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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_3921_Библиотеки_им_академика_М_И_Перельмана
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10.3 Optical Microangiography (OMAG) 235
The static signal, Is(k,x), the low frequency part, was reconstructed following the
theory described above. An ideal simulation sample, Iideal(k,x), with no optical
heterogeneity could be achieved by Eq. (10.49). Using a frequency synthesizing
method, the flow signal, If(k,x), extracted from the original fringe data by applying
a high-pass filter at each wavelength, and the static signal, extracted from the
ideal simulation sample by applying a low-pass filter at each wavelength, were
recombined to a new synthesizing signal, Isyn(k,x). After applying the PRDOCT
algorithm, we could obtain the Doppler optical microangiography (DOMAG)
phase difference image. Based on the following linear relationship between phase
difference and velocity [34, 49], we could directly obtain the velocity information of
the sample.
Because the backgroundtissue signal wasrejected previously, theDOMAG image
provides two great improvements on two aspects. First, based on phase-resolved
technology, the flow velocity was directly provided by DOMAG, compared to
traditional OMAG. Second, the texture pattern artifacts caused by the optical
heterogeneity, which could greatly reduce the performance of the PRDOCT, was
successfully rejected. In consequence, the phase SNR of the DOMAG was greatly
improved compared to PRDOCT.
10.3.4.2 Experimental Verification
To test the performance of our method, we first apply it on the flow phantom
experiments. A phantom was made from gelatin mixed with 2% milk to simulate
the background optical heterogeneity of the tissue in which a capillary tube with
an inner diameter of ∼200 µm was submerged and ∼2% TiO
2
particle solution
was flowing. The flow velocity of the solution was controlled by a precision syringe
pump. The inclining angle of the tube toward the incident beam was set as ∼90
◦
.In
this experiment, each B-scan (lateral direction) contained 1000 A-lines and covered
2.5 mm. Thus, the corresponding x between adjacent A-lines was 2.5 µm. The
resulting images are illustrated in Figure 10.23.
Figure 10.23a is the structure image obtained through the conventional FDOCT
method. We use this image to get flow region in our experiment. Four points,
the top, bottom, left, and right points of the inner wall, were chosen to mark
the flow region. Figure 10.23b is the OMAG flow image. As we can see, the
light backscattered by the fluid particles was successfully highlighted, while the
background static phantom was rejected. Figure 10.23c,d are the DOMAG and
PRDOCT flow images, respectively. Comparing these two images, one can see
that the background character texture pattern artifacts are successfully eliminated
in the DOMAG method. These artifacts are introduced by optical heterogeneity
of the phantom. In consequence, the noise level of Figure 10.23c is significantly
reduced compared to Figure 10.23d, PRDOCT method. These aspects could also
be illustrated by Figure 10.23e. The blue curve is selected from the location marked
with blue line in Figure 10.23c, while the red curve is selected from the same
location marked with the red line in Figure 10.23d. The phase difference caused by
the fluid particles is almost the same (the parabolic curve) using these two methods,
while the noise (the flat curve) of the blue is much smaller than that of the red.
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236 10 Optical Microangiography: Theory and Application
(a) (b)
(d)
(e)
(c)
2.5
2
1.5
1
0.5
0
Phase difference (rad)
0 0.5 1 1.5 2
Lateral position (mm)
Doppler OMAG
PRDODT
Figure 10.23 Flow phantom experiment results. (a) Struc-
ture image, (b) OMAG flow image, (c) Doppler OMAG
image, (d) PRDOCT image, and (e) two lines extracted from
the same depth location of DOMAG and PRDOCT. (Source:
Images are reproduced from Ref. [69].)
To quantify the illustrated efficiency of the improvement demonstrated by the
DOMAG method compared to PRDOCT method, we calculated N (noise, which
could also be present by standard deviation of the phase differences between
adjacent A-lines, σ
φ
), S (signal), and phase SNR of both methods. The noise in our
experiment is presented by the standard deviation of the noise region. The signal,
S, is evaluated through the following algorithm in the flow region:
S =
R
x=L
T
z=B
(
ϕ
xz
>
N
)
(10.57)
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10.3 Optical Microangiography (OMAG) 237
Table 10.1
Evaluated noise, signal, and phase SNR of a
phase difference flow image of PRDOCT and Doppler OMAG.
N(∆φ(rad)) S (number) Phase SNR (dB)
DOMAG 0.036 4731 51
PRDOCT 0.405 3116 39
Improvement 92% 1.52 (unitless) 12
where > returns 1 when φ is bigger than N, else it returns 0. By doing this,
the signal, S, here could denote the effective detectable signal numbers and phase
SNR is the ratio of these two values, S and N. The results are illustrated in
Table 10.1. With our new digital background reconstruction method, the phase
noise N was reduced from 0.405 to 0.036 rad, which is about 92% improvement.
For the reduction of the background noise, the detectable effective signal number
was also greatly improved, from 3116 to 4731, which is a 52% improvement. Based
on these two aspects, the phase SNR was successfully improved by 12 dB, from 39
to 51 dB.
The phase noise we used here could also be called as the phase sensitivity,which
could be determined by the intensity SNR of the system, X, by the following
equation [55]:
σ
2
φ
=
1
X
(10.58)
The phase sensitivity value obtained from Eq. (10.56) is the upper limit value
that phase-resolved method can get in the totally correlated situation. In the
above experiment, the intensity SNR of the flow region is ∼30 dB, which is quite
common in experiments to extract a blood flow signal in in vivo experiment. The
corresponding phase sensitivity is ∼0.033 rad. As we can see, the sensitivity of our
method is quite close to the totally correlated situation.
10.3.4.3 In Vivo Imaging with DOMAG
For further testing the potential of DOMAG in noninvasive assessment of mi-
crocirculation in vivo, we obtained transcranial cerebrovascular images of mice.
In the following experiments, the mice we used were three-month-old male
C57BL/6J mice, which were purchased from commercial breeders (Charles River
Laboratories), and each of them weighed 23–28g. Twenty four hours before we
performed the experiment, the hair of the mice was removed by some kind of a
depilatory cream. During the experiment, the mouse was anesthetized by using 2%
isoflurane (0.2 l min
−1
O
2
, 0.8 l min
−1
air). To make sure the body of the mouse was
in an active condition, we used a warming blanket and a thermometer to maintain
the body temperature of the mouse between 36.7 and 37.1
◦
C. Before the image data
was acquired, a skin window of the mouse head was carefully opened using sterile
technology and with skull left intact. To make the head of the animal as stable as
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238 10 Optical Microangiography: Theory and Application
possible, we used a custom stereotaxic imaging stage. The exposed skull of the
mouse was washed with saline to maintain moisture. All animals were disposed off
according to IACUC regulations. The protocol was approved by the Oregon Health
and Sciences University Institutional Animal Care and Use Committee and was in
compliance with the guidelines of the National Institutes of Health for care and
handling of laboratory animals.
For 3D image, the amplitude of the X–Y scanner was set at 2.5 mm by 2.5 mm,
which contained 2000 A-lines in lateral direction and 500 B-scans in elevation
direction (y-direction). Thus the distance interval between adjacent A-lines was
∼1.25 µm, while the distance interval between adjacent B-scans was ∼5 µm. The
original raw data was first processed frame by frame, and then the flow images
were recombined to provide a 3D volumetric vasculature image of the mouse
head. Figure 10.24a is the conventional OCT cross-sectional structure image of the
mouse head, from which the histologically important layers were clearly identified.
Figure 10.24b presents the DOMAG phase difference image, φ (x, z). With the
orientation of the blood vessels, which could be obtained from the volumetric
vasculature image, the velocity information could be extracted from Eq. (10.57).
Figure 10.24c shows the image that we got by merging Figure 10.24a,b together to
present exactly where the blood flow located. The red color means the blood vessels
have a forward velocity, while the green means they have a backward direction.
p
−
p
0
p−p
0
(a)
(b)
(c)
(d)
Figure 10.24 Doppler OMAG image
results. (a) Conventional OCT structure
image, (b) Doppler OMAG flow image, (c)
OCT cross-sectional structure image show-
ing the location of the blood flow with the
forward ones coded with red color and the
backward ones with green color, (d) volu-
metric rendering of cerebrovasculature. The
red color represents the forward blood flow
while the green color represents the back-
ward blood flow.
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10.3 Optical Microangiography (OMAG) 239
(a)
(b)
500 µm
−10
mm s
−1
10
mm s
−1
0
Figure 10.25 Maximum-amplitude projection view (x–y)
of (a) OMAG and (b) DOMAG of the cerebral blood flow
in the cortical brain of the mouse shown in Figure 10.24.
(Source: Images are reproduced from Ref. [69].)
To combine all two-dimensional slices, DOMAG could provide rendering 3D
volumetric image of blood vessel networks, presented in Figure 10.24d. The red
color denotes the flow with forward direction, while the green is the flow with
backward direction.
To view in detail the blood vessel networks coded with velocity information,
Figure 10.25b provides the x–y projection view with the blood vessel with forward
flow direction in red and backward direction in green. On the basis of the
linear relationship between phase differences and velocity present in Eq. (10.57),
Figure 10.25b is actually a velocity projection along the light beam. Together with
the blood vessel perfusion information given by OMAG (the 2D x–y projection
view of blood vessel perfusion networks is presented in Figure 10.25a), DOMAG
provides a tool that has the potential capability of precisely quantitatively evaluating
the blood vessel.
10.3.4.4 Comparison between PRDOCT and DOMAG
In Figure 10.26, we demonstrated the differences between OMAG, conventional
PRDOCT method, and DOMAG method. Figure 10.26a is a 2D conventional
OCT cross-sectional structure image. The OMAG method obtained the images of
microstructures via SD-OCT (Figure 10.26a), blood flow via OMAG (Figure 10.26b),
and the corresponding velocities of blood flow via DOMAG (Figure 10.26c).
DOMAG calculated the velocities of blood flow in functional vessels, including
capillaries (white arrows, for example), and even in the vessels ∼1.5 mm deep
below the bone surface (red arrow). However, the PRDOCT result (Figure 10.26d)
indicates that conventional DOCT fails to provide detailed velocities of blood
flows in this case. The level of background phase noise is an important metric
when quantifying blood flow, particularly in capillaries, because this metric affects
our ability to extract useful flow signals from the noisy background. Using the
method described in Section 10.3.4.2, the noise level for PRDOCT was typically
0.5 rad, largely due to the heterogeneous property of the tissue sample as seen in
Figure 10.26d and as discussed in Section 10.3.4, suggesting that PRDOCT might
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240 10 Optical Microangiography: Theory and Application
Cortex
White matter
Skull
(a)
(b)
(c) (d)
−p
p
−p
p
500 µm
Figure 10.26 Comparison between OMAG
and PRDOCT B-scan imaging of the cortical
brain in mice in vivo. (a) OMAG structural
image (i.e., SD-OCT) and the correspond-
ing (b) OMAG flow image, (c) DOMAG
flow velocity image, and (d) PRDOCT flow
velocity image. See the text for explanation
of the arrows. (Source: Images are repro-
duced from Ref. [69].)
not be able to measure blood flow velocities <1.1 mm s
−1
when the A-scan rate
is at ∼20 kHz. However, DOMAG was able to reduce this noise level to 0.034
rad, which is comparable to the phantom experiments shown in Section 10.4.1,
suggesting an approximate 15-fold improvement in imaging blood flow velocities
over conventional PRDOCT in this in vivo imaging case. Thus, we expect that
DOMAG will be a good candidate tool to quantify blood flow within perfused tissue.
To further show the advantages of DOMAG in imaging the blood flow velocities
over PRDOCT, we compared 3D DOMAG and PRDOCT images evaluated from
a scanned tissue volume from the mouse brain cortex with the skull left intact.
Figure 10.27 (shown as projection images to x– y) illustrates the difference between
OMAG, DOMAG, and PRDOCT imaging of cerebral blood flow (CBF) in mice
under the same experimental conditions. To obtain the PRDOCT flow image,
we had to use algorithms established in [67, 68] to reduce the noise artifacts,
where algorithms for minimization of the sample motion artifacts, segmentation
of regions of interest, and correction of phase-wrapping errors were implemented.
Note that it did not require performing the segmentations in DOMAG in order
to render the 3D image as the phase noise level was low in the entire 3D space.
These results indicate that DOMAG (Figure 10.27b) could reliably determine the
velocities of blood flows within almost all vessels in the scanned tissue. Not
surprisingly, PRDOCT (Figure 10.27c) can be erroneous in quantifying blood flows
within the scanned tissue due to noise produced in PRDOCT, which masks slow
flows (<1.1 mm s
−1
) in small vessels. Furthermore, blood vessel diameters seen in
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10.3 Optical Microangiography (OMAG) 241
(a) (b) (c)
6.5
mm s
−1
−6.5
mm s
−1
0
Figure 10.27 Comparison between in vivo
3D OMAG and PRDOCT imaging of the
cortical brain in mice with the intact skull.
Shown are the maximum x–y projection
views of (a) OMAG cerebral blood flow
image, (b) DOMAG flow velocity image,
and (c) PRDOCT flow velocity image. The
physical size of scanned tissue volume
was 2.5 × 2.5 × 2.0 mm
3
. White bar =
500 µm. (Source: Images are reproduced
from Ref. [69].)
the DOMAG and OMAG images were significantly larger than those in the DOCT
images, suggesting a clear advantage of DOMAG over DOCT in quantifying blood
flow in the scanned tissue.
The reason forthese differences is thatthe performance ofconventional PRDOCT
is limited by the background texture noise pattern caused by the optical hetero-
geneity, that is, microstructures, of the tissue sample [21]. On the other hand,
DOMAG uses an ideal reconstructed sample as the tissue background, which
makes the adjacent OMAG A-scans totally correlated, maximally satisfying the cor-
relation requirement for the phase-resolved technique. As a consequence, DOMAG
reduces the background phase noise to a minimum. This improves the capability
of DOMAG to detect low blood velocity near the wall of the blood vessel, and as
a result, the diameter of blood vessel detected by DOMAG is larger than that by
PRDOCT, as seen in Figure 10.27.
An alternative way to better illustrate the phase noise levels is to use 3D
plots of cross-sectional images (B-scans). Shown in Figure 10.28 is such an
illustration for a typical B-scan of the cortical brain in mice. Figure 10.27a is
the conventional PRDOCT flow velocity plot, without applying the segmentation
approach to eliminate the random phases in low-signal regions. The flow signals
are pointed by the black arrows and the noise in the useful signal region is
pointed with red arrow. In the low-OCT-signal regions, for example, the region
above tissue surface where there is no light reflectivity and the region deep in
the tissue where the detected optical signal is low due to the light attenuation,
the evaluated phases will exhibit random phase noise signals in PRDOCT. From
Figure 10.28a, it is clear that the noise in the low-signal region overwhelmed the
useful flow signals, thus segmentation is often needed in PRDOCT to exclude
this random noise. After segmentation of the tissue regions of interest using the
methods in [67, 68], a better view is given in Figure 10.28b to show the effects of
background noise in the tissue region. In Figure 10.28b, the noise pointed with
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242 10 Optical Microangiography: Theory and Application
3
2
1
0
0
1
2
3
2.5
2
1.5
1
0.5
0
−3
−2
−1
Lateral position (mm)
Depth position (mm)
Phase difference (mm)
2
1
0
0
1
2
3
2.5
2
1.5
1
0.5
0
−2
−1
Lateral position (mm)
Depth position (mm)
Phase difference (mm)
2
1
0
0
1
2
3
2.5
2
1.5
1
0.5
0
−2
−1
Lateral position (mm)
Depth position (mm)
Phase difference (mm)
(a) (b)
(c)
Figure 10.28 3D flow images. (a) Conventional PRDOCT
flow image without segmentation, (b) conventional PRDOCT
flow image with segmentation, and (c) Doppler OMAG flow
image. (Source: Images are reproduced from Ref. [69].)
a red arrow is so high that it prevents the small blood vessel signals from being
detected. We should pay special attention to those pointed by blue arrows, where
it is difficult to distinguish between blood signals and noise. For DOMAG, shown
in Figure 10.28c, the background noise is very small compared to the blood vessel
signals, which improves significantly the imaging performance for DOMAG. It
should be noted that Ren et al. previously proposed a moving-scatterer-sensitive
optical Doppler optical coherence tomography (MSS-DOCT) technique for in vivo
blood flow imaging using SD-OCT [72, 73]. In their method, a delayed-line filter
was used to suppress the influence of stationary scatterers by subtracting adjacent
complex axial scans before applying the phase-resolved method to calculate the
Doppler frequency shift. There are distinct differences between DOMAG and
MSS-DOCT in that (i) the former operates on the wave number domain signals,
that is, interferograms, while MSS-DOCT operates on the time domain signals,
that is, complex OCT images and (ii) DOMAG filters out the signals caused by the
static scattering components from the entire B-scan signals, while the latter uses
delay-line filters applied to the neighborhood A-scans to suppress the static signals.
10.4
Applications of OMAG
Because of its exceptionally high spatial resolution and velocity sensitivity, sev-
eral basic research and clinical applications of OMAG have been demonstrated,
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10.4 Applications of OMAG 243
which includes monitoring cortical hemodynamics and cerebral vascular perfusion
mapping in rodent models for brain research, cerebral blood perfusion,and vascular
plasticity following TBI in rodent models, screening vasoactive drugs, monitor-
ing changes in tissue morphology, and hemodynamics following pharmacological
intervention and mapping, and imaging ocular blood flow.
10.4.1
In Vivo Imaging of Mouse Cerebral Blood Perfusion and Vascular Plasticity Following
Traumatic Brain Injury Using OMAG
TBI often causes alterations in CBF that are thought to influence secondary
pathophysiology and neurologic outcome in human brain. Inadequate CBF is
an important contributor to mortality and morbidity after TBI [74]. Despite the
importance of cerebral vascular dysfunction in TBI pathophysiology, the effect
of trauma on CBF has been less well studied than the effect of trauma on the
brain [75]. Similarly, our understanding of the rehabilitation and autoregulation
of cerebrovascular blood circulation after TBI also remains incomplete. In this
regard, a noninvasive technique for imaging in vivo blood flow, down to capillary
level resolution, would be of great value.
Three-month-old C57 BL/6 mice (20 –30 g) were used in the study to show the
potential of OMAG for monitoring changes in dynamic CBF following TBI in
vivo. The experimental protocol was in compliance with the Federal guidelines for
care and handling of small rodents and approved by the Institutional Animal Care
and Use Committee. Before OMAG imaging, the mouse head was shaved and
depilated. During the imaging, the animal was immobilized in a custom-made
stereotaxic stage and was lightly anesthetized with isoflurane (0.2 l min
−1
O
2
,
0.8 l min
−1
air). The body temperature was kept between 35.5 and 36.5
◦
Cbyuse
of a warming blanket and monitored by a rectal thermal probe throughout the
experiment. An incision of ∼1 cm was made along the sagittal suture, and the
frontal, parietal, and interparietal bones were exposed by pulling the skin to the
sides. The animal was then positioned under the OMAG scanning probe. In order
to acquire the CBF images over a large area of the cortex, the scan was performed
clockwise, which resulted in six OMAG images covering areas between anterior
coronal suture (Bregma) and posterior coronal suture (Lambda). The total image
acquisition time for the six OMAG scans was ∼8 min. For each 3D OMAG image,
a volumetric segmentation algorithm [60] was applied to isolate the blood flow
signals within the cortex, and a maximum projection method was then used to
project the blood flow signals onto the x–y plane in order to reduce the image
size. The final image, representing the CBF over the mouse cortex, was obtained
by stitching six resulting images together and cropping, covering an area of
∼4.2 × 7.2 mm
2
over the mouse head.
Before inducing TBI, a control OMAG image was acquired as the baseline for
later comparison. Then the mouse was subjected to TBI. In order to induce a
traumatic lesion in the cortex, a 30-gauge needle was disinfected and used to
puncture a round and vertical hole with a depth of 1.5 mm measured from the
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244 10 Optical Microangiography: Theory and Application
upper surface of the skull. The bleeding was washed out using medical-grade
saline. About 30 min after the onset of TBI, OMAG imaging was initiated at the
same region as the control. After imaging, the animal was sutured, disinfected,
and injected with antibiotics, and then returned to the cage for rehabilitation. A
series of OMAG images were taken on the same animal on days 1 (24h after TBI),
(a)
Control
(c)
Day 1
(e)
Day 7
(b)
Day 0
(d)
Day 4
(f)
Day 10
(g) (h)
Figure 10.29 3D OMAG imaging of the
cortex during TBI in mice. Compared to
baseline (a), progressive vessel regula-
tion (vessels are pointed by white arrows)
and neovascularization at traumatic area
develop during TBI rehabilitation. The site of
injury is pointed by green arrow. (g,h) The
photographs of the brain cortex with and
without skull on the same mouse. The area
in (a–f) corresponds to the area marked
with dashed white box in (g) and (h).
The scale bar represents 1.0 mm. (Source:
Images are reproduced from Ref. [77].)
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