Japanese Journal of Applied Physics
Vol. 44, No. 6B, 2005, pp. 4593–4597#2005 The Japan Society of Applied Physics

Construction of Reference Data for Tissue Characterization of Arterial Wall
Based on Elasticity Images
Jun I NAGAKI, Hideyuki H ASEGAWA, Hiroshi K ANAI, Masataka I CHIKI1 and Fumiaki TEZUKA2
Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan1
Sendai Hospital of East Railway Company, Sendai 983-8520, Japan
2
Sendai Medical Center, Sendai 980-0022, Japan(Received November 12, 2004; accepted February 13, 2005; published June 24, 2005)Previously, we developed the phased tracking method [H. Kanai et al.: IEEE Trans. Ultrason. Ferroelectr. Freq. Control 43(1996) 791] for measuring the minute change in thickness during one heartbeat and the elasticity of the arterial wall. By
comparing pathological images with elasticity images measured with ultrasound, elasticity distributions for respective tissues
in the arterial wall were determined. We have already measured the elasticity distributions for lipids and ﬁbrous tissues(mixtures of smooth-muscle and collagen ﬁber) [H. Kanai et al.: Circulation 107 (2003) 3018]. In this study, elasticity
distributions were measured for blood clots and calciﬁed tissues. We discuss whether these elasticity distributions, which weremeasuerd in vitro, can be used as reference data for classifying cross-sectional elasticity images measured in vivo intorespective tissues. In addition to the measurement of elasticity distributions, correlations between collagen content andelasticity were investigated with respect to ﬁbrous tissue to estimate the collagen and smooth-muscle content based onelasticity. Collagen and smooth-muscle content may be important factors in determining the stability of the ﬁbrous cap ofatherosclerotic plaque. Therefore, correlations between elasticity and elements of the tissue in the arterial wall may provide
useful information for the noninvasive diagnosis of plaque vulnerability. [DOI: 10.1143/JJAP.44.4593]
KEYWORDS: elasticity image, elasticity distribution, tissue characterization, atherosclerosis, collagen content

1.

Introduction

Cerebral infarction and myocardial infarction are terminal
symptoms of atherosclerosis. Therefore, it is important todiagnose atherosclerosis in an early stage. The rupturing ofatherosclerotic plaque is probably the most important factor
underlying the sudden outbreak of acute coronary syndrome.1) Direct characterization of the composition andvulnerability of atherosclerotic plaque may oﬀer insight into
the mechanism of plaque regression and progression.2,3) The
elasticity of the arterial wall is largely aﬀected by changes incomposition due to the development of atherosclerosis.4)
Therefore, the measurement of elasticity has the potential forarterial wall tissue characterization. For assessment ofelasticity, we developed a method using transcutaneousultrasound for measuring the minute changes in the thickness of the arterial wall during a heartbeat.5–10) In this paper,
the reference data on elasticity distributions for respective
tissues are presented to classify arterial tissues based on theelasticity images measured in vivo. From in vitro experiments using excised human femoral arteries, the relationshipbetween tissue components in the arterial wall and theelasticity was investigated by comparing the elasticity
images measured using ultrasound with corresponding
pathological images. From in vitro experimental results,(1) elasticity distributions of blood clots and calciﬁed tissues
were determined in addition to those of lipids and ﬁbrous
tissues,10) and (2) the correlation between the collagencontent and elasticity was investigated to noninvasively
estimate collagen and smooth-muscle content in ﬁbrous
tissues based on elasticity.
2.

Methods

2.1 Elasticity estimation of arterial wall 5,10)
An ultrasonic beam was sequentially scanned through M

E-mail address: hasegawa@us.ecei.tohoku.ac.jp

positions using a linear ultrasonic probe at 7.5 MHz withconventional ultrasound diagnostic equipment (ToshibaSSH-140A), and multiple (Nm þ 1) points were preset fromthe luminal surface to the adventitia along the m-th ultrasonic beam (m ¼ 1; . . . ; M) with constant intervals of
h0 ¼ 375 mm at time t0 just before the ejection period. By
dividing the arterial wall into multiple layers, we deﬁned then-th layer (n ¼ 1; . . . ; Nm ) as being between two succeeding
points, n and n þ 1, along each beam. To measure thechange in thickness of each of the Nm layers, the instantaneous depth xm;n ðtÞ of the n-th point along the m-th beam wassimultaneously tracked by applying the phased tracking
method 5,6) to the received ultrasound. The minute decreaseof several tens of micrometers in wall thickness of the n-thlayer resulting from the arrival of the pressure wave at thebeginning of the ejection period was determined byhm;n ðtÞ ¼ xm;nþ1 ðtÞ  xm;n ðtÞ.
In the phased tracking method, used to calculate the auto
correlation function between the quadrature demodulated
signals of succeedingly received echoes, minute phasechanges of about 0.4 degrees caused by movement of then-th point during the pulse transmission interval T(¼ 200 ms) can be accurately determined by introducing aconstraint, namely, that their waveforms are identical but
their phase values change.5,6) The lowest value of the change
in thickness was validated as being about 0.5 mm by
expanding a rubber plate in a water tank.7) Such a minutechange in thickness cannot be measured in water by anyother method. This method has already been applied with
suﬃcient reproducibility to the in vivo detection of regional
instantaneous displacements and changes in thickness in thecarotid arteries.8)
From the ratio of the maximum decrease in thickness
during one heartbeat, hm;n;max ¼ maxt jhm;n ðtÞj, to theinitial thickness h0 of the n-th layer, the maximum
deformation of the n-th layer was obtained by "m;n;max ¼
hm;n;max =h0 . Since the deformation was suﬃciently small

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and was in the linear regime, it showed incremental strain in
the radial direction. By assuming that the arterial wall isincompressible and that the blood pressure is applied normal
to each layer, the elastic modulus of the n-th layer along them-th beam, E;m;n , is approximately given by9)
1 m;n;0Nm  n þ 1
pE;m;n þ; ð2:1Þ
2 h0  N m
Nmj"m;n;max j
where m;n;0 is the initial inner radius of curvature of the n-thlayer along the m-th beam at a time t0 . We assumed that thepressure in the arterial wall decreases linearly with thedistance from the intimal side to the adventitia and that thearterial wall is almost isotropic.11)
The regional elasticity, E;m;n , was estimated from thecross-sectional image. Since the reﬂected ultrasound wasreceived at a sampling interval of 100 ns (¼ 75 mm alongdepth direction) after quadrature demodulation, we furtherdivided each layer with a thickness of h0 (¼ 375 mm) into 5points, shifted the initial depth of each layer with a thicknessof one ﬁfth of h0 , and applied the above procedure to each
depth. Thus, E;m;n was estimated at intervals of 75 mm in thedepth direction.
2.2 Experimental system for in vitro experiments
Figure 1 shows the experimental setup for in vitro
experiments using excised human femoral arteries. Thechange in internal pressure was generated using an artiﬁcial
heart, and the internal pressure was measured with thepressure catheter (Camino 110-4) placed in the lumen of theartery. The artery ﬁxed in the water tank was measured witha linear probe (center frequency: 7.5 MHz).
2.3 Construction of elasticity distribution for each tissueIn this study, the elasticity distributions were obtainedwith respect to blood clots and calciﬁed tissues. After
ultrasonic elasticity measurements, the arteries were ﬁxed informalin. The plane scanned by ultrasound was identiﬁed byimaging a needle, which was ﬁxed in the external surface ofthe posterior wall, in the B-mode image during the ultrasonicmeasurement.10) The pathological images of the measured
planes were made with elastica-masson staining for bloodclots and with hematoxylin-eosin staining for calciﬁed
tissues. By referring to the pathological images, the regions
which correspond to blood clots and calciﬁed tissues wereassigned in the corresponding cross-sectional elasticity
safetyreliefvalve

measurement
systemairpumpair

artificial
heart

water
ultrasonicprobe
specimenpressure
detector (110–4)
Fig. 1. Schematic diagram of the system for in vitro experiments.

luminal surface
12
posterior wall

external surface

N m –1Nm
1, 2,mM –1, M

Fig. 2. Illustration of assignment of regions in a pathological image.

images. From the regions assigned for respective tissues,elasticity distributions were determined.
2.4 Estimation of collagen content
Fibrous tissue consists mainly of collagen ﬁbers andsmooth muscle. The correlation between the collagencontent and the elasticity content was investigated withrespect to ﬁbrous tissue to noninvasively estimate thecollagen and smooth muscle content based on the measured
elasticity.
In the elasticity image, there are M ultrasonic beams and
Nm regions along m-th beam (m ¼P
1; . . . ; M). Therefore, inM
an elasticity image, there are
m¼1 Nm regions withrespective elasticity values. Each region in an elasticity
image is referred as REm;n (m ¼ 1; . . . ; M, n ¼ 1; . . . ; Nm ). As
shown in Fig. 2, each region REm;n in the elasticity image iscompared with the corresponding region RPm;n in thepathological image assigned as follows: The entire pathological image, which corresponds to the entire elasticity
image, is divided into M sections in the axial direction of theartery, and each m-th section of M sections is divided intoNm regions in the radial direction. The sizes of all regions inan elasticity image are equivalent. However, actual sizes ofregions assigned in the pathological image diﬀered becauseof the distortion of the arterial wall due to dehydration
during formalin ﬁxation. In this paper, by assuming that thechange in size due to distortion is homogeneous, each M
section was divided into Nm regions of equivalent size in theradial and axial directions.
Then, the collagen content of each region RPm;n assigned in
the pathological image was estimated using the Mahalanobis
distance. In this paper, the composition of each region RPm;nis classiﬁed into one of four classes (i ¼ 1: collagen, 2:smooth muscle, 3: elastin, 4: background). The mean,
i ¼ ðr ; g ; b ÞT , and covariance matrix, i , of RGB
values were determined for each class i by manuallyassigning typical regions in the pathological image for eachclass. From the determined mean i and the covariancematrix i , the Mahalanobis distance di2 between each pixel,
X ¼ ðxr ; xg ; xb ÞT , in the region RPm;n and the center of the i-thclass is obtained as follows:X1ðX  i Þ:ð2:2Þ
di2 ¼ ðX  i ÞTi
Each pixel X is classiﬁed into class imin which has the least
Mahalanobis distance to X. To evaluate the collagen content
in ﬁbrous tissue, we employed two arteries mainly consistingof ﬁbrous tissue. In other words, there are no blood clots,

Jpn. J. Appl. Phys., Vol. 44, No. 6B (2005)(a−1)

specimen A(a−2)

J. INAGAKI et al.

(b−1)

4595

(a)

specimen B(b−2)

3.75mmanterior
wall
lumen
posterior
wall

3mm

elastic
modulus [MPa]

600µm

600µm

04(c)
321000.5

11.5

20.5

11.5

2
4 MPa
scanned area(b)

4 MPa

5 mm

calcified tissue

Fig. 3. Elasticity images (1) and pathological images (2) of two ﬁbrousarteries. Divided regions, RPm;n , are shown by the black lines superimposedon the pathological images. (a) Specimen A. (b) Specimen B. (c) Colors
assigned to corresponding elasticity values.

zoomFig. 5. (a) Elasticity image of the posterior wall of an excised humanfemoral artery. (b) Pathological image of the posterior wall made withhematoxylin-eosin staining.

posteriorwall
3mm

00.5

11.52

scanned area

4 MPa(b)40300kPa

30

blood clot
_ 57 kPa (N=612)
96 +

20

calcified tissue_ 1.0 MPa (N=218)
2.0 +

100

lipid: frequency [%]

5 mm

01234
56
elastic modulus [MPa]

5(b)
lipid
_+
481 40 kPa (N=425)

40smooth muscle andcollagen fiber_ 0.63 MPa (N=5213)
1.0 +

30
20

32
1100

432150blood clot(a)00zoom10

calcified tssue: freq. [%]blood clot: frequency [%]lumenfiberous tissue: freq. [%](a)anteriorwall

3.75mm234
elastic modulus [MPa]Fig. 4. (a) Elasticity image of the posterior wall of an excised humanfemoral artery. (b) Pathological image of the posterior wall made withelastica-masson staining.

Fig. 6. (a) Elasticity distributions of blood clots and calciﬁed tissues.
(b) Elasticity distributions of lipids and ﬁbrous tissues (mixtures ofsmooth muscle and collagen ﬁbers).10)

lipids or calciﬁed tissues in these arteries.
Figures 3(a-1) and 3(b-1) show the elasticity images oftwo arteries. Figures 3(a-2) and 3(b-2) show the pathologicalimages of the corresponding sections. Black meshes show
divided regions RPm;n which correspond to REm;n in therespective elasticity images. Figure 3(c) shows the colors
assigned to corresponding elasticity values.
In the process for creating the pathological image, somedeformations unavoidably occur. Such deformations lead todiﬀerences in size and shape between the elasticity andpathological images. Therefore, we used a part of the arterial
wall showing little diﬀerence in size and shape between theelasticity image and the pathological image.

The resolution was too small to exactly correlate a region
in the elasticity image to the corresponding region in thepathological image because of the deformation caused bydehydration. Therefore, we employed spatially averaged
values obtained from regions with about 600 mm in the axial
direction  600 mm in the radial direction in size.
3.

Results

3.1 Construction of elasticity distribution for each tissue
Figures 4(a) and 5(a) show the elasticity images of two
excised human femoral arteries. After ultrasonic measurement, the pathological images of the measured sections weremade as shown in Figs. 4(b) and 5(b) with elastica-masson

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3.2 Relationship between collagen content and elasticity
Figure 7 shows the relationship between the collagencontent and the elasticity for the two ﬁbrous arteries shownin Figs. 3(a) and 3(b). In Fig. 7, plots and vertical bars show
the spatial means and standard deviations within regions
about 600 mm  600 mm in size. There are 36 points, whichwere calculated from 758 divided regions REm;n . The straightline shows the regression line obtained by applying the leastsquares method to the spatial means. A positive correlation
between collagen content and elasticity was found.
Figures 8(a) and 8(b) show the relationship between thecollagen content and the smooth-muscle content in eachdivided region RPm;n and each spatial averaging region of
about 600 mm  600 mm, respectively. In this estimation,
regions were manually assigned twice with respect to thesame pathological image to estimate both collagen andsmooth-muscle content in a divided region. In the ﬁrstassignment, the collagen content of each divided region
RPm;n ð1Þ was estimated. In the second assignment, thesmooth-muscle content of each divided region RPm;n ð2Þ was100

elastic modulus [MPa]

2.0
1.5
1.0
0.5
00204060
collagen content [%]

80

100

Fig. 7. Relationship between collagen content and elasticity.

806040200020406080

100

collagen content [%](b)

80
6040200020406080

100

collagen content [%]Fig. 8. Relationship between collagen content and smooth muscle content
in the region with the pathological image. (a) Before spatial averaging.
(b) After spatial averaging.

estimated. Then, the collagen content in RPm;n ð1Þ v.s. thesmooth-muscle content in RPm;n ð2Þ was plotted in Fig. 8(a).
There are some points for which the sum of collagen andsmooth-muscle content show a value of over 100% inFig. 8(a). This means that the sizes and positions of RPm;n ð1Þ
and RPm;n ð2Þ were not identical. This result suggests that thesize of each divided region RPm;n is too small to identify aregion in the arterial wall, especially in the case ofcomparing the elasticity image with the pathological image,
because the deformation due to dehydration also inﬂuences
the values. As shown in Fig. 8(b), almost all the sums ofcollagen and smooth-muscle content are below 100% after
spatial averaging with respect to a region 600 mm  600 mmin size. This result suggests that the inﬂuence of region
disagreement was reduced by comparing larger regions.
Therefore, we also applied spatial averaging to estimate therelationship between collagen content and elasticity.
In Fig. 8(b), most sums of both contents were about 90%,
which shows that ﬁbrous arteries consist mainly of collagenand smooth muscle. By assuming that the ﬁbrous tissue
consists of only collagen and smooth muscle, we estimate
the collagen and smooth muscle content of ﬁbrous tissue
based on its elastic modulus. Figures 9(a) and 9(b) show thecollagen and smooth-muscle content for each elasticity value
superimposed on the elasticity distribution of ﬁbrous tissues
shown in Fig. 6(b). From the correlation shown in Fig. 7,collagen and smooth-muscle content can be estimated asshown in Figs. 9(a) and 9(b) based on elasticity measured
with transcutaneous ultrasound.
4.

2.5

100(a)

smoothmuscle content [%]staining and hematoxylin-eosin staining, respectively. From
the respective pathological images, the blood clot and thecalciﬁed tissue were identiﬁed as shown by the regions
surrounded by green lines in Figs. 4(b) and 5(b). The means
and standard deviations with respect to elastic modulus weredetermined to be 96  57 kPa for the blood clot and 2:0 
1:0 MPa for the calciﬁed tissue, where the number of points
assigned in the elasticity images were 612 and 278,
respectively.
Figure 6 shows the elasticity distributions of the bloodclot, calciﬁed tissue, lipid, and ﬁbrous tissue (mixture ofcollagen ﬁber and smooth-muscle).10) By comparing each
elasticity distribution, great similarity was found in theelasticity distributions of lipids and blood clots. This meansthat the classiﬁcation of these tissues based on elasticity isdiﬃcult. Moreover, the elasticity distributions of ﬁbrous
tissue and calciﬁed tissue largely overlapped each other.
However, it will be possible to classify lipids or blood clots
from ﬁbrous tissues or calciﬁed tissues. These two groups(soft and hard tissues) may be distinguished at about
300 kPa. These results suggest that hard tissues such as
ﬁbrous tissues and calciﬁed tissues, which contribute to thestability of plaque, and soft tissues such as lipids and bloodclots, which contribute to instability, can be noninvasively
diﬀerentiated based on elasticity.

smoothmuscle content [%]4596

Conclusions

By comparing the elasticity distributions of blood clots,calciﬁed tissues, lipids and ﬁbrous tissues,10) it was foundthat arterial tissues can be classiﬁed into soft tissues (lipidsor blood clots) and hard tissues (ﬁbrous tissues or calciﬁedtissues) from the elasticity image. These two groups weredistinguished at about 300 kPa, and this threshold isimportant to make a rough tissue characterization based onelasticity. Furthermore, comparing collagen content andelasticity, a positive correlation was found. This result oﬀers
the potential of estimating collagen content based onelasticity, and this collagen-content estimation may contribute to noninvasive evaluations of the vulnerability ofatherosclerotic plaques.

100(a)relationship between
collagen and elasticity

438060fibrous tissue402
collagen content

12000

frequency [%]5(b)relationship between
smooth−muscle and elasticity

431008060

fibrous tissue240
smooth−muscle content

10200123
elastic modulus [MPa]40smoothmuscle content [%]frequency [%]5J. INAGAKI et al.

collagen content [%]Jpn. J. Appl. Phys., Vol. 44, No. 6B (2005)

Fig. 9. Estimated (a) collagen content and (b) smooth muscle content
contained in ﬁbrous tissue superimposed on the elasticity distribution ofﬁbrous tissue.

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