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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 55, no. 12, December 2008

Simultaneous Imaging of Artery-Wall
Strain and Blood Flow by High Frame Rate
Acquisition of RF Signals
Hideyuki Hasegawa, Member, IEEE, and Hiroshi Kanai
Abstract—Mechanical properties of the arterial walls are
significantly altered by atherosclerosis, and various studies
have been recently conducted to measure the regional elastic
properties (radial strain) of the arterial wall. We have developed a phase-sensitive correlation-based method, namely, thephased-tracking method, to measure the regional radial strain.
On the other hand, the measurement of blood flow is an important practical routine in the diagnosis of atherosclerosis. It
would be useful if the regional strain of the arterial wall as wellas blood flow could be assessed simultaneously. Such measurement would require a high frame rate of several kilohertz. In
this study, acquisition of ultrasonic RF echoes at a high frame
rate (about 3500 Hz) was achieved using parallel beamformingin which plane waves were transmitted only 3 times and receive beamforming created 24 beams for each transmit beam.
The accuracy in measurement of the minute radial strain was
evaluated by a basic experiment using a cylindrical phantom.
The error of the measured strain from the theoretical strain
profile and its standard deviation were 4.8% and 9.5%, respectively. Furthermore, the radial strain of a carotid arterial walland blood flow were simultaneously imaged in vivo.

I. IntroductionPathological change of the arterial wall due to atherosclerosis leads to a significant change in its mechanical properties [1], [2]. Most conventional methods
for noninvasive measurement of elasticity are based on
measurement of the pulse wave velocity [3]–[6] or that of
the change in diameter [7]–[10]. Although these methods
are useful in terms of their ability to assess the vascularelasticity noninvasively, the elasticity evaluated by thesemethods corresponds to the average elasticity in the direction of propagation and the entire circumference.
Elastography was introduced by Ophir et al. to measure the strain distribution of biological tissue by crosscorrelating 2 different RF signals, namely, that before andthat after deformation [11]–[14]. Then de Korte et al. applied elastography for strain imaging of the arterial wallwith intravascular ultrasonography (IVUS), namely, intravascular elastography [15], [16]. In the cited studies, theelasticity distribution of coronary atherosclerotic plaque
was obtained by the measured displacement distribution
in the radial direction. This measured elasticity distribution was compared with the pathological image, the reManuscript received March 2, 2008; accepted July 8, 2008.
H. Hasegawa and H. Kanai are with Department of Electronic Engineering, Graduate School of Engineering, Tohoku University, Sendai,
Japan (email: hasegawa@us.ecei.tohoku.ac.jp).
Digital Object Identifier 10.1109/TUFFC.2008.978

sults suggesting the potential for tissue characterization ofatherosclerotic plaque by measurement of its elasticity.
As a transcutaneous approach, the displacement andstrain around carotid atherosclerotic plaque have beenmeasured using tissue Doppler imaging [17]. The inhomogeneity of displacements measured upstream and downstream of atherosclerotic plaque suggests that artery-wallmotion has potential for use in the evaluation of plaquevulnerability. Furthermore, studies on noninvasive vascular elastography have also been conducted [18]–[20]. In
most of the above-mentioned methods, a correlation-based
technique is used for the estimation of the displacement
and strain of the arterial wall [15]–[18], [21]. Also, in recent years, iterative methods have been introduced for estimating 2-D displacement [19], [22].
We have been studying the measurement of the displacement and radial strain (change in thickness) of thearterial wall based on the phase-sensitive correlationbased technique and have developed the phased-tracking
method [23]–[27]. Elasticity images of the human carotid
artery have been obtained based on the measured strain
distribution, and the potential for transcutaneous tissue
characterization has been shown by classifying the elasticity images using the elasticity reference data obtained byin vitro experiments [28]–[31].
On the other hand, the measurement of blood flow is an
important practical routine in clinical situations, and theinteraction between blood flow and characteristics of thearterial wall is also important in the diagnosis of atherosclerosis. Plett et al. measured high-frequency vibrations
on the arterial wall around atherosclerotic plaque basedon the Doppler technique using a fixed ultrasonic beam
[32]. They hypothesized that such vibrations were causedby turbulence of blood flow around plaque. Such irregularvibrations and motion of the arterial wall may promote
the vulnerability of atherosclerotic plaque.
The shear stress acting on the luminal surface of thearterial wall is an important factor of the atheroscleroticchange of the arterial wall. Tortoli et al. developed a system that simultaneously measured the distension of the
carotid arterial wall and blood flow using 2 ultrasonicbeams [33]. They measured the true blood flow velocity
using 2 ultrasonic beams to estimate the wall shear rate,
together with the distension of the arterial wall.
It has been reported that the artery dilates when bloodflow increases because endothelial cells produce nitricoxide, which relaxes smooth muscle in the media, in response to the shear stress due to blood flow. Therefore,

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Hasegawa and Kanai : simultaneous imaging of artery-wall strain and blood flow

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Fig. 1. Illustration of one transmit-receive procedure in parallel beamforming.

the endothelial function can be evaluated by measuring
the dilation of the artery or the change in the mechanicalproperty of the wall [34]–[36].
In these studies, blood flow and characteristics of thearterial wall (e.g., vibration and elasticity) were not imaged simultaneously. Therefore, it would be useful if theregional strain of the arterial wall and blood flow could beassessed simultaneously. Such measurement would requirea high frame rate of several kilohertz. In this study, a highframe rate acquisition of ultrasonic RF echoes (about 3500
Hz) was achieved using parallel beam forming [37]–[42].
The accuracy in measurement of the minute radial strain
was evaluated by a basic experiment using a cylindricalphantom. Furthermore, the radial strain of a carotid arterial wall and blood flow were simultaneously imaged invivo.

II. Principles
A. Parallel Beamforming
In conventional linear scanning, both transmit and receive beamforming are performed. Therefore, the frame
rate, fFR, is determined by dividing the pulse repetition
frequency (PRF), fPRF, by the number of beams, Nbm.
Typically, frame rate fFR is about 140 Hz when fPRF =10 000 Hz and Nbm = 72.
On the other hand, only receive beamforming is performed in parallel beamforming. Many beams are createdby receive beamforming for each transmission of a wide
beam. For example, a frame rate fFR of about 3300 Hz
can be achieved when fPRF = 10 000 Hz and the numberof transmissions, Ntr, is 3. Parallel beamforming achieves
a high frame rate at the expense of the spatial resolution
because transmit beamforming is not performed.

In this study, a plane wave was transmitted using Nt =96 elements of a linear array probe equipped to a commercial diagnostic system (α-10, Aloka, Tokyo, Japan), andRF echoes were received by the same 96 elements. Fig. 1
shows an illustration of one transmit-receive procedure.
One receiving beam was formed using the RF signals received by Nc = 72 of the 96 elements. Therefore, (Nt – Nc)= 24 receiving beams could be formed for each transmission.
The number of transmissions, Ntr, was set at 3, and theelement number, {ni}, used for i-th transmission (i = 0, 1,…, Ntr) is expressed as follows:n i = (N t - N e) × i + j.

(j = 0,1, 2,..., N t)

(1)

By performing receive beamforming for each of the 3transmissions, (Nt – Nc) · Ntr = 72 receiving beams werecreated. In the receive beamforming, focusing was performed with respect to each sampled point in the scanned
region. Pulse repetition frequency fPRF was set at 10 416
Hz (observable depth: 74 mm), and a frame rate fFR of
3472 Hz was achieved. In the present study, the RF signal
received by each of the 96 elements was acquired at a sampling frequency of 40 MHz for offline processing (receive
beamforming, calculations of strain and blood flow).
In this study, the imaging plane and the surface of thelinear array probe were parallel to the arterial longitudinal
direction. Under such condition, the receiving beam at
an angle, ϕ (in Fig. 1), of 90 degrees coincided with thearterial radial direction. Therefore, receiving beams at ϕ
= 90 degrees were formed to estimate the radial strainof the arterial wall. For imaging of blood flow, receiving
beams at ϕ = 70 and 110 degrees were formed. As shownin Fig. 2, these beamformed RF signals were combined for
simultaneous imaging of the radial strain and blood flow.
Images of the radial strain of the arterial wall and blood

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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 55, no. 12, December 2008

Fig. 2. Illustration of simultaneous imaging of artery wall strain and blood flow.

angle ψ0 was set to 20 degrees, which corresponds to thebeam angles ϕ of 70 and 110 degrees. The ratio γ(ψ0) at ψ0= 20 degrees (ϕ = 70 and 110 degrees) is 0.913.
The beamformed RF signals at ϕ = 90 degrees were
processed as described in the following sections to estimate the radial strain. For imaging of blood flow, a standard double delay line canceler [44] was used for high-passfiltering of the beamformed RF signals at ϕ = 70 and 110
degrees. The power of the high-pass filtered RF signals
was estimated and displayed based on the conventional
power Doppler technique.
B. Tracking of Global Motion of the Arterial Wall

Fig. 3. Ratio γ(ψ0) of the magnitude of the grating lobe to that of themain lobe plotted as a function of steering angle ψ0.

flow in the shadowed region in the right-hand side of Fig.
2 were obtained.
The angles of the receiving beams for blood flow measurement were determined by theoretical consideration of
the magnitude of the grating lobe (see the appendix) [43].
By considering the parameters employed in this study,
wavelength λ = 150 μm (at speed of sound c0 = 1500 m/s
and center frequency f0 = 10 MHz), element pitch d = 200
μm, and w/λ ≈ 1, it is found that the magnitude of thegrating lobe becomes larger than that of the main lobe
when the steering angle ψ0 is larger than 22 degrees. Fig.
3 shows the ratio, γ(ψ0), of the magnitude of the grating
lobe to that of the main lobe theoretically calculated by(10) in the appendix. Therefore, in this study, the steering

As shown in Fig. 4, the position of the peak in the correlation function c k m (i; t) between RF signals s(x; km)and s(x = c0τ/2; km + i) in the kmth and (km + i)th frames
at depths x and x + c0τ/2 moves in relation to the movement of the arterial wall in the direction of an ultrasonicbeam, where km is defined as the frame number of the mth
key frame (k0 = 0). The region of interest (ROI) in ultrasound data, which corresponds to the region for calculation of correlation function c k m (i; t), was determined bymanually assigning the depths of the lumen-intima andmedia-adventitia boundaries, x1(km) and x N x (k m ), of thearterial wall in the first frame (km = k0 = 0) because an
automated segmentation method was not developed in thepresent study. The ROI position in another frame (km ≠ 0)
is automatically determined by the procedure described
below. The global displacement of the arterial wall must
be determined from the sampled version of the correlation
function (shown by the filled circles in Fig. 4) because RF

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Fig. 4. Illustration of correlation-based tracking (PBF: parallel beamforming).

signals {s(x; k)}(k: frame number) are sampled at a sampling frequency of fS = 1/Ts. In Fig. 4, ΔX = c0Ts/2. isthe sampling interval in length.
In conventional ultrasonic equipment based on linear
scanning, as shown in Fig. 4, neither the frame rate fFR
nor the sampling frequency fs are high. In this case, thedisplacement is estimated by finding the discrete lag t̂ (=+Ts in Fig. 4), which gives the maximum value of sampledcorrelation function ck(1; τ) between RF signals s(x; k)and s(x + c0τ/2; k +1), in the direction of lag τ. Theoretically, the maximum tracking error is half the samplinginterval (ΔX/2 = (1540 m/s)/(40 MHz)/2/2 = 9.6 μm).
On the other hand, in parallel beamforming, frame rate
fFR = 3472 Hz is much higher than that in conventional
linear scanning, whereas sampling frequency fs is the same.
Therefore, as shown in Fig. 4, the change in the positionof the peak in the correlation function between 2 consecutive frames is much smaller than sampling interval Ts. In
this study, 2 frames (= k and k + iˆc = k
in Fig. 4),
m

m

m+1

between which the global displacement of the arterial wall
is closest to one sampling interval Ts, can be determinedby finding the frame km + iˆc (iˆc = 8 in Fig. 4), which
gives the maximum value of sampled correlation function
c k m (i; t), in the direction of frame i at a certain lag τ (=+Ts in Fig. 4). In other words, the displacement between
kmth and (km + iˆc)th frames is determined to be c0Ts/2.
The maximum tracking error in this case depends on thedisplacement of the arterial wall between 2 consecutive
frames. It becomes (10 mm/s)/(3472 Hz) = 2.9 μm whenthe velocity of the arterial wall and frame rate are 10
mm/s and 3472 Hz, respectively.
The lag τ (= + Ts in Fig. 4) at which the maximum
value of sampled correlation function c k m (i; t) is searched
for in the direction of frame is determined as follows: As
described above, the displacement of the arterial wall between 2 consecutive frames is much smaller than the spacing of sampled points in parallel beamforming. Therefore,
it is sufficient to evaluate correlation functions {c k m (i; t)}at lags τ = 0, ±Ts, and ±2Ts for each i (= 0, 1, 2, …).
When c k m (i c;T s ) [or c k m (i c; -T s )] becomes larger thanc k m (i c; 0) in the (km + ic)th frame, the frame, iˆc (>ic),
in which c k m (iˆc;T s )[orc k m (iˆc; -T s )] is maximum, issearched for in the direction of the frame until c k m (i;T s )[or c k m (i; -T s )] (i > ic) becomes smaller than c k m (i; 0) or
c k m (i;2T s ) [or c k m (i; 0) or c k m (i; -2T s )]. Using this procedure, the difference (= tracking error) between the peak
positions of the true correlation function and its sampled
version is minimized as shown in Fig. 4. As describedabove, the global motion of the arterial wall can be tracked
by calculating correlation functions at only 5 lags (τ =–2Ts, –Ts,0, Ts, 2Ts).
By assigning km + 1 = km + iˆc and updating the ROI
position as x̂ 1 (km + 1) = x̂ 1 (km) + c0Ts/2 (or x̂ 1 (km) –c0Ts/2), the above procedure is repeated to track the position of the arterial wall throughout one cardiac cycle, as
shown in Fig. 5.

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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 55, no. 12, December 2008

Fig. 5. Illustration of variables.

After the removal of global motion by the above procedure, the residual displacement uj(km) between the kmth
and km + 1th frames at each sampled point j (= 1, 2, …,
NX) along each ultrasonic beam is estimated using thechange in the phase of the RF echo [45]–[47]. The residual displacement uj(km) contains global motion because
there is small tracking error as shown in Fig. 4. However,
it is sufficient to estimate the displacements between the
km th and km+1th frames because the large global motion
is almost removed (tracked) by the above procedure andthe residual displacements {uj(km)} are subsamples andsmaller than half the wavelength of the employed ultrasound. This method of estimation of the displacement distribution significantly reduces the number of calculations(there are many frames between the kmth and km+1th
frames). Radial strain εr,j(km) is obtained by estimating
the spatial gradient of the estimated displacement distribution {uj(km)}.
III. Basic Experimental Results
C. Transmitted Sound Field for Parallel Beamforming
Figs 6(a), (b), and (c) show the ultrasonic RF signals
measured by a hydrophone (Toray Engineering, Tokyo,
H025–002) placed at distances in the depth (axial) direction between the linear array probe and hydrophone of 10mm, 15 mm, and 20 mm, respectively. The output signal
from the hydrophone was acquired with an oscilloscope(Tektronix Japan Ltd., Tokyo, TDS2014) at a sampling
frequency of 1 GHz. The hydrophone scanned at every 0.5

mm in the lateral direction using a stage. A plane wave
was formed in the depth range from 10 to 20 mm, whichcorresponds to the typical depth position of the carotid
artery. The lateral width of the radiated plane wave issimilar to the transmitting aperture width of about 20
mm (96 elements). Fig. 6 shows the waveform of the RF
signal and its envelope along the white dashed line in Fig.
6(c). The width at half maximum of the envelope wasfound to be 0.4 μs.
B. Comparison of Spatial Resolutions of Conventional
Linear Scanning and Parallel Beamforming
Nylon wires (0.1 mm in diameter) embedded in agar
(403GS, Gammex, Inc., Middleton, WI) were imaged toinvestigate the spatial resolution in parallel beamforming.
Figs. 7(a) and (b) show B-mode images obtained byconventional linear scanning and parallel beamforming,
respectively. Clear images of the 4 wires were obtained.
In the measurement by conventional linear scanning, RF
signals focused in real time were acquired at a sampling
frequency of 40 MHz.
Fig. 7(c) shows the amplitude profile along the cyanlines in Fig. 7(a) and (b). The widths at half maximumof the amplitude profiles are similar. However, the widthat −20 dB is somewhat greater, which worsens the lateral resolution in the B-mode image obtained by parallel
beamforming. As shown by these results, parallel beamforming achieves a high frame rate (3472 Hz) at the expense of lateral resolution.

Hasegawa and Kanai : simultaneous imaging of artery-wall strain and blood flow

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the aperture. As can be seen in Fig. 8(b), a slight degradation of the beam profile was found when 72 elements were
employed for receive beamforming. There is a somewhat
distinct degradation in the profile obtained with 64 elements, especially in the regions indicated by the dashedovals in Fig. 8(b). Therefore, the number of elements inreceive beamforming was set at 72 in subsequent experiments.
C. Measurements of the Cylindrical Phantom for
Evaluation of Accuracy in Strain Estimation
In basic experiments for evaluation of the accuracy ofstrain estimation, a cylindrical phantom made of silicone
rubber was measured by ultrasound. The outer and innerdiameters were 10 and 8 mm, respectively. The phantom
contained 5% carbon powder (by weight) to obtain sufficient scattering from inside the wall.
Fig. 9 shows a schematic of the measurement system.
Change in pressure inside the phantom was induced by circulating a fluid using a flow pump. The change in internalpressure was measured by a pressure sensor (NEC, Tokyo,
9E02-P16). The applied pulse pressure was 48 mmHg.
To measure the elastic moduli of silicone rubber for the
calculation of the theoretical strain profile, pressure-diameter testing was conducted. In that testing, the change inexternal diameter of the phantom was measured with alaser line gauge (KEYENCE, Osaka, VG-035).
1) Pressure-Diameter Testing: Fig. 10(a) shows thetrigger signal for driving the flow pump. Figs. 10(b) and(c) show waveforms of the internal pressure and change
in external diameter of the phantom, respectively. In Fig.
10, the waveforms of 10 measurements are superimposed.
From the measured internal pressure, pi, and the change
in external diameter, 2 · Δro, the elastic modulus, E, isobtained as follows [49]:E =3 r i2 p i
3 r i2pi
3 r i2r o p i,==
2 r o2 - r i2 Dr o
2 r o2 - r i2 Dr o
2 r o2 - r i2 e qro(2)Fig. 6. Ultrasonic RF signals measured by a hydrophone placed at distances between the linear array probe and the hydrophone of (a) 10 mm,(b) 15 mm, and (c) 20 mm. The hydrophone scans in the lateral direction
using a stage. (d) Waveform of the RF signal and its envelope along thewhite dashed line in (c).

The same wires were then imaged with different numbers of elements in receive beamforming. Fig. 8(a) showsa B-mode image of the wires obtained with 88 elements inreceive beamforming. Fig. 8(b) shows amplitude profiles
along the cyan line in Fig. 8(a) obtained with 4 different
numbers of elements in receive beamforming. It is wellknown that the lateral beam profile depends on the size of

where ri and ro are the original internal and external radii,
respectively.
In Fig. 10(d), the measured internal pressure is plotted
as a function of the change in external diameter Δro. The
slope, pi/Δro, was estimated by applying the least-squares
method to the measured data shown in Fig. 10(d). The
estimated slope, pi/Δro, is shown by the solid line in Fig.
10(d). Elastic modulus E of the phantom was determined
to be 749 kPa.
2) Estimation of Radial Strain: Fig. 11(a) shows a longitudinal B-mode image of the phantom obtained by parallel beamforming. In Fig. 11(a), angles ϕ of the receiving beams were 90 degrees. The method for tracking the
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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 55, no. 12, December 2008

Fig. 7. B-mode images of fine wires embedded in agar: (a) conventional linear scanning; (b) parallel beamforming; and (c) amplitude profiles along
the cyan lines in (a) and (b), which are normalized by the maximum amplitudes of the respective profiles.

applied for all 72 ultrasonic beams. The receive beamforming was performed offline based on the method described in Section II-A to create the receiving beams at ϕ
ϕ = 90 degrees.
Fig. 11(b) shows RF echoes from the posterior wallalong the leftmost beam in Fig. 11(a) during one cycle ofthe flow pump. In Fig. 11(b), shifts of RF signals in the
direction of depth, which are caused by the global motionof the wall, have already been removed. The aligned RF
signals show that the global motion of the wall was successfully tracked.
The radial strain distribution in the posterior wall wasthen estimated by the method described in Section II-B
using the phases of RF echoes. In Fig. 11(c), the estimatedradial strains are plotted as a function of the distancefrom the luminal boundary of the posterior wall (in the
directions of the ultrasonic beams). Plots and vertical bars
show the mean and standard deviation, respectively, ateach radial position r, which were obtained by the individual strain distributions along 72 ultrasonic beams. The
solid curve in Fig. 11(c) shows the theoretical radial strain
εr,r of a homogeneous tube at each radial position r, which
was obtained using the elastic modulus E measured bypressure-diameter testing and the measured internal pressure as follows [48]:e r,r = -3r i2r o2pi.
2222 (r o - r i )r E

(3)

The estimated strain distribution agrees well with thetheoretical strain profile. Mean error emean and standard
deviation SDmean evaluated by (4) and (5) were 4.8% and9.5%, respectively.
Nx|E l[ˆ
e r, j ] - e r,r =x j|
1,
e mean =|e r,r =x j|
N x j =1

åNx

SD mean =1
N x j =1

åE l[(eˆr, j - E l[eˆr, j ]) 2],|e r,r =x j|

(4)

(5)

where Ei[·] represents the averaging with respect to beam
position l.
IV. In Vivo Simultaneous Imaging of Radial
Strain and Blood Flow
The right common carotid artery of a 33-year-old male
was measured in vivo. Fig. 12(a) shows a B-mode image

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Fig. 9. Schematic of measurement system.

Fig. 8. (a) B-mode image of fine wires embedded in agar obtained with
88 elements in receive beamforming. (b) Amplitude profiles along thecyan line in (a) obtained by four different numbers of elements in receive
beamforming.

of the artery obtained by conventional linear scanning. To
construct the image in Fig. 12(a), beamformed RF signals
sampled at 40 MHz (frame rate: 226 Hz) were envelopedetected, normalized by the maximum amplitude in theimage, and then converted into brightness.
Fig. 12(b) shows a B-mode image of the same artery obtained by parallel beamforming. A B-mode image similar
to that by conventional linear scanning could be obtained
at a very high frame rate of 3472 Hz. To construct theimage in Fig. 12(b), RF signals received by the array elements were acquired at a sampling frequency of 40 MHz,and receive beamforming was performed offline based on
the method described in Section II-A to form the receiving beams at ϕ = 90 degrees. As in the creation of the
B-mode image in Fig. 12(a), the beamformed RF signals
were envelope-detected and converted into brightness. The
envelope-detected signals (instantaneous amplitude) werenormalized by their maximum value among all frames. Let

Fig. 10. Waveforms of internal pressure pi and changes in external diameter Δro of the phantom: (a) trigger signal for the flow pump, (b) internal pressure pi, (c) change in external diameter Δro, and (d) relationshipbetween internal pressure pi and change in external diameter Δro.

us define the normalized envelope by Gp(j,l; k), where j,l, and k define depth, beam number, and frame number,respectively. The radial strain of the posterior wall was
estimated by applying the same procedure as in Section
III-D to the beamformed RF signals.
Blood flow was imaged using ultrasonic beams formed
with angles ϕ of 70 and 110 degrees. Obliquely beamformed RF signals were high-pass filtered using the standard double delay line canceler [44]. The powers of thehigh-pass filtered RF signals were estimated by the conventional power Doppler technique. The number of frames
used for calculation of the average power was 64. The rootsof the estimated average power were normalized by their

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Fig. 12. Longitudinal B-mode image of the right common carotid arteryof a 33-year-old male obtained (a) by conventional linear scanning and(b) by ultrasonic beams formed with beam angles ϕ of 90 degrees basedon parallel beamforming.

With respect to the shadowed region in the right-handside of Fig. 2, echo amplitude G(j,l; k) at each point (j, l)in the kth frame is obtained as follows:G(j, l; k) = aG p(j, l; k) + (1 - a)G o(j, l; k ).

(0 £ a £ 1)
(7)

Fig. 11. (a) B-mode image of the phantom in the longitudinal plane and(b) RF signals from the posterior wall during one cycle of the flow pump.
Shifts of RF signals in the direction of depth caused by the global motionof the wall have already been compensated for. (c) Radial strains plotted
as a function of the distance from the luminal boundary of the posteriorwall. Plots and vertical bars are means and standard deviations, respectively, for 72 ultrasonic beams.

maximum among all frames. Let us define the normalizedroots of power by G70(j,l; k) and G110(j,l; k) for beam angles ϕ of 70 and 110 degrees, respectively. As shown in Fig.
2, regions scanned by beams at these angles overlap. The
normalized root of power, Go(j,l; k), for obliquely formed
beams is defined as in (6) (see next page).

In this study, α was set at 0.9.
Fig. 13(1a) and 13(1b) show images of G(j,l; k) at the
R-wave of the electrocardiogram and 0.15 s after the Rwave. As shown in Fig. 13(1b), echoes from blood particles
are enhanced when the blood flow velocity is high (at 0.15s). Fig. 13(1c) shows a blood flow image (at 0.15 s after the
R-wave) obtained by receive beamforming with angle ϕ of
90 degrees. By comparing Fig. 13(1b) with Fig. 13(1c),the blood flow imaging was found to be much improvedby changing the angle between the directions of blood flow
and ultrasonic beam from 90 degrees by oblique receive
beamforming (ϕ = 70 and 110 degrees). Fig. 13(2) shows
blood flow images obtained by the same diagnostic equipment based on conventional linear scanning and power
Doppler imaging. Although the ability of the conventional
method to image the echo signals from blood particles atlower flow rates (in cardiac diastole) is superior to that ofthe proposed method, the proposed method successfully
imaged blood flow.
In Fig. 14, the estimated radial strain at the corresponding time is overlaid on the image of G(j,l;k). The
magnitude of the radial strain shown in Fig. 14 was comparable to that of the circumferential strain of about 7%,
which was obtained by estimating the global displacements of the anterior and posterior walls at an ultrasonicbeam located at the center of the imaged region based on
the method described in Section II-B (maximum change
in diameter: 480 μm; original diameter at the R-wave ofelectrocardiogram: 7 mm). In addition, echoes from thelumen-intima boundary of the posterior wall are visible
in the B-mode image shown in Fig. 12(b). In such cases,
it has been reported that the strain is stably measured(standard deviation between cardiac cycles: 6.4% [49]). As
shown in Fig. 14, the artery-wall strain and blood flow
were successfully imaged by the proposed method.

Hasegawa and Kanai : simultaneous imaging of artery-wall strain and blood flowìïG 70(j, l; k ) or G 110(j, l; k )ïG o(j, l; k ) = ïíG 70(j, l; k ) + G 110(j, l; k )ïïïî2(beams at f = 70 and 110 degrees do not overlap),(beams at f = 70 and 110 degrees overlap).

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(6)

Fig. 13. Blood flow imaging: (1a) and (1b) blood flow images at 0 s and 0.15 s after R-wave of electrocardiogram obtained by parallel beamforming with receive beamforming at ϕ = 70 and 110 degrees; (1c) blood flow image at 0.15 s after R-wave obtained by parallel beamforming withreceive beamforming at ϕ = 90 degrees; (2a) and (2b) blood flow images obtained by conventional diagnostic equipment based on power Doppler
imaging.

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Fig. 14. Simultaneous imaging of artery-wall strain and blood flow. At (a) 0 s, (b) 0.075 s, (c) 0.15 s, (d) 0.225 s, (e) 0.3 s, (f) 0.375 s, (g) 0.45 s, (h)0.525 s, (i) 0.6 s, (j) 0.75 s, (k) 0.825 s, and (l) 0.9 s after the R-wave of electrocardiogram.

V. Discussion
In the method herein proposed, the interval of frames
between which the phase shift of echoes is estimated (interval of 2 consecutive key frames) is much larger than theoriginal frame rate of 3472 Hz. However, aliasing does notoccur because the estimated displacement between 2 key
frames is the distance corresponding to the interval of thepoints sampled, in this study, 19.25 μm (speed of sound:
1540 m/s). Therefore, the residual displacements at otherradial positions after compensation of global motion areless than 19.25 μm. When the center frequency of the received RF echo is exactly the same as the nominal center
frequency (10 MHz) of the employed ultrasonic probe, adisplacement of 19.25 μm produces a phase shift of RF
echoes of π/2 (corresponding to 38.5 μm). The residual

displacement at each radial position after compensationof global motion is smaller than 19.25 μm, which is lessthan the aliasing limit of 38.5 μm at 10 MHz. In addition,
only the strain of the posterior wall was imaged because
there were echoes from tissues between the skin surface
and the anterior wall, and such echoes would influence
the strain estimation. The possible sources of such echoes
were the side lobe and multiple reflection. In this study,
the influence of the signal-to-noise ratio of the echo signal
on the accuracy of strain estimation was not investigated,
and a quantitative evaluation of such influences would be
required. With respect to the in vivo experimental results
shown in this paper, the signal-to-noise ratio in the in vivo
experiment was similar to that in the basic experimental
result using the phantom (mean and standard deviationof normalized amplitudes of echoes in all correlation win-Hasegawa and Kanai : simultaneous imaging of artery-wall strain and blood flow

Fig. 15. (a) Blood flow image G(j,l; k) at 0.15 s after R-wave of electrocardiogram obtained by parallel beamforming at α = 0.5. (b) Bloodflow image at 0.15 s after R-wave obtained by parallel beamforming.
Regions where the normalized power Go(j,l; k) were larger than 0.2 arecolored.

dows used for strain estimation: 0.26 ± 0.22 (phantom),
0.19 ± 0.16 (carotid)). Therefore, the accuracy of strain
estimation in the in vivo experiment was considered to be
similar to that in the basic experiment.
In blood flow imaging by parallel beamforming, transmit beams are not focused on and the intensity of radiatedultrasound is much lower than that in conventional linear scanning. Therefore, the high-pass filtered RF signals
must be amplified significantly to visualize weak echoesfrom blood particles. In this process, background noise isalso amplified, which leads to degradation of the contrastof the blood flow image G(j,l; k) (Fig. 13(1-a)) in comparison with the B-mode image Gp(j,l; k), shown in Fig.
12(b). Image degradation at lower α in (7) is significant
due to the amplification of noise as shown in Fig. 15(a);the image in Fig. 15(a) was obtained at α = 0.5. To avoid
a significant degradation of a blood flow image, α was
empirically assigned by an operator.
The parameter α was introduced because the discrimination of echoes from blood particles from those fromslowly moving tissue by high-pass filtration was not sufficient. To improve the discrimination, receiving beams
were obliquely formed (steered angle: ±20 degrees). However, the discrimination was not still sufficient. Colored
regions in Fig. 15(b) show the regions where the normalized root of power Go(j,l; k) for obliquely formed beams
is larger than 0.2. As shown in Fig. 15(b), clutter fromthe arterial wall was not perfectly removed. Therefore, in2637

this study, blood flow was displayed in gray scale based on(7) without thresholding. Further investigation is requiredfor improving the discrimination (e.g., increase in the intensity of a transmit beam and improvement of clutter
filtering).
As described above, in this study, blood flow was qualitatively imaged by high-pass filtering of received RF echoes.
Ultrasonic beams for blood flow imaging were formed at
2 different beam angles, the angles of these ultrasonicbeams relative to the direction of blood flow being different. Therefore, there would be discontinuities in an image
when the flow velocity is quantitatively imaged based on
the standard Doppler technique because the estimation offlow velocity significantly depends on the angle between
the direction of flow and the ultrasonic beam. In future
work, the quantitative estimation of blood flow velocity
will be investigated to overcome such problems.
In this study, RF signals received by transducer elements were acquired for offline receive beamforming. In
the current system, processing of dynamic focusing at 3
different beam angles and calculation of strain and bloodflow is difficult during a frame interval of about 0.3 ms(at a frame rate of 3500 Hz). Real-time implementation of
the proposed method requires further optimization of thealgorithm and development of specific hardware. In addition, an automated method for detection of the arterial
wall in ultrasound data needs to be developed for realtime processing.

VI. Conclusions
In this study, a high frame rate acquisition of RF echoes(3472 Hz) was achieved using parallel beamforming, which
realizes the simultaneous imaging of the artery-wall strain
and blood flow. In the estimation of strain, the global
motion of the arterial wall was tracked based on the correlation between RF signals, and the displacement distribution in the wall was then estimated using the phasesof RF signals. The accuracy of the strain estimation was
validated by a basic experiment using a cylindrical phantom. Furthermore, the wall strain and blood flow of a carotid artery was successfully imaged in vivo. The proposed
method would provide useful information for diagnosis ofatherosclerosis.
Appendix
Relationship between Steering Beam Angle andGrating Lobe
The directivity of a linear array D(ψ) can be expressedas the product of the directivity of an array Da(ψ) andthat of an element De(ψ) [43] as follows:
D(y) = D e(y) × D a(y),

(8)

2638

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 55, no. 12, December 2008

where the angle ψ is defined as ψ = 90° – ϕ. The directivity Da(ψ) shows that of an array composed of omnidirectional point sources (elements), and Da(ψ) is expressed by
the number of sources Ne and the spacing of sources d as
follows:
ïì N epd
ïü(sin y - sin y 0) ïý
sin ïíïïî l
ïïþ
,D a(y) =ïìï pdïüïN e sin í (sin y - sin y 0) ý
ïïî l
ïïþ

(9)

where ψ0 and λ are the steering angle and wavelength ofultrasound in tissue, respectively. The directivity of anrectangular element De(ψ) is expressed by the width of anelement w as follows:æ pwö
sin çç
sin y ÷÷÷çè l
øD e(y) =
.
pw
sin y
l

(10)

Acknowledgments
We are grateful to Panasonic Co., Ltd. for providing
the cylindrical phantom used in this study.
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Hideyuki Hasegawa was born in Oyama, Japan, in 1973. He received the B.E. degree fromTohoku University, Sendai, Japan, in 1996. He received the Ph.D. degree from Tohoku University
in 2001. He is presently an associate professor at
the Graduate School of Biomedical Engineering,Tohoku University. His main research interest is
medical ultrasound, especially diagnosis of atherosclerosis based on measurements of motion andmechanical properties of the arterial wall. Dr.
Hasegawa is a member of the IEEE, the Acoustical Society of Japan, the Japan Society of Ultrasonics in Medicine, andthe Institute of Electronics, Information and Communication Engineers.

Hiroshi Kanai was born in Matsumoto, Japan,
on November 29, 1958. He received a B.E. degreefrom Tohoku University, Sendai, Japan, in 1981,
and M.E. and Ph.D. degrees in electrical engineering, also from Tohoku University, in 1983 and1986, respectively. From 1986 to 1988, he was with
the Education Center for Information Processing,Tohoku University, as a research associate. From1990 to 1992, he was a lecturer in the Department
of Electrical Engineering, Faculty of Engineering,Tohoku University. From 1992 to 2001, he was an
associate professor in the Department of Electrical Engineering, Facultyof Engineering, Tohoku University. Since 2001, he has been a professor
in the Department of Electronic Engineering, Graduate School of Engineering, Tohoku University.
His present interests are in ultrasonic measurement and digital signal
processing for diagnosis of heart diseases and arteriosclerosis. Dr. Kanai
is a member of the Acoustical Society of Japan, the Institute of Electronics Information and Communication Engineering of Japan, the Japan
Society of Ultrasonics in Medicine, Japan Society of Medical Electronics
and Biological Engineering, and the Japanese Circulation Society.