensity noise generated by the
light from the reference arm add to the interference signal. In order to eliminate
this problem, an alternative configuration called balanced heterodyne configurations
as shown in Figure 10.1a has been commonly used, in which these background
noise components are canceled by subtracting the photocurrents generated by two
photodetectors. Then the resulting interfering light is detected by a photodiode
(PD). Figure 10.1b shows the relative target positions in the eye, and Figure 10.1c
shows the raw interferograms (A-scan) that are obtained by scanning the RM and
correspond to the different structural features of the ocular medium. Figure 10.1d
shows the reference-arm-signal-subtracted interference signal from the output of
the balanced detector. In the preceding step, the interferograms are amplified and
backed up with a band pass filter tuned to the Doppler frequency, often called
the ‘‘carrier frequency,’’ which is related to the scanning speed of the RM. This
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200 10 Optical Microangiography: Theory and Application
Target positions in eye
Detected OCT signal with
reference signal
Sample
reflectivity
profile
Detected OCT signal without
reference signal
Envelope detected OCT signal
AL
AC
PL
PC
Target positions in eye
DC offset
Relative position of
reference arm / time
0
Detector
response
(AC + DC part)
(a)
(b) (c)
(d) (e)
Relative position of
reference arm / time
Relative position of
reference arm / time
0
Envelope
of detector
response
Detector
response
(AC part)
Amplifier
Envelope
detector
A/D converter
Computer
Reference
z
50/50
Sample
x − y
Differential
detector module
+
−
Broad band
source
Σ
Optical
circulator
Figure 10.1 (a) Schematic of a typical fiber-optics-based
time domain OCT setup, (b) reflectivity profile of target in
the ocular medium, assuming there exists 4 interfaces: AC,
PC, AL, and PL (c) detected interference signal by the pho-
todetector, (d) detected signal with reference signal filtered
out, and (e) demodulated and envelop-detected OCT signals.
procedure helps to eliminate extraneous signals arising from background light.
Then, for the next scan of the RM, the probing beam is shifted to an adjacent
position, and so on, to yield a set of consecutive A-scans. These A-scans are then
combined into a single picture to form a cross-sectional image of the object, the
B-scan. Three-dimensional, volumetric data sets can be generated by acquiring
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10.2 Optical Coherence Tomography 201
sequential cross-sectional images by scanning the incident optical beam in a raster
pattern.
In contrast to standard microscopy, OCT can achieve fine axial resolution
independent of the beam focusing and spot size. The axial image resolution in
OCT is determined by the measurement resolution for echo-time delays of light.
The axial resolution of an OCT is an important specification of an OCT system,
and in many biomedical applications, high axial resolution is often required to
distinguish different cellular ultrastructures. The axial resolution of OCT is defined
as the full width half maximum (FWHM) of the source coherence length l
c
. For a
source with a Gaussian spectral distribution, the axial resolution is given by
z =
2ln2
π
c
v
=
2ln2
π
λ
2
λ
≈ 0.44
λ
2
λ
(10.1)
where z and λ are the FWHM of the autocorrelation function and spectralwidth,
respectively, and λ
0
is the central wavelength of the light source [31]. It can be seen
that broadband light sources are required to achieve high axial resolution, as the
axial resolution is inversely proportional to the spectral width of the light source.
The transverse resolution in OCT imaging is the same as in optical microscopy and
is determined by the diffraction-limited spot size of the focused optical beam. The
diffraction-limited minimum spot size is inversely proportional to the numerical
aperture (NA) or the focusing angle of the beam. The lateral resolution x can be
written as
x =
4λ
π
f
d
(10.2)
where f is the focal length of the objective lens and d is the 1/e
2
Gaussian beam
wrist at the objective lens. It can be seen from the above equation that high lateral
resolution can be achieved by using a large NA to decrease the spot size. However,
for the selection of optics, there is a trade-off between the lateral resolution and the
imaging depth. A higher lateral resolution leads to a decrease in the depth of focus,
or confocal parameter b, which is twice the Rayleigh range
2z
R
= b =
πx
2
2λ
(10.3)
The Rayleigh range gives the distance from the focal point to the point where the
light beam diameter has increased by a factor of
√
2. This effectively limits the
scanning range of the OCT, different from the working range of the scanning
reference delay line, as it is the range over which lateral resolution is maintained.
In OCT, the coherence-gated information about the elementary volume of the
scatters within the obscuring scattering specimen can be obtained from either
the time domain measurement (TD-OCT) or the frequency domain (FD-OCT)
[24, 31] measurement. As a variant of coherence domain variant interferometric
imaging modality, FD-OCT has been widely attracted in the biomedical imaging
field because of its higher sensitivity and imaging speed compared to conventional
TD-OCT. The principle of FD-OCT relies on the transformation of the OCT
time-varying signal along the optical axis, termed the A-scan, into the frequency
domain.
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202 10 Optical Microangiography: Theory and Application
10.2.2
Frequency Domain OCT (FD-OCT)
The basic physics of FD-OCT is based on the inverse scattering theorem. According
to Wiener– Khintchine theorem, the spectral power amplitude of the backscattered
wave equals the Fourier transform (FT) of the axial distribution of the object scat-
tering potential. FD-OCT has the advantage that the full sample depth information
is obtained in a parallel manner such that no moving parts are necessary. On
the basis of implementation, the FDOCT can be divided into two classes, spectral
domain optical coherence tomography (SD-OCT) and swept-source optical coher-
ence tomography (SS-OCT) [32]. In SD-OCT, the optical frequency components
are captured simultaneously with a dispersive element and linear detector; on
the other hand, in SS-OCT, the optical frequency components are captured by
a single detector in a time-encoded sequence by sweeping the frequency of the
optical source. Recent studies have shown that FD-OCT can provide signal-to-noise
ratio (SNR) that is more than 20 dB better than that provided by the conventional
TD-OCT.
The OMAG imaging modality can be implemented either using the SS-OCT
or the SD-OCT technique. However, at present, we implemented the OMAG
imaging modality based on the SD-OCT technique. A typical implementation of
fiber optics based SD-OCT setup is shown in Figure 10.2a. The backscattered
low-coherence light is mixed with a reference beam by the 2 ×2 fiber-optics-based
Michelson interferometer, then the grating-based spectrometer at the output of
the interferometer separates each spectral component detected using a linear array
detector. The interference signal detected by the linear detector is expressed as
I(k) = I
S
(k) +I
R
(k) +2
I
S
(k)I
R
(k)
n
α
n
cos
2kz
n
(10.4)
where I
R
(k) and I
S
(k) are the wavelength-dependent intensities reflected from the
reference and sample arms, respectively, and k is the wave number. The third
term on the right-hand side of Eq. (10.4) represents the interference between the
backreflected lights from the sample and reference arm. α
n
is the square root of
the sample reflectivity at depth z
n
. In order to reconstruct the depth information, the
spectrum is inverse Fourier transformed, which yields the following convolution:
FT
−1
[I(k)]
2
=
2
(z) ⊗
I
R
δ(z) +
n
I
S,n
δ(z) +
n
α
2
n
δ(z − z
n
)
+
n
α
2
n
δ
(
z +z
n
)
(10.5)
where Γ (z) represents the envelope of the coherence function. The first and second
terms on the right-hand side of the Eq. (10.42) describe the autocorrelation (or
self-interference) of the reference signal and sample signal, respectively. The third
and fourth terms are due to the interference of backreflected beam from the
reference and sample surfaces and its complex conjugates. The SD-OCT detects
the spectrally resolved interference signal with a spectrometer that consists of a
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10.2 Optical Coherence Tomography 203
Sample
reflectivity
profile
Spectral
amplitude
Spectral
amplitude
Amplitude
k-space z-space
AL PL
AC
Mirror image
(e)(d)
(b)
(a)
(c)
λ-space
AL
PL
AC
PC
PC
Target positions in eye
CMOS
camera
COMP
L1
DG
PC
OC
FC
PC
L4 L5 RM
L2
L3
X-scan
PC
SLD
LASER
Target positions in eye Detected spectral domain signal
Spectrum with ground substation &
λ to K-space mapping
Fourier transformed spectral
domain signal
Y-scan
Eye
Figure 10.2 (a) Experimental schematic of a FDOCT setup,
(b) reflectivity profile of anterior chamber of an eye, (c) de-
tected spectral interferogram by the camera (A-scan), (d)
remapped spectral interferogram in k-space with background
subtraction, and (e) Fourier transformed spectrum.
high-efficiency diffraction grating (DG) and a high-speed line camera. Figure 10.2b
shows the reflectivity profile of the different target positions in the ocular medium,
and Figure 10.2c shows the intensity spectrum detected by the camera. In order
to suppress autocorrelation, self-cross-correlation, and camera noise artifacts, all
the spectral interferograms in each slice along the x-direction (B-scan) were
first ensemble-averaged at each wavelength to obtain a reference spectrum. This
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204 10 Optical Microangiography: Theory and Application
back ground spectrum was then subtracted from each A-scan. However, since
the FT relates the physical distance (z) with the wave number (k = 2π/λ), the
spectra obtained with the SD-OCT spectrometer are not necessarily evenly spaced
in k-space. In order to obtain a proper depth profile, the subtracted spectral
interferograms are then remapped from λ-space to k-space by using the spline
interpolation method, as shown in Figure 10.2d. Owing to the Fourier relation
(Wiener–Khintchine theorem between the autocorrelation and the spectral power
density), the depth-resolved information can be immediately reconstructed by a
Fourier transformation from the remapped spectra, without movement of the
reference arm, as shown in Figure 10.2e.
For a Gaussian source centered at λ
0
with a FWHM bandwidth λ,thecomplex
coherence function is described by Eq. (10.1). The depth range that can be probed
with an SD-OCT is dependent on the spectrometer resolution and the detector size
(number of pixels). For a conventional SD-OCT system, the maximum imaging
depth is defined as
l
max
=
1
4n
λ
2
0
λ
S
N (10.6)
Where n is the refractive index of the medium, λ
0
is the center wavelength of the
detected spectrum, λ
S
is the spectrometer bandwidth, and N is the number of
pixels of the camera. For ambiguity-free image, this depth range should be doubled.
The term
(
λ
S
/N
)
−1
can be seen as the inverse of the spectral resolution power
δλ
−1
of the detecting spectrometer and is proportional to the coherence length of
the detected spectral channel, which is responsible for one of the main drawbacks
of SD-OCT, which is the signal decay observed for structures far away from the
relative zero-delay.
10.2.3
Doppler OCT
Doppler optical coherence tomography (DOCT) or optical Doppler tomography
(ODT) is the functional extension of OCT, which can permit quantitative imaging
of fluid flow in highly scattering specimens [33 –38]. The technique is similar
to Doppler velocimetry. However, Doppler velocimetry suffers from imprecise
imaging due to the long coherence length of the light source used, which causes
interference of the static and Doppler-shifted components of light over a long
optical path. The low-coherence gating property of OCT overcomes this problem,
permitting quantitative imaging of fluid flow in highly scattering media, such as
monitoring in vivo blood flow beneath the skin. In DOCT, the velocity resolution
depends on detection electronics, scan angle, and acquisition time. Reported flow
velocity resolutions are in the region 10 –100 µms
−1
; however, recent development
in Fourier domain Doppler optical coherence tomography (FD-DOCT) has shown
that a velocity resolution of just a few micrometers per second may be achieved
[39–46]. The DOCT can provide 3D tomographic map and velocity profile of blood
flow in tissue, which attracted a number of biomedical applications, for example,
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