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References 163
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165
9
Tissue Viability Imaging
Jim O’Doherty, Martin J. Leahy, and Gert E. Nilsson
9.1
Introduction
There is a constantly growing need for reliable and user-independent assessment
of the skin microcirculation and other skin parameters not only in medical
applications but also in the development and evaluation of pharmaceuticals, skin
care products, and cosmetics. Owing to the essential link between microcirculation
function and adequate tissue oxygen delivery and thus organ function, the tissue
blood supply has been noted as a crucial indicator of injury and disease [1, 2].
Given that many of the parameters of interest vary spatially over the skin surface,
these needs are generally better served by the use of imaging technologies than
by single-point measurement devices. Since the most superficial microvascular
network of the skin resides in the papilla just under the epidermal layer, the
measurement depth of the technology of choice must be compatible with these
dimensions. Methods based on photonics operating in the visible and near-infrared
regions possess a depth sensitivity that fulfills these requirements. To attain a high
productivity in skin testing, such methods should also incorporate software for
effective processing of the large amount of data generated and should preferably
be able to reduce image information to numbers and indexes suitable for statistical
testing. Furthermore, the methods should be easy to apply in a reproducible way
in clinical settings as well as at the skin test laboratory and work site. Among
the suitable candidates based on photonics principles available for fulfillment of
these requirements, capillary video microscopy [3], laser Doppler imaging [4], and
subsurface spectroscopic imaging [5] are currently the most promising. Owing
to the variability in tissue optical parameters from one tissue to another, these
technologies deliver arbitrary values that scale linearly with the parameter of
interest rather than absolute quantities. In this chapter, tissue viability imaging
(TiVi) based on wideband spectroscopy of backscattered light is described in further
detail.
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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166 9 Tissue Viability Imaging
9.2
Operating Principle
Since the digital camera was introduced in the 1990s, they have developed quickly
and are increasingly used as part of advanced imaging systems in a variety
of medical and other applications. Skin observations through perpendicularly
oriented linearpolarization filtersto reducesurface glarefirst transpiredin 1991[6].
Owing to research carried out in the mid-1990s, which stated that reflection-based
polarized light imaging in skin would not suffer significant blurring [7] and also
the accelerated arrival of high-resolution charge coupled devices (CCDs), led to
increased use of the technique. To reduce the influence of direct reflections of
the light from the flash in the surface of the object and capture a ‘‘subsurface’’
photo based on diffusely backscattered and depolarized photons, cross-polarization
filter techniques are frequently used. Alternatively, if information about the surface
structure of the skin is of primary interest, copolarization filter techniques that
suppress the influence of the diffusely backscattered and depolarized photons
remitted from inside the tissue while direct surface reflection is enhanced can be
used [8]. The group’s work improves image contrast based on light scattering in
the superficial layers of the skin, which can visualize the disruption of the normal
texture of the papillary and upper reticular dermis of the skin. The group expanded
the work to be used in Mohs surgery, whereby the images may be used to guide
clinical excision of skin cancers, and shows promise in the assessment of skin
topography. An example image is shown in Figure 9.1, where the borders of a burn
wound are significantly enhanced. They also expanded the system to a handheld
prototype camera and refined the image processing to include data from two CCDs,
while investigating the characteristics of the texture and surface appearance of a
range of skin conditions [9].
0.18
0.2
0.16
0.14
0.12
0.08
0.06
0.04
0.02
0
0.1
2
4
6
8
10
12
14
16
18
20
5
y (mm)
2
4
6
8
10
12
14
16
18
20
y (mm)
10 15 20
x (mm)
5101520
x (mm)(a) (b)
Figure 9.1 Polarization images of normal (a) and a burn
scar (b), showing clearly defined boundaries of the wound.
(Source: Figure after Ref. [8], reproduced with permission.)
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9.2 Operating Principle 167
In the cross-polarized mode, the polarization filters in front of the flash and the
detector array have orthogonal polarization directions. Linearly polarizedwhite light
from the flash is partly reflected by the upper layer of the skin and partly diffusely
scattered in the deeper dermal layers where the microvascular network is located
(Figure 9.1). Most of the directly reflected light (7% in total) preserves its state of
linear polarization, while the light diffusely scattered in the tissue (93%) becomes
randomly polarized. About 53% of the light is directly absorbed in the tissue, while
the remaining portion emerges from the tissue as diffusely reflected light, is almost
completely depolarized, and can be considered to consist of two 20% fractions of
parallel and perpendicular polarizations with respect to the direction of the original
filter. A portion of the randomly polarized light emanating from deeper tissue lay-
ers, however,passes through this filter and reaches thedetector. Thislight is filtered
through a set of red, green, and blue filters integrated in the camera photodetector
array, and the corresponding photo is storedelectronically in the camera or the com-
puter as three matrixes representing the red (600 –700 nm), green (500 –600 nm),
and blue (400– 500 nm) color planes, respectively. These three combined color
planes constitute the true color photo. This gating of photons is based on the as-
sumption that weakly scattered light (the surface reflections) retains its polarization
state, whereas strongly scattered light will successively depolarize with each scat-
tering event. A schematic is shown in Figure 9.2 where the difference in generation
of copolarized images (CO) and cross-polarized images (CR) can be observed.
The effect is clearly seen in materials that reflect the majority of light impinging
on them. As an example, Figure 9.3 shows that the intensity reflected by the metal
key occurs from surface reflections only, hence the larger change in intensity when
progressing in filter angle degrees from a cross-polarized image to a copolarized
image. The resulting curves were fitted with a standard sinusoid, since rotating
the polarizer further would cause a repeating pattern. It is interesting to note
that the full width half maximum for skin (84
◦
) is less than that for the metal
key (124
◦
), which may be caused by subsurface scattering and absorption in the
skin tissue (Figure 9.4). There is also a larger dynamic range when examining the
back-reflections from the key because the returning light is attributed to surface
reflections only (≈90%); thus, minimum intensity (only 10% of incident light)
G
Light source
Melanin layer
Epidermis
Capillaries
Filter 1
Linearly
polarized
Depolarized
R
B
Linearly
polarized
Filter 2
CCD
Figure 9.2 Schematic showing the operating principle of subsurface spectroscopic imaging.
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168 9 Tissue Viability Imaging
(
a
)(
b
)
Figure 9.3 Copolarized (a) and
cross-polarized (b) images of directly
reflecting objects. The surface skin tissue is
suppressed in the cross-polarized image, and
information from the deeper layers reached
the CCD as is indicated from the more red
color of the subjects hand. The metallic
objects serve as extremes as all light from
them will retain its linear polarization.
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
100 120 140 160 180 200 220 240 260
Filter angle difference (degrees)
Normalized incident intensity
CR image
CR image
CO image
Metal data
Skin data
Skin data–fit
Metal data–fit
Figure 9.4 Resultant light intensity by
rotation of a detecting linear polarizing fil-
ter from 90
◦
(CR image) to 180
◦
(copo-
larized image) and 270
◦
(cross-polarized
image) for a metal key and Caucasian skin
(Figure 9.3b). Note the higher intensity vari-
ation of surface reflections from the key.
Maximal surface reflections for the metal
key and skin occur when the difference be-
tween the filters is 180
◦
, leading to a CO
image. Minimal reflections occur when the
filters are crossed. The shape of light inten-
sity with polarization angle variation for the
tissue and key closely follows a sinusoidal
shape.
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9.2 Operating Principle 169
(
a
)(
b
)
Figure 9.5 (a) Acquired cross-polarized image and (b) the
associated TiVi image showing the concentration of RBCs in
the microvasculature.
is reached when the surface reflections are blocked. This is not the case for the
skin sample, and it can be noticed that the surface reflections represent only a
small fraction of the returning light (≈10%) due to the penetration into the deeper
compartments of the tissue. Reflections from the metal key reduce from 100% of
detected intensity to ∼10%, while for the skin sample, the reflections are reduced
from 100 to 90% of detected intensity.
The green component of the light reaching the detector is attenuated due to
a high absorption in the red blood cells (RBCs), while the red component is
virtually unaltered because of its relatively low absorption in the RBCs. Sur-
rounding tissue absorbs green and red light to approximately the same amount
[10]. Subsurface imaging of the skin RBC concentration takes advantage of this
wavelength-dependent absorption in the hemoglobin molecule of the RBC. By
applying an algorithm in which the value of each picture element in the green
color matrix is subtracted from the corresponding value in the red color matrix, an
output matrix representing the local RBC concentration is generated. This output
matrix is displayed as a color-coded map of the local RBC concentration of the
skin microvascular network, an example of which is shown in Figure 9.5. Further
images are provided as to the applicability of TiVi in the large and narrow fields
of view, with Figure 9.6 showing the human nail fold in the index finger, with the
concentration of RBCs visible in individual vessels. This builds on the technique
of nail fold capillaroscopy where blood velocity can be determined by direct visual
observation of the flowing RBCs in the capillary loops to a system where the
concentration may be quantified.
It should be noted that the spectral signature between the light source used for
microscopy and the standard TiVi system are not consistent; with changing a light
source, a recalibration should be performed to ensure that system output scales
linearly with RBC concentration. This linearity is discussed further in Section 9.2.2.
Figure 9.7 shows a wide field of view of a burn wound that may allow detailed
comparison of different areas of the wound concurrently. Brain hemodynamics
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170 9 Tissue Viability Imaging
Figure 9.6 A cross-polarized image acquired of the nail fold
plexus acquired with a standard digital microscope and its
associated TiVi image showing the concentration of RBCs in
the individual vessels (magnification at ×400).
Figure 9.7 An example image showing the capability
for wide field burn wound assessment. Different parts of
the wound may be assessed concurrently and, over time,
providing a reproducible setup of the patient.
may also be investigated as shown in Figure 9.8, where TiVi images of an
exposed mouse brain show the individual blood vessels. The image shows that
brain hemodynamics may be performed on the exposed brain. With the system
operating in photo mode, a new photo can be captured every 5 s with a maximum
image size of 5184 × 3456 pixels, limited by the recharge time of the flash (∼5s).
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9.2 Operating Principle 171
(a)
(b)
Figure 9.8 (a) Image showing an exposed mouse brain and
(b) corresponding TiVi image of a section of the brain. The
TiVi visualization of the brain allows the hemodynamics of
single vessels to be assessed over time, and dynamic stud-
ies may be performed with the high-speed system.
The theoretical basis of the TiVi system is based on Kubelka –Munk theory of
diffuse reflection. The wavelength-dependent intensity of backscattered light with
a perpendicular polarization to the incident-polarized light is described by the
equation [11]
I
per
(λ) ∝ k
0
(
λ
)
I
0
T
epid
(λ)R
d
(λ) (9.1)
where k
0
(λ) represents the fraction of the total emitted light intensity I
0
within
the wavelength interval λ, impinging on the skin, T
epid
(λ) represents the
transmission properties of the epidermal layer, and R
d
(λ) represents diffusely
reflected light in the area of the reticular dermis. An algorithm is suggested which
is sensitive to the concentration of RBCs in the tissue and does not depend on the
total light intensity. Using Eq. (9.1) above, the algorithm is stated as
RBC
conc
= k
gain
T
epid
(
λ
r
)
R
d
(
λ
r
)
− kT
epid
λ
g
R
d
λ
g
T
epid
(
λ
r
)
R
d
(
λ
r
)
(9.2)
An assumption is made where T
epid
(λ
r
) and T
epid
(λ
g
) are approximated to 1
on the basis of mathematical observations by regarding the melanin layer as a
modulating filter. Using Kubelka–Munk and associated diffusion theory, it can be
shown that
R
d
(λ) = 1 +
8µ
a
(λ)
3µ
s
(λ)
−
(8µ
a
(λ))
2
(3µ
s
(λ))
2
+ 2
8µ
a
(λ)
3µ
s
(λ)
1
2
(9.3)
Where the absorption (µ
a
) and scattering (µ
s
) coefficients are composed of two
parts; one relating directly to the RBC itself (µ
RBC
(λ)) and the other part relating
to background tissue (µ
TISSUE
(λ)). Thus,
µ
s
(
λ
)
= RBC
f
µ
sRBC
(
λ
)
+
(
1 − RBC
f
)
µ
sTISSUE
(
λ
)
(9.4a)
µ
a
(
λ
)
= RBC
f
µ
aRBC
(
λ
)
+
(
1 − RBC
f
)
µ
aTISSUE
(
λ
)
(9.4b)
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172 9 Tissue Viability Imaging
Table 9.1 Average absorption (µ
a
) and scattering (µ
s
)coef-
ficients (cm
−1
) for the relevant biological chromophore in the
red (λ
r
) and green (λ
g
) wavelength regions.
Absorber Red (600–700 nm) Green (500–600 nm)
µ
a
(∆λ
r
) µ
s
(∆λ
r
) µ
a
(∆λ
r
) µ
s
(∆λ
r
)
Tissue 2.7 187 3 223
RBCoxy 3.5 861 177 920
RBCdeoxy 25 861 201 920
Epidermis 35 450 40 535
where RBC
f
represents the volume fraction of RBCs in the tissue volume. Table 9.1
represents the coefficients for the chromophores of interest in the determination
of µ
a
and µ
s
. In practice, Eq. (9.5) is applied to an image by way of mathematical
operations on the color planes that constitute the image, namely
M = k
gain
M
red
− kM
green
M
red
(9.5)
And further processing in order to linearize the relationship between RBC
conc
and
RBC
f
by
M
out
= Me
−pM
(9.6)
The matrix produced, M
out
, is a 2D array of RBC
conc
values.
9.3
Validation
9.3.1
Monte Carlo Modeling
The average penetration depth of red and green photons in skin tissue returning
to the skin surface was investigated by adaptation of a Monte Carlo simulation
model that incorporated the polarization properties of the photons [12]. Previous
codes have established the fundamentals of polarized light propagation in turbid
media [13]. Gating of the photons by monitoring the Stokes vector of the photon on
detection was performed in order to compare the sampling depth of total detected
photons with the sampling depth-detected CR photons. Optical properties of the
relevant biological chromophores in tissue used in these simulations are shown
in Table 9.1. Their results in Figure 9.9 showed that by using cross-polarized
detection, the average penetration depth increased from 345 to 482 µm for red
wavelengths and from 316 to 387 µm for green wavelengths [5]. This implies
that the measurement volume (the volume from which the bulk of the signal is
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9.3 Validation 173
0.5
0
1
0 200 400 600 800 1000
Depth (µm)
0.5
0
1
0 200 400 600 800 1000
Depth (µm)
All photons
All photons
CR photons
CR photons
Red (600–700 nm)
Green (500–600 nm)
(a)
(b)
Figure 9.9 (a,b) Probability density func-
tions of the Monte Carlo simulation in the
red and green wavelength regions. The verti-
cal arrows represent the average sampling
depth of the ‘‘all photons’’ (unpolarized)
simulation and the ‘‘CR photons’’ simulation
where only linearly polarized photons are ac-
cepted. (Source: After Ref. [5], reproduced
with permission.)
acquired) is located well into the reticular dermis in most skin sites. Owing to the
epidermal layer thickness of ∼50–100 µm being unaccounted for in this model,
the total depth of detected photons as stated above will be marginally larger than
the Monte Carlo depth, that is, on the order of 400–500 µm. This increase in depth
sensitivity has been confirmed also in enhanced visual scoring of skin erythema
using a polarized light visualization system [14].
9.3.2
Experimental Modeling
The linear relationship between the output matrix values (TiVi
index
-values) gener-
ated and the actual concentration of RBCs was verified by way of a fluid model
composed of tightly wound latex tubing simulating the blood vessels of the mi-
crocirculations. The system was perfused by fresh human blood mixed with saline
to produce RBC concentrations ranging from 0 to 4% in steps of 0.2%, which
was considered to cover the physiological range of skin tissue. Maximal oxygen
saturation (∼100%) of the mixture was provided by stirring and exposure to am-
bient air, while minimal oxygen saturation (∼0%) was attained by bubbling N
2
gas through the blood samples. Five photos were captured for each RBC frac-
tion and cropped to a region of interest (ROI) covering the center of the fluid
model. The average TiVi
index
-values were then plotted as a function of the actual
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