Journal of Atherosclerosis and Thrombosis Vol.16, No. 6

782

Original Article

Impact of Lifestyle-Related Diseases on Carotid Arterial Wall
Elasticity as Evaluated by an Ultrasonic Phased-Tracking Method inJapanese Subjects
Toshio Yamagishi 1, Makoto Kato 2, Yoshiro Koiwa 3, Hideyuki Hasegawa 4, 5, and Hiroshi Kanai 5, 4
1

Department of Internal Medicine, Tohoku Kosai Hospital, Sendai, Japan
Panasonic Shikoku Electronics Co., Ltd, Yokohama, Japan
3
Oizumi Memorial Hospital, Shiroishi, Japan
4
Department of Biomedical Engineering, Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan
5
Department of Electronic Engineering, Graduate School of Engineering, Tohoku University, Sendai, Japan
2

Aim: We investigated the relationship between coronary risk factors and the intima-media thickness(IMT) and wall elasticity of carotid arteries. A new real-time ultrasonic measurement system thatallows measurement of the elasticity of the carotid arterial intima-media complex was applied to 350
subjects, who were also checked for the presence/absence of hypertension, dyslipidemia, diabetes
mellitus and regular smoking. Simultaneous measurement of the elastic modulus and IMT was conducted at four sites in the bilateral carotid arteries.
Methods and Results: In the group with maximum IMT (max IMT) ＜ 1.1 mm, the IMT, as well as
the mean elastic modulus in the circumferential direction (Eθ), showed positive correlations with age
and coronary risk factors. Multiple regression analysis showed that age, systolic blood pressure andpulse rate remained independent determinants of Eθ. The number of criteria fulfilling the diagnosisof metabolic syndrome showed a good positive correlation with the value of Eθ in the group withmax IMT values ＜ 1.1 mm.
Conclusion: Measurement of carotid arterial wall elasticity together with IMT is useful to detect distortions in intramural elasticity distribution occurring in the early stages of atherosclerosis.
J Atheroscler Thromb, 2009; 16:782-791.
Key words; Elastic modulus, Carotid arteries, Intima-media thickness, Metabolic syndrome,
Atherosclerosis

Introduction
Carotid arterial intima-media thickness (IMT) is
one of the established indices of chronic atherosclerotic arterial disease 1-5); however, IMT is not a direct
measure of the stiffness of the arterial wall. Recently, a
new ultrasonic system that can measure regional elasticity in the arterial wall utilizing a phased tracking
method has been developed 6-10). The modulus of elasticity has also been successfully derived from measurAddress for correspondence: Toshio Yamagishi, Department
of Internal Medicine, Tohoku Kosai Hospital, 2-3-11
Kokubun-cho, Aoba-ku, Sendai 980-0803, Japan
E-mail: tyamagishi@tohokukosai.com
Received: October 3, 2008
Accepted for publication: May 26, 2009

ing change in arterial wall thickness during one cardiac cycle as an index of the “stiffness/softness” of thearterial wall. In a previous study, we reported the usefulness of measuring the elastic modulus of common
carotid arteries (CCAs) by ultrasound imaging todetecting early-stage atherosclerotic lesions caused bycigarette smoking 9).
The main aim of the present study was to determine whether early-stage atherosclerotic changes,
caused by hypertension, diabetes mellitus, dyslipidemia and obesity, could also be detected using theultrasound-based tissue characterization system for thearterial wall. Another objective of the study was toassess the relationship between the IMT and the elastic modulus, especially using a cutoff value of the max
IMT of 1.1 mm in various lifestyle-related diseases,

Carotid Arterial Wall Elasticity

including metabolic syndrome.

Table 1. Characteristics of the study population
Risk Factor (−)(n = 101)

Risk Factor (＋)(n = 249)38.3±8.9
65 (63.1%)
22.0±2.776.4±10.0
113.1±10.5
71.9±8.541.2±8.1
69.4±9.4
178.8±27.5
82.4±52.1
58.2±13.2
98.3±23.3
86.7±8.3
4.6±0.4
5.0±1.554.7±11.6＊＊＊
143 (58.1%)
23.7±3.3＊＊＊82.6±9.0＊＊＊
128.2±16.3＊＊＊77.9±10.2＊＊＊50.3±12.5＊＊＊70.3±10.2
227.2±42.4＊＊＊
142.5±82.2＊＊＊
54.6±14.6＊＊＊
135.4±35.3＊＊＊
103.1±29.8＊＊＊5.5±1.0＊＊＊
5.5±1.3

Hypertension (%)
Hyperlipidemia (%)
Diabetes mellitus (%)
Smoking (%)
Smoking Index
Hyperuricacidemia (%)
Metabolic syndrome (%)

0
0
0
0
0
0
0

47.6
73.0
17.7
49.0
622.7±388.4
11.3
17.6

Mean IMT (mm)Mean Eθ (kPa)
Plaque occurrence (%)
baPWV (cm/sec)

0.50±0.09
144.3±39.6
2.01093.8±248.5

0.73±0.15＊＊＊165.1±52.9＊＊＊
68.6
1506.4±310.4＊＊＊

Methods
Study Population
Three hundred fifty healthy volunteers anduntreated outpatients (209 men and 141 women;mean age, 49.9 years old) with and without lifestylerelated diseases were enrolled in this study. The clinical and demographic characteristics of the study population are shown in Table 1. Subjects were assessed forthe presence of atherosclerotic risk factors as definedby the guidelines of the Japanese Societies of Hypertension 11), Atherosclerosis 12) and Diabetes Mellitus 13).
Hypertension was defined as a systolic BP ≥ 140
mmHg and/or diastolic BP ≥ 90 mmHg. Hyperlipidemia was defined as serum low-density lipoproteincholesterol (LDL-C) ≥ 140 mg/dL and/or serum triglyceride (TG) ≥ 150 mg/dL. Diabetes mellitus was
defined as a fasting plasma glucose (FPG) ≥ 126
mg/dL. Smoking was assessed using a self-administered questionnaire and was classified as current vs.
never. None of the subjects had secondary hypertension, hypertension complicated by recent cardiovascular events, atrial fibrillation, or arteriosclerosis obliterans (ASO), defined as an ankle/brachial blood pressure index (ABI) ＜ 0.9.
The subjects provided informed consent and thestudy was approved by the Institutional Ethics Committees of Tohoku Kosai Hospital and Panasonic Shikoku Electronics Co., Ltd.

783

Age (y.o.)Male
BMI (kg/m2)
Waist (cm)
SBP (mmHg)
DBP (mmHg)
PP (mmHg)
PR (bpm)
TC (mg/dL)
TG (mg/dL)
HDL-C (mg/dL)
LDL-C (mg/dL)
FPG (mg/dL)
HbA1c (%)
UA (mg/dL)＊＊＊

Risk Factor Evaluation
A detailed history of the risk factors and medical
conditions of each subject was obtained. The subjects
were requested to fast overnight without medication
until blood samples were drawn. Venous blood samples were then drawn for analysis of FPG and serum
concentrations of TC, TG, high-density lipoproteincholesterol (HDL-C) and HbA1C by standard laboratory methods. Serum LDL-C was calculated by Friedewald’s equation. None of the patients had a TG
＞ 400 mg/dL, at which the Friedewald equation is
known to yield unreliable results. Body mass index(BMI) was calculated as the weight [kg]/height2 [m2].
Metabolic Syndrome
Metabolic syndrome was defined as a waist circumference ≥ 85 cm in men and ≥ 90 cm in women,along with two or more of the following three risk factors: hypertension (blood pressure ≥ 130/85 mmHg),
dyslipidemia (HDL-C ＜ 40 mg/dL or TG ≥ 150 mg/dL), and glucose intolerance (FPG ≥ 110 mg/dL) 14).

p ＜ 0.001 vs risk factor (−)
RF: Risk factor (hypertension, diabetes mellitus, hyperlipidemia andsmoking), BMI: Body mass index, Waist: waist circumference, SBP:
Systolic blood pressure, DBP: diastolic blood pressure, PP: pulse pressure, PR: pulse rate, TC: total cholesterol, TG: triglyceride, HDL-C:
high density cholesterol, LDL-C: low density cholesterol, FPG: fasting plasma glucose, UA: uric acid, baPWV: brachio-ankle pulse wave
velocity.

Carotid IMT and Elasticity Measurements
The subjects were studied after having abstained
from caffeine, alcohol, and smoking for the previous
12 hours. The subjects rested in a supine position for
15 min in a quiet room before the baseline hemodynamic measurements were obtained. Brachial bloodpressure and pulse rate (PR) (mean of three readings)
were measured in the right arm with an automateddigital oscillometric sphygmomanometer (EW-3110;
Matsushita Electric Works, Osaka, Japan). Imaging
study of the bilateral CCAs was performed using a
newly developed high-resolution ultrasonic measurement system (prototype; Panasonic Shikoku Electron-

Yamagishi et al .

784ics,) with a center frequency of 7.5 MHz. One welltrained ultrasound technologist who regularly participates in quality control measurement sessions performed all the ultrasound examinations 9).
IMT can only be determined accurately in thefar arterial wall because only far wall IMT is definedby leading edges, which allows correct ultrasonographic representation. Therefore, the far wall at thefollowing sites was measured: 1) the distal 3 cm of thestraight part of both CCAs, 2) the distal 1 cm of bothcarotid bulbs. As in several previous studies, wedefined a plaque as a focal raised lesion using an IMT
cutoff value of 1.1 mm. The mean IMT was determined as the average of the IMT values measured atfour locations on the CCAs bilaterally, not including
the bulb. The max IMT was determined as the maximum value of the IMT measured at six locations on
the CCAs bilaterally, including the bulb, in order toassess for the presence of plaques.
The novel ultrasound system employed in thisstudy measures radial strain of the arterial wall during
one cardiac cycle and calculates the elasticity from theradial strain and the pulse pressure. The distributionof elasticity is displayed as a 2D cross-sectional color
image on B-mode images, and the image is updated
every heartbeat. For the measurement of minutechanges in thickness, the system uses the phased tracking method 5-10). The elasticity parameter was estimated at intervals of 80 μm in the depth direction
and 400 μm in the axial direction. From the maximum change in thickness during one heartbeat, theradial strain εr of each assigned layer in the arterial
wall was calculated as follows:
εr = (hmax−hmin)/hmax,(1)where hmax and hmin are the maximum and minimum
thicknesses, respectively, of an assigned layer in thewall.
The elastic modulus in the radial direction (Er)and that in the circumferential direction (Eθ) were
calculated as follows:
Er = Pulse Pressure/εr,Eθ= (1/2)×(r0/h0＋1)×Er,

(2)
(3)

where pulse pressure is the difference between the brachial systolic and diastolic blood pressure (carotid
blood pressure would be more accurate but is not easy
to measure), and h0 = hmax and r0 are the initial wall
thickness and radius of the vessel in end diastole,
respectively. Radial strain εr is caused by radial compression and circumferential stretching due to theincrease of blood pressure Δp when the longitudinalstrain is neglected. Circumferential stretching pro-duces radial strain due to the incompressibility of thearterial wall. Therefore, both the radial and circumferential stresses should be considered to evaluate elasticity; however, as shown in Eq. (2), Er is defined as theratio of pulse pressure (which corresponds to radialstress) to radial strain. Circumferential stress acting on
the cylindrical shell is not the same as pulse pressure
and also depends on r0/h0; therefore, Er is apparent
elasticity in the radial direction and depends on r0/h0
as well as on the elasticity of the arterial wall. Alternatively, Eθ was introduced to evaluate the elasticity of
the arterial wall by suppressing the influence of r0/h0 7).
The measurement reproducibility has been reported
previously 11). In the present study, the reproducibilityof the elastic modulus was assessed in 49 patients.
There were no significant differences between the firstand second visits in the SBP (p = 0.21), PR (p = 0.59),
IMT (p = 0.95) or Eθ (p = 0.69). Fig. 1A shows thelevel of agreement of Eθ. The correlation coefficientsfor SBP, PR, IMT and Eθ were 0.73, 0.90, 0.87 and0.91 (p ＜ 0.0001), respectively. The coefficients ofvariation (CV) of SBP, PR, IMT and Eθ were 12.4%,
17.0%, 33.7% and 38.6%, respectively. As shown by
the Bland-Altman plots in Fig. 1B, the mean intraobserver-intersession difference was 4.8 kPa with an SDof 25.0 kPa for Eθ. In the graph, most of the data
points fell within the 2 SD range.
Pulse Wave Velocity (PWV) Measurements
Brachial-ankle PWV (baPWV) was measured
using volume-plethysmographic apparatus (Form/ABI;Colin Co., Ltd., Komaki, Aichi, Japan) by simultaneous BP and waveform measurements of all four limbs
along with ECG and phonogram tracings. PWV wasautomatically calculated by time-phasic analysis using
the following formula: distance between two sites
divided by the pulse wave transit time. The baPWV
was measured from the ascending point of the rightbrachial pulse volume recorder to the ascending pointof each ankle pulse volume recorder. The distance
between the right brachium and ankle was estimatedas described previously 15).
Statistical Analysis
Data are expressed as the mean±SD. Statisticalanalysis was performed using the JMP ® software package (JMP 7.0.1; SAS Institute, USA), and p values＜ 0.05 were considered to denote significance. Differences among groups were analyzed by one-way analysis of variance (ANOVA) or analysis of covariance(ANCOVA). Linear regression analysis was performed
to evaluate the associations among the IMT, elastic
modulus and other clinical variables. Multiple linearCarotid Arterial Wall Elasticity

B 60

r=0.91 n=49 p<0.0001

300

E�, Difference between
the two measurements (kPa)E�, 2nd visit (kPa)

A

250
200
150
100
50
0

0

50

100

150

785

200

250

300

E�, 1st visit (kPa)

+2SD

40
20
0
-20
-40
-60

-2SD
0

50

100

150

200

250

300

E�, Mean of measurements (kPa)

Fig. 1. (A) Reproducibility of the elastic modulus, Eθ. Correlation between the measurements of Eθ values at
the 1st and 2nd visits.
(B) Bland-Altman plots showing the differences between the Eθ values at the 1st and 2nd visits plottedagainst their mean values. Lines represent the mean difference and the limits of agreement, that is, ±2SD.

regression analysis was applied to evaluate whether the
relationship between any two parameters was independent of other related factors.
Results
Associated Risk Factors
We conducted measurements at four locations in
the bilateral carotid arteries and obtained the meanvalues of IMT and Eθ. As shown in Table 1, themean IMT and mean Eθ in the group with at least
one risk factor (Risk Factor (＋)), i.e., hypertension,
hyperlipidemia, diabetes mellitus and/or smoking,were significantly larger than those in the healthygroup (Risk Factor (−)). As shown in Fig. 2, the mean
IMT and mean Eθ values were correlated with age inall patients. The strength of the correlation was in theorder of mean IMT (r = 0.74, Fig. 2A) ＞ mean Eθ
(r = 0.30, Fig. 2B); however, the mean IMT wasslightly correlated with the mean Eθ (r = 0.19,
p = 0.0006), as shown in Fig. 2C, indicating that theelastic modulus does not always increase with thickening of the IMT. The results of simple regression analysis (Table 2) revealed that the mean IMT was significantly positively correlated with age, BMI, waist circumference, SBP, DBP, TC, TG, LDL-C, FPG,
HbA1c and baPWV, and negatively correlated with
the HDL-C; the mean Eθ was significantly positively
correlated with age, BMI, waist circumference, SBP,
DBP, PR, FPG, HbA1c and baPWV.
The results of multiple regression analysis for all

the subjects, shown in Table 3, revealed age, SBP and
HbA1C to be independent determinants of the mean
IMT; however, age, SBP and PR remained independent determinants of the mean Eθ.
Analysis Using a Cutoff Value of the Max IMT
Since it has been reported that native Japanesereach an IMT of 1.1 mm at age 70 and subjects withmax IMT ＜ 1.1 mm are often classified as not having
atherosclerosis 5), we divided the participants into thetwo groups divided by a cutoff value of the max IMT,
i.e., a group with max IMT values less than 1.1 mm(max IMT ＜ 1.1 mm) and a group with max IMT
values equal to or more than 1.1 mm (max IMT ≥ 1.1mm). As shown in Table 4, the mean Eθ was significantly larger in the group with max IMT ≥1.1 mm(n = 173) than in that with max IMT ＜ 1.1 mm(n = 177).
In the group with max IMT ＜ 1.1 mm, as shownin Table 5, in simple regression analysis of the mean
IMT and mean Eθ, the correlation coefficients, except
those for the lipid levels, that is, TC, TG, HDL-C andLDL-C, showed a similar tendency in all participants;
however, in the group with max IMT ≥ 1.1 mm, thecorrelation coefficients between the mean IMT andmean Eθ with risk factors were weaker than the results
obtained from analysis of the whole subject population. A negative correlation was observed between the
PR and the mean IMT.
In regard to lipid levels, the mean Eθ did notshow a significant correlation with lipid levels in theYamagishi et al .

786

Figure 2C

B 400

r=0.74, p<0.0001

1.1
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
20

r=0.30, p<0.0001

350
mean E� (kPa)mean IMT (mm)

A 1.2

30

40

50

60

70

80

300
250
200
150
100
50
20

30

40

50

60

70

80

Age (y.o.)Age (y.o.)400

RF = 0RF > 1350

mean E� (kPa)

300
250
200
150
100

r=0.19, p=0.0006

50

0.4

0.6

0.8

1.0

1.2

mean IMT (mm)Fig. 2. Correlation of age with mean IMT (A) and mean Eθ (B). Correlation of mean IMTwith mean Eθ (C). RF = 0, group with no risk factors; RF ≥1, group with at least one
risk factor.

Table 2. Correlation coefficients of mean IMT and mean Eθwith risk factors obtained by simple regression analysis

Age
BMI
Waist
SBP
DBP
PR
TC
TG
HDL-C
LDL-C
FPG
HbA1C
UA
baPWV
＊

Mean IMT

Mean Eθ

0.74＊＊＊
0.23＊＊＊
0.29＊＊＊
0.52＊＊＊
0.28＊＊＊−0.09
0.35＊＊＊
0.25＊＊＊
＊＊
−0.16
＊＊＊
0.32
0.27＊＊＊
0.27＊＊＊
0.01
0.57＊＊＊

0.30＊＊＊
0.13＊
0.18＊＊
0.49＊＊＊
0.23＊＊＊
0.16＊＊
−0.02
0.10
−0.07
−0.01
0.18＊＊
0.18＊＊
0.05
0.39＊＊＊

p ＜ 0.05, ＊＊p ＜ 0.01, ＊＊＊p ＜ 0.001

Table 3. Multiple regression analysis for all subjects
Mean IMT

Age
Gender
BMI
SBP
PR
HDL-C
HbA1C

Mean Eθ

β

p

β

p

0.53

＜ 0.0001

−0.03

NS
NS
0.001
NS
NS
0.017

0.15
0.10
0.01
0.48
0.13
0.05
0.05

0.0133NSNS＜ 0.0001
0.0112
NS
NS

0.06
0.21
−0.10
−0.09
0.12

Table 4. Statistics of mean IMT and mean Eθ in the twogroups with max IMT ＜1.1 mm and with max IMT≥ 1.1 mm
Max IMT ＜ 1.1 mm Max IMT ≥ 1.1 mm(n = 177)(n = 173)
Mean IMT
Mean Eθ

0.54±0.11
150.6±45.8

0.78±0.14
167.9±53.3

p＜ 0.0001

0.0017

Carotid Arterial Wall Elasticity

Table 5. Correlation coefficients of mean IMT and mean Eθwith risk factors in the two groups with max IMT＜ 1.1 mm and with max IMT ≥ 1.1 mm obtainedby simple regression analysis

Age
BMI
Waist
SBP
DBP
PR
TC
TG
HDL-C
LDL-C
FPG
HbA1C
UA
baPWV

Max IMT ＜ 1.1 mm

Max IMT ≥ 1.1 mm

Mean IMT

Mean Eθ

Mean IMT

Mean Eθ

0.64＊＊＊
0.38＊＊＊
0.42＊＊＊
0.41＊＊＊
0.26＊＊
0.04
0.46＊＊＊
0.41＊＊＊
＊＊
−0.26
＊＊＊
0.43
0.35＊＊＊
0.44＊＊＊
0.11
0.47＊＊＊

0.33＊＊＊
0.17＊
0.24＊＊
0.41＊＊＊
0.19＊
0.27＊＊
0.10
0.21＊
−0.03
0.08
0.19＊
0.24＊
0.21＊
0.39＊＊＊

0.46＊＊＊−0.02−0.03
0.30＊＊＊
0.02
＊
−0.17
−0.02
−0.03
−0.09
0.15
0.09
0.14
0.09
0.41＊＊＊

0.18＊
0.04
0.06
0.50＊＊＊
0.18＊
0.13
＊
−0.23
−0.02
−0.08
＊
−0.17
0.14
0.11
−0.04
0.29＊＊

787

Correlation with the Number of Risk Factors andMetabolic Syndrome
As shown in Fig. 4A, in the group with max IMT＜ 1.1 mm, both the mean IMT and mean Eθ
increased significantly with the number of cardiovascular risk factors (hypertension, hyperlipemia, diabetes
mellitus, and smoking) (ANOVA, p ＜ 0.0001).
In addition, as shown in Fig. 4B, the mean IMT
and mean Eθ were significantly increased in metabolic
syndrome subjects with max IMT ＜ 1.1 mm (Mets,n = 41, male 34, female 7) than in non-Mets subjects
with max IMT ＜ 1.1 mm (p ＜ 0.05).
As shown by the horizontal axis in Fig. 5, thesubjects were classified into six groups based on waist
circumference and the number of risk factors. The sexand age-adjusted means of the mean IMT, mean Eθ
and baPWV were all elevated in subjects with fullblown metabolic syndrome as well as in those withpre-metabolic syndrome (p ＜ 0.05).
Discussion＊

p ＜ 0.05, ＊＊p ＜ 0.01, ＊＊＊p ＜ 0.001

1.2
1.1 r=0.08
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3 r=0.43
0 50 100 150 200 250 300
LDL-C (mg/dL)

350
300 r=-0.17

max IMT > 1.1 mm
max IMT < 1.1 mm

250

mean E� (kPa)mean IMT (mm)In this study, the relationships between the risk
factors and the elastic modulus values Eθ were examanalysis of the whole subject population (Table 2).
ined by comparing healthy volunteers and patientsOn the other hand, in the group with max IMT ≥ 1.1
with lifestyle-related diseases.
mm, while no significant correlation of the mean IMTFirst, good reproducibility of the measurement ofwith the lipid levels was observed, the mean Eθ
Eθ was shown for the same examiner. Assessment ofshowed a significant negative correlation with thethe elastic modulus is easy and the parameter is as
LDL-C and TC (Table 5 and Fig. 3). In the groupaccurate as the IMT in reflecting arterial wall elasticwith max IMT ＜ 1.1 mm, the mean IMT showed aity. We did not recognize any difference in reproducpositive correlation with TC, TG and LDL-C, and aibility at any locations.
negative correlation with HDL-C, while the mean EFigureθ
3 In general, carotid IMT is conventionally
showed a significant positive correlation with only thereported to be correlated with age, blood pressure,TG.
FPG and serum cholesterol levels, and the degree ofobesity 1-5, 16, 17). Similar to previous studies, our results

200
150
100
50 r=0.15
0 50 100 150 200 250 300
LDL-C (mg/dL)

Fig. 3. Correlation of LDL-C with mean IMT and mean Eθ.

Yamagishi et al .

788

Figure 40.8

220p<0.0001

0.7

mean E� (kPa)mean IMT (mm)

A

0.6

0.5

0

1

200

180

160

2<

Number of risk factors

0.7

without Mets
with Mets

*

0.6

0.5

0

1

2<

Number of risk factors

220*
mean E� (kPa)mean IMT (mm)B 0.8

p<0.0001

200

180

160

* p<0.05
Fig. 4. (A) Relationships between the number of risk factors and mean
IMT and mean Eθ in the group with max IMT ＜ 1.1 mm.
(B) Mean IMT and mean Eθ in the absence and presence of metabolic syndrome (Mets) in the group with max IMT ＜ 1.1 mm.

in Table 3 show that age, SBP and HbA1c were independent determinants of the mean IMT by multiple
regression analysis. On the other hand, only age, SBP
and PR were independent risk factors of an increase ofEθ.
We demonstrated that the IMT and elastic modulus might reflect different aspects of the atherosclerotic process. The conventional ultrasonic B-mode
method, including carotid IMT measurement, showsmorphological changes such as thickening and calcification. Studies with conventional integrated backscatter (IBS) analysis 18-20) only reflect a difference in echogenicity and do not directly show the elasticity of thearterial wall. In the present study, our method enabledqualitative evaluation of the carotid arterial wall withsimultaneous measurement of the elastic modulus andthe IMT. As shown in Fig. 2C, an increased IMT is
not always associated with an increased elastic modulus. As shown in Table 5, with max IMT values lessthan 1.1 mm, positive correlations were observed
between Eθ and most of the risk factors (Table 5);
however, these correlations were found to be weakerwith max IMT values equal to or greater than 1.1
mm. It would seem that mural thickness is an important consideration in assessing the correlation of theelastic modulus with coronary risk factors. This wasparticularly true for TG and LDL-C, that is, in thegroup with max IMT ＜ 1.1 mm, only TG in theserum showed a positive correlation with Eθ. On theother hand, in the group with max IMT ≥ 1.1 mm,
serum LDL-C showed a negative correlation with Eθ
(Table 5 and Fig. 3). It has been reported that carotid
stiffness, which is commonly considered as an early
indicator of vascular damage, is not increased in casesof hypercholesterolemia 21). Assessment of advanced
plaques by transmission electron microscopy revealed
intact, but attenuated, endothelium overlying the cellular deposits, lipid-containing smooth muscle cells,
partially absent basement membrane, macrophages
filled with small cytoplasmic lipid droplets, and an
extracellular matrix composed of elastic tissue, myelin
figures, necrotic debris and cholesterol clefts 22). Variations in the elastic modulus of the arterial wall occurring with changes in the relative ratios of these com-Figure 5

mean IMT (mm)0.8

Carotid Arterial Wall Elasticity

p<0.0001

0.7
0.6
0.5

mean E� (kPa)180p=0.0007

160
140
120

baPWV (cm/sec)

1700
1600

p=0.017

1500
1400
1300
1200

Number ofrisk factors

0

1

2<

Waist<85 (90) cm
n: 103
94
41

0

1

2<

Waist > 85 (90) cm
27
44
41

Fig. 5. Sex- and age-adjusted means of the mean IMT andmean Eθ and baPWV stratified by the waist circumference and number of risk factors of metabolic syndrome (hypertension, dyslipidemia, and glucose intolerance). The diagnosis of metabolic syndrome in Japanese subjects is based mainly on a waist circumferenceof ≥ 85 cm in men and ≥ 90 cm in women. Error bars
indicate the SEM. P-values were obtained by ANCOVA.

ponents may explain the weak correlations of Eθ withcoronary risk factors in the group with max IMT ≥ 1.1
mm. The inverse correlation of Eθ with LDL-C in thegroup with max IMT ≥ 1.1 mm may be explained by
the similar phenomenon of the pathogenesis of vulnerable or unstable lipid-rich lesions in acute coronary
artery syndrome 23-25). Thus, the combination of IMT
and elastic modulus of the carotid arterial wall may
help to detect atherosclerotic lesions effectively.
In the group with max IMT ＜ 1.1 mm, an accumulation of risk factors is associated with elevation ofEθ as well as IMT and has been reported previously

789

in patients who smoke 9) and have diabetes mellitus 26).
In subjects with normal intima-media thickness, thecorrelations of the overall elasticity of the common
carotid artery with coronary risk factors have beenreported to be stronger than those of conventional
IMT 27). In the present study, it was found that otherrisk factors contributed to an increase of Eθ, especiallyin the group with max IMT ＜ 1.1 mm. In early atherosclerotic lesions, impaired local availability of nitricoxide and endothelium-dependent vasodilatation may
result from either short- or long-term exposure to several risk factors. Recurrent or persistent exposure to
the risk factors may result in a state of persistent endothelial dysfunction and altered vascular wall milieu
that might promote progression of the structuralchanges associated with atherosclerosis 28). Thesechanges are proposed as one possible explanation for
the increases in elastic modulus values in association
with various risk factors in the group with max IMT＜ 1.1 mm observed in this study.
In lifestyle diseases, including metabolic syndrome, PWV is an established marker of atherosclerosis 29-31). It is correlated with the IMT and mainlyreflects the functional changes of the blood vessels,
but is not related to regional elasticity 26); in the present study, as shown in Table 2, 5, the Eθ and IMT
were correlated with baPWV. As shown in Fig. 5, we
also found that an increase in the number of risk factors for metabolic syndrome was correlated with theelastic modulus as well as IMT and the baPWV. Tsubakimoto et al. showed a similar correlation ofbaPWV with an increase in the number of risk factors
for metabolic syndrome 31).
The present study has the following limitations.
Eθ may be a better marker to show the elasticity of
the arterial wall itself because Er (apparent elasticity)
is influenced not only by increased elasticity, but also
by thickening of the arterial wall at the same location,
especially in areas with marked thickening. Eθ also
seems to be relatively unaffected by age, as shown in
Fig. 2. In Fig. 3, LDL-C was weakly but significantly
correlated with Eθ in the group with max IMT ≥ 1.1
mm. Eθ showed a decrement of elasticity, which isthought to cause the accumulation of lipid deposits.
However, a limitation of the measurement of Eθ by
the current technique is that echoic determination of
the borders of the anterior wall and the adventitia of
the posterior wall of the carotid artery is imprecise,especially at curved boundaries such as in the bulb
and severely atherosclerotic regions. Without an accurate measurement of h0/r0 as described in the Methods
section, Eθ cannot provide an accurate estimate ofelasticity.

790

Yamagishi et al .

In summary, determination of the elastic modulus of the carotid arterial wall as well as IMT measurement could be useful for assessing the local state in the
carotid artery and the systemic clinical condition associated with the accumulation of risk factors. A combination of the measurements of both elasticity and
IMT yields more information and opens up the possibility of evaluating various arteriosclerotic lesions inlifestyle-related disorders such as metabolic syndrome.
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