ieee transactions on ultrasonics, ferroelectrics, and frequency control, vol. 46, no. 5, september 1999

1229

Real-Time Measurements of Local Myocardium
Motion and Arterial Wall Thickening
Hiroshi Kanai, Member, IEEE, Yoshiro Koiwa, and Jianping Zhang
Abstract—We have already developed a new method,
namely, the phased tracking method, to track the movement of the heart wall and arterial wall accurately basedon both the phase and magnitude of the demodulated signals to determine the instantaneous position of an object.
This method has been realized by an oﬀ-line measurement
system, which cannot be applied to transient evaluation of
rapid response of the cardiovascular system to physiological stress. In this paper, therefore, a real-time system tomeasure change in the thickness of the myocardium and thearterial wall is presented. In this system, an analytic signal
from standard ultrasonic diagnostic equipment is analogueto-digital (A/D) converted at a sampling frequency of 1
MHz. By pipelining and parallel processing using four highspeed digital signal processing (DSP) chips, the method justdescribed is realized in real time. The tracking results forboth sides of the heart and/or arterial wall are superimposed on the M (motion)-mode image in the work station(WS), and the thickness changes of the heart and/or arterial wall are also displayed and digital-to-analogue (D/A)
converted in real time. From the regional change in thickness of the heart wall, spatial distribution of myocardial
motility and contractility can be evaluated. For the arterial
wall, its local elasticity can be evaluated by referring to theblood pressure. In in vivo experiments, the rapid responseof the change in wall thickness of the carotid artery to thedose of the nitroglycerine (NTG) is evaluated. This new
real-time system oﬀers potential for quantitative diagnosisof myocardial motility, early stage atherosclerosis, and thetransient evaluation of the rapid response of the cardiovascular system to physiological stress.

I. Introductionn the interventricular septum (IVS) and the posteriorwall of the left ventricle (LV) shown in Fig. 1(1-a),thickening and thinning periodically occur during myocardial contraction and relaxation as illustrated in Fig. 1(1b) and (1-c). This thickening and thinning in each local
area of the heart wall corresponds to the regional myocardial motility, which originates from the sliding of the
myosin and actin ﬁbers. To realize this evaluation transcutaneously using ultrasound, it is necessary to track the
instantaneous positions xA (t) and xB (t) of the two points,

I

Manuscript received September 29, 1998; accepted March 25, 1999.
This work was supported in part by a Grant-in-Aid for ScientiﬁcResearch from the Ministry of Education, Science and Culture ofJapan.
H. Kanai is with the Department of Electrical Engineering, Graduate School of Engineering, Tohoku University, Sendai 980-8579,
Japan (e-mail: hkanai@ecei.tohoku.ac.jp).
Y. Koiwa is with the First Department of Internal Medicine, Tohoku University School of Medicine, Seiryou-machi, Aoba-ku, Sendai
980-8574, Japan.
J. Zhang is with Section 2, Technical Division, Systems Design
Service Corporation, Daito Building 3F, Takada 3-32-1, Toshiamaku, Tokyo 171, Japan.

A and B, which are preset at the end-diastole along theultrasonic beam in the IVS or the posterior wall. Then, thechange in thickness, ∆hAB (t), between these two points A
and B from their thickness hAB (t0 ) at the end-diastole isobtained from the diﬀerence between xA (t) and xB (t) as
illustrated in Fig. 1(1-c) if the ultrasonic beam is almost
perpendicular to the wall during the cardiac cycle [1].
In the heart, there are complex movements, that is, torsional, sagittal, and horizontal movements, especially during cardiac contraction. However, as shown by the magnetic resonance (MR) tagging pattern, there are far fewer
torsional, sagittal, and horizontal movements in the IVS
compared with those in the right ventricular anterior wall,the LV posterior wall, and the apex [2]. Thus, our measurements have been applied to the IVS to eliminate complexity of the three-dimensional motions during the cardiac
cycle [1],[3].
As for the arterial wall, in the ejection period, thepressure wave comes from the LV and expands the lumen. Thus, the arterial wall becomes slightly thin during the ejection period. In the literature, measurementof the change in diameter, ∆dBA (t), of the lumen has
been reported. From ∆dBA (t), the elasticity of the arterial wall can be diagnosed by assuming that it is homogeneously changed in the circumferential direction becauseof atherosclerosis.
On the other hand, measurement of the change in thickness makes it possible to evaluate the elasticity of the arterial wall in each local area; the locality in the circumferential direction is indispensable to diagnosis of the innercharacteristics of atherosclerotic plaque. For this purpose,by tracking the instantaneous positions, xA (t) and xB (t),which are, respectively, preset to xA (t0 ) and xB (t0 ) at theend diastole along the ultrasonic beam in the arterial wall
as illustrated in Fig. 1(2-b), the small change in wall thickness, ∆hAB (t), between these two points, A and B, is obtained as illustrated in Fig. 1(2-c) if the ultrasonic beamis almost perpendicular to the wall. From the ratio of thechange in thickness, ∆hAB (t), to the thickness, hAB (t0 ),between these points preset at the end diastole, the deformation is obtained. If the deformation is suﬃciently small
and is in the linear regime, it shows the strain and theregional elasticity of the wall can be approximately evaluated using the pulse pressure measured at the brachialartery [4]. Therefore, the transcutaneous measurement of
the change in thickness of the regional area of the heart
wall or the arterial wall during each cardiac cycle provides the essential tools for diagnosis of heart diseases oratherosclerosis.

c 1999 IEEE
0885–3010/99$10.00 1230

ieee transactions on ultrasonics, ferroelectrics, and frequency control, vol. 46, no. 5, september 1999

Fig. 1. An illustration explaining the procedure of measuring the change in thickness, ∆hAB (t), of the heart/arterial wall, and the change
in diameter, ∆dBA (t), of the lumen by tracking the movement xA (t) and xB (t) of points A and B respectively, preset in the heart wall
and arterial wall along the ultrasonic beam. (1) for the IVS; (2) for the arterial wall. (a) Cross-sectional image, (b) displacement xA (t) andxB (t), (c) change in thickness, ∆hAB (t), of the heart/arterial wall and change in diameter, ∆dBA (t).

The accuracy required for the simultaneous measurement of the instantaneous positions xA (t) and xB (t) of
points A and B is estimated as follows. For the IVS, forexample, the thickness is about 10 mm for a normal young
adult, and the change in thickness is approximately 1 to
3 mm during one cardiac cycle [3]. Thus, when the distance of 0.75 mm between these two points in the LV wallis preset at the end diastole, the minimum value of the
thickness change, ∆hAB (t), between these points is approximately 75 µm. For the carotid artery, on the other
hand, the thickness of the wall is about 1 mm, and thechange in thickness, ∆hAB (t), is less than 100 µm during
one cardiac cycle in normal adults [4].
For either case, therefore, the necessary spatial resolution in the measurement of instantaneous position as a
waveform is at least 10 µm. If the velocity signals vA (t)and vB (t) of these two points, A and B, are detectedbased on the pulse Doppler method, the necessary accuracy of the velocity measurement is about 10 µm/200 µs=0.05 m/s when the pulse repetition frequency (PRF) of
the transmission-pulse train is 5 kHz (=1/200 µs). If theequivalent sampling period of the velocity signal vi (t) islonger than 200 µs as in the FFT (fast Fourier transform)based standard Doppler system, for example, more accurate velocity measurement is required. Because there ismotion with large amplitude (about ±10 mm) caused by
the heartbeat at the point in the LV wall, moreover, thedynamic range required for the measurement of the movement is about 1000 (10 mm/10 µm) = 60 dB in amplitude.
Though M-mode echocardiography oﬀers an advantage
in critically examining at the motion pattern of the LV,
its spatial resolution along the ultrasonic beam is limited

to a few wavelengths, namely, at most about 1 mm for ultrasound of 3 MHz because an M-mode image is displayed
based on the amplitude of the reﬂected ultrasound. On
the other hand, there have been numerous elaborate techniques proposed for noninvasive measurement of the velocity of the blood ﬂow in the heart or the arteries based on
the Doppler eﬀect [5]–[14]. Moreover, several methods, including the phase-locked-loop (PLL) techniques, have been
proposed to measure rough changes in the diameter of thearterial walls by tracking arterial wall displacement in realtime [15]–[33].
For the accurate detection of the velocity signal, thatis, the instantaneous movement, on or in the heart wallor arterial wall, we have developed the following phased
tracking method [3]. Using this method, by calculating theauto-correlation function under the constraint least meansquare technique between the sequentially received echoes,
the phase change caused by movement of the preset point(i ) during the pulse repetition period ∆T (1/PRF) is determined accurately, and the average velocity vi (t) during
the period is obtained. By adding the product of vi (t) and∆T to the previous object position xi (t), the next position,xi (t+∆T ), is estimated as xi (t)+vi (t)×∆T . This method
has been conﬁrmed by experiments using a water tank andhas been applied to the in vivo detection of small velocity signals with suﬃcient reproducibility at points in the
IVS of the human heart [3]. The detected velocity signal
shows the rapid motion, including high frequency components with small amplitudes, which cannot be recognizedby M-mode echocardiography.
Moreover, the method has been applied to multiple
points preset along an ultrasonic beam in the LV wall sokanai et al.: myocardium motion and arterial wall thickening

1231

that the instantaneous object positions {xi (t)} and the velocity signals {vi (t)} are obtained for these multiple points{i} in the LV wall [1]. From the results, by deleting theparallel component, the thickness change components during myocardial contraction/relaxation are detected. Then,
their spatial distribution is obtained and is superimposedon the M-mode image using a color code.
Spectrum analysis was ﬁrst applied to the resultant noninvasively detected velocity signals {vi (t)} to identify thefrequency band for the components, from 25 to 90 Hz, because of the myocardial thickening and thinning, whichshows the novel possibility of diagnosis of the local myocardium [1], [3].
However, the method of measurement herein describedhas been developed by batch processing on an oﬀ-line system in our laboratory. The development and application ofreal-time processing signiﬁcantly facilitate its use in clinical diagnosis and will oﬀer a new tool for clinical examination. For example, NTG is used medically as a vasodilator
for rapid treatment of angina pectoris [34]. Real-time measurement of the transient change in thickness of the heart
wall or the arterial wall just after the sublingual administration of NTG will be of use in direct evaluation of the
response of the heart wall or the arterial wall to the antianginal drug. At the same time, real-time monitoring during
clinical intervention is essential to avoid hyper-responses,
such as serious hypotension and/or arrhythmia.
Because the quantity of A/D-converted data is too greatand because it is time-consuming to transfer the data fromthe A/D converter to a computer in the oﬀ-line system,
real-time processing is indispensable to realize new clinicalexamination tools for evaluation of transient change of thetolerance test.
For the real-time realization of the color-Doppler
method [14] and tissue Doppler imaging [35],[36], a highspeed digital circuit, such as an application-speciﬁc integrated circuit (ASIC), is employed to calculate the complex auto-correlation between the sequentially received
echoes. In the tracking processing of the instantaneous
position, the object position is moved along the ultrasonicbeam based on the previous results from the complex autocorrelator. For more ﬂexible processing, we employ hardware based on high-speed ﬂoating-point DSP chips and aWS.
In the hardware system employed in this study, thereceived echo is quadrature demodulated, and then the
resultant in-phase and quadrature signals are simultaneously A/D converted at a sampling frequency of 1 MHz
with a 12-bit accuracy. For these large-scale data, it is notpossible to transfer them from the A/D converter to the
DSP boards using the VME-bus (versa module Europeanbus; the IEEE1024 standard) because its transfer speed
is not so high. Much time-consuming processing is necessary from the A/D conversion to a real-time display of the
M-mode image, the resultant waveforms, and the tracking
results on the CRT (cathode-ray tube) of the WS. Thus,
we employ four DSP chips. The A/D converter boards areconnected directly to the DSP board. All of the processingin the four DSP should be synchronized with the transmission timing of the ultrasonic pulse, and every processassigned to each DSP chip should be terminated during
the pulse repetition period, ∆T .
In this paper, after a brief description of the principleof the measurement of thickening and thinning, the architecture of the developed real-time system is described,
especially with respect to the previously mentioned problems to be solved. The accuracy of the system is conﬁrmed
by experiments using a water tank, and then the real-timesystem is applied to in vivo experiments on the measurement of thickening and thinning in the human IVS walland the carotid arterial wall. Finally, the system is applied to the transient evaluation of the rapid response of
the change in wall thickness of the artery to the dose of
NTG.
II. Principles of Measurement of Change
in Thickness of the WallBy referring to the M-mode image, which is reconstructed from the A/D-converted data, we manually presetxA (t0 ) and xB (t0 ) as the depth of two points, A and B,
in the heart wall or arterial wall along an ultrasonic beam
at a time t0 of R-wave of the electrocardiogram (ECG) as
illustrated in Fig. 1(1-b) and (2-b). We assume that both
point A and point B have only a velocity component thatis parallel to the direction of the beam if the direction andposition of the ultrasonic beam are appropriately selected
in order to be perpendicular to the wall during the cardiac cycle. The principle of the accurate detection of thechange in thickness, ∆hAB (t), between points A and B in
the wall is brieﬂy described as follows by referring to [3].
A. For Measurement of Instantaneous
Movement ∆di (t) of Object (i)RF pulses with an angular-frequency of ω0 = 2πf0 are
transmitted at a time interval of ∆T from an ultrasonictransducer. The ultrasonic pulse reﬂected by the object (i)(i=A, B) is received by the same ultrasonic transducer.
The output signal is ampliﬁed, and quadrature demodulation is applied to the signal. The resultant in-phase andquadrature signals for each transmitted pulse are simultaneously A/D converted at a sampling frequency 1/TS ,and these two signals are combined into a complex signal, y(xi ; t), where xi (t) and its simple expression xi denote the depth of the object (i) from the ultrasonic transducer as shown in Fig. 2. Because xi (t) is given by the
product of the acoustic velocity, c0 , and the instantaneous
period, τi (t), required for one-way transmission from theultrasonic transducer to the object (i), phase θ(xi ; t) of
signal y(xi ; t) is given by the angular frequency, ω0 , multiplied by twice the delay time, τi (t). Thus, the phaseshift ∆θ(xi ; t + ∆T ) of the subsequently received signals

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exactly coincides with the well-known conventional complex auto-correlation procedure, except for the recursive
adjustment of the sample window position based on thedisplacement estimated by the integration of the instantaneous velocity as described subsequently in (4). The range
for averaging of the auto-correlation is denoted by ±∆x.
C. For Tracking of the Object Position xi (t)Fig. 2. An illustration of the measurement of change in thickness,∆hAB (t), between two points A and B in the pulse repetition period∆T just after t0 .

y(xi ; t + ∆T ) from y(xi ; t) in the interval ∆T is given by∆θ(xi ; t + ∆T ) = θ(xi ; t + ∆T ) − θ(xi ; t)
= 2ω0 {τi (t + ∆T ) − τi (t)}2ω0∆di (t + ∆T ) [radian]
=
c0

(1)

where ∆di (t+∆T ) = xi (t+∆T )−xi (t) is the instantaneous
movement of the object (i) in the period ∆T after time t
as illustrated in Fig. 2. Then, ∆di (t + ∆T ) is given fromthe measured data by∆di (t + ∆T ) = c0 ·∆θ(xi ; t + ∆T )
2ω0

(m).

(2)

i (t + ∆T ) by ∆T , the mean velocity averBy dividing ∆daged during the ∆T is given as follows:
i (t + ∆T )∆T∆dvi t +
=
2
∆T

(m/s)

(3)

where t + ∆T /2 shows the middle between t and t + ∆T .
The velocity signal and its spectrum are eﬀective in the
diagnosis of local myocardium [1].
B. For Accurate Determinationof the Phase Change ∆θ(xi ; t)Because it is essential for the measurement to determine the phase change ∆θ(xi ; t) of (2) during period ∆Taccurately, the constraint least squares method is introduced into the determination procedure of the instantaneous movement of the object position xi (t) in [3]. As described in the last paragraph of Section II C of [3], however,for the case of the sampling period TS = 1 µs, which is employed in the real-time system developed in this paper, thequantized movement (lag) δx of the object during ∆T isless than the spatial resolution ∆xS = TS ×c0 /2 = 750µm.
Thus, the possible quantized lag value of δx is always 0, andthe previously mentioned constraint least squares method

The position xi (t) of the object (i ) in the heart wallchanges by more than 10 mm because of the heartbeat in
one cardiac cycle. Even for a point in the carotid artery,the movement caused by the arrival of the pulsive wave isabout several hundred micrometers. It is, therefore, necessary to track the instantaneous object position xi (t). For
i (t + ∆T )this purpose, by accumulating the estimate ∆dof the instantaneous movement in (2), the next object position xi (t + ∆T ) is estimated by
i (t + ∆T ) (m) (i = A, B).
xi (t + ∆T ) = xi (t) + ∆d(4)
i (t + ∆T ) and theThus, the instantaneous movement ∆dnext object position xi (t + ∆T ) are simultaneously determined as illustrated in Fig. 2 and are obtained as waveforms.
When the time interval, ∆T , of the transmission of the
RF pulses is about 200 µs, the maximum value of the instantaneous movement, ∆di (t), of an object (i) in the heart
wall is about 20 µm during the time interval ∆T because
the velocity is less than 0.1 m/s. For the carotid artery,the maximum value of ∆di (t) is about 1 µm. Because thequadrature-demodulated signals are A/D converted in asampling interval, TS , of 1 µs in this paper, the spatial
resolution ∆xS = TS × c0 /2 = 750 µm in the direction of
depth. As illustrated in Fig. 2, therefore, the instantaneous
movement, ∆di (t), in the heart wall and the arterial wall
is much less than ∆xS and the wavelength of about 200µm at 7 MHz or 500 µm at 3 MHz. The resultant estimatexi (t) of the next object position of (4) in the just mentioned procedure is represented not by a discrete value of
every ∆xS but by the continuous value that is determined i ; t) in (1). Thus, accurate
from the phase diﬀerence ∆θ(xtracking of the object is realized by this method, and small
instantaneous movement of micron order is determined.
D. For Measurement of Thickness Change in the WallBy simultaneously applying the previously mentioned
method to each of the two points A and B along the ultrasonic beam in the heart wall or the arterial wall, the instantaneous movement, ∆di (t), and the object positions,xi (t), are estimated for i = A and B as shown in Fig.
1(1-b) or (2-b). At the beginning of this procedure, theinitial positions (depth) xA (t0 ) and xB (t0 ) of the points
at a time t0 are manually preset. Then, at every arrival of
the R-wave of the ECG, each displacement, xi (t), of eachpoint (i) is reset to the initial position xi (t0 ). For the heartkanai et al.: myocardium motion and arterial wall thickening

1233

wall, xA (t0 ) and xB (t0 ) are in the myocardium of the IVS
or in the posterior wall of the LV, and, for the carotid
artery, xA (t0 ) and xB (t0 ) correspond to the positions on
the intima and the adventitia of the anterior or posteriorwall, respectively.
Let us assume that the ultrasonic beam is almost perpendicular to the wall during one cardiac cycle and thatthe direction of velocity of each point (i) in the wall is parallel to the direction of the ultrasonic beam. Thus, fromthe diﬀerence between the instantaneous object positionsxA (t) and xB (t), the thickness of the local region, which
is denoted by hAB (t), is obtained byhAB (t) = x
B (t) − x
A (t) (m).

(5)

The change in thickness, ∆hAB (t), from the initial valuehAB (t0 ) at time t0 , is obtained from the estimated velocities, vA (t) and vB (t), as follows:∆hAB (t) = hAB (t) − hAB (t0 ) t{
vB (t) − v=A (t)}dt (m).

(6)

t0

For the arterial wall, moreover, by dividing the absolutevalue of ∆hAB (t) by the initial minimum distance hAB (t0 ),the deformation SAB (t) between the points in the direction
of the radius is deﬁned by S
AB (t) = |∆hAB (t)|/hAB (t0 ).
If the deformation is suﬃciently small and is in the linear
regime, the deformation shows strain.

Fig. 3. An overview of the developed real-time system (lower), whichis connected with the standard ultrasonic diagnostic system (upper).

III. Design of A Real-Time Measurement System
A. Architecture of the System
To realize the just mentioned procedure in real time, wehave designed the following system using four high-speed
ﬂoating DSP chips from DSP(A) to DSP(D) and a host
WS (SUN hyperSPARC, 150 MHz, Force Computer Inc.,San Jose, CA), which controls the DSP via the VME-bus.
The whole structure of the real-time system is shown in
Fig. 3. In the ultrasonic diagnostic equipment, the standard B-mode cross-sectional image and M-mode image aredisplayed to identify the measurement points on the wall.
The area around a measurement point is assigned by using
the sample volume, the position of which is controlled bya tracking ball. The signal z(t) received by the ultrasonictransducer of Fig. 3 is ampliﬁed and quadrature demodulated in the equipment.
The resultant analytic signal y(x; t) is A/D convertedwith a two-channel 12-bit A/D converter at a sampling interval, TS , of 1 µs. The spatial resolution ∆xS = TS · c0 /2
in the depth direction is about 0.75 mm. As shown in Fig.
4, the analytic signal is digitized only for the period, thestarting point of which is marked by the sample volume.
The signal that indicates the position of the sample volume
is generated in the modiﬁed ultrasonic diagnostic system
and input into a signal generator (AFG2020, Tektronix,

Fig. 4. Upper: An illustration explaining the timing of the sampling
length and waveforms. Lower: A timing chart showing the relationships among the ﬁve tasks based on their pipelining and the parallel
processing between tasks TD/A and Tsave .

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Wilsonville, OR) as a trigger, where the signal generator
is completely synchronous with the master clock of the ultrasonic diagnostic equipment. The length, T0 , of the sampled period and the number of the data, N0 = T0 /TS , inpoints for each frame are assigned in advance, both in thesignal generator and in the subpanel for parameter settingin the real-time system. For this intermittent digitization,a sampling clock of 1 MHz is generated only for the period
T0 by the signal generator as shown in Fig. 4. The ECG
and phonocardiogram (PCG) are also digitized.
B. Tasks in the System
The following ﬁve tasks, termed TA/D , Tcal , TD/A ,Tsave , and Tdisp , are necessary for the measurement system
as shown in Fig. 4.
1. TA/D : Task for A/D Conversion in DSP(A):• Intermittent acquisition of N0 -point in-phase andquadrature signals, ECG, and PCG using the
FIFO (fast-in ﬁrst-out memory) during a length of
T0 seconds from each transmitted pulse as shownin Fig. 4.
• Conversion of the acquired signals from integertype to ﬂoating-point-type and their packing into
structure-type data DA/D .
• Transfer of the data DA/D to the DSP (B) via thecommunication port (CP).
2. Tcal : Task for Determining Instantaneous Movement
and Tracking in the DSP(B):• Acquisition of data DA/D from task TA/D .
• The processing described in Section II.

(a) calculation of complex auto-correlation in
Section IIB between successively received
data.
(b) calculation of instantaneous phase shifts
 A ; t) and ∆θ(x
 B ; t) for points A and B.
∆θ(x(c) determination of the instantaneous movement, ∆dA (t) and ∆dB (t), of (2).
(d) accumulation of ∆dA (t) and ∆dB (t) to determine the next displacement xA (t) and xB (t),which are necessary for the tracking of the object points.
• Packing of data ∆dA (t), ∆dB (t), xA (t), xB (t), theoriginal analytic signal y(x; t), the ECG, and the
PCG into structure-type data Dcal .
• Transfer of data Dcal to the DSP(C) via the CP.
3. TD/A : Task in the DSP(B) for D/A Conversion:• Conversion of the data type of ∆dA (t) and ∆dB (t)in the data Dcal from the ﬂoating-point-type tothe integer-type and transfer of the resultant data
to the FIFO, which is connected to the twochannel D/A converter.
4. Tsave : Task in the DSP(C) for Updating Data to be
Saved on the Hard Disk:• Transfer of data Dcal to update data Dsave in aring buﬀer of the global memory so that the latest
10-s data are always kept in the memory.
• After the “SAVE” button is clicked in the main
panel of the system, transfer of the current headaddress of data Dsave in the ring buﬀer to theglobal memory, where the head address is necessary for the host WS to save data Dsave on thehard disk.
• Transfer of data Dcal to DSP(D).
5. Tdisp : Task in DSP(D) for Preparing Data to be Displayed:• Down-sampling of the resultant six waveform data∆dA (t), ∆dB (t), xA (t), xB (t), the ECG, and the
PCG, in data Dcal at a sampling frequency of
PRF/M1 , where M1 is set at about 10 in the system by considering whether there is suﬃcient resolution.
• Reconstruction of the M-mode image data fromthe absolute magnitude|y(x; t)| = (y(x; t))2 + (y(x; t))2of the analytic signal y(x; t). This M-mode reconstruction procedure is performed for every M2frame, where M2 is set at about 50.
• Packing of the down-sampled waveforms and the
M-mode image data into a structure-type data
Ddisp and its transfer to the global memory, whichis accessible from the host WS via the VME-bus.
• Generation of the interruption to the host WS sothat it will display the data.
C. Elapsed Time for Tasks
For real-time processing, each of the ﬁve tasks TA/D ,Tcal , TD/A , Tsave , and Tdisp in the DSP should be terminated at least within the pulse repetition interval ∆T .
When each data frame is N0 points in length as shownin Fig. 4 and the complex auto-correlation in Section II
B is evaluated in the range ±∆x, the elapsed time required for each task is measured as shown in the left-handside of Table I. In these estimates, four actual DSP chips,
TMS320C40 GFL50 (refer to Appendix A for details), areemployed.
When there is only one DSP chip, however, the accumulated elapsed time, Tsngl , required from the beginningof TA/D to the end of Tdisp should be terminated within
the pulse repetition interval ∆T . In this case, by the actual measurement, Tsngl is a function of the ∆x and N0 as
follows:
Tsngl = 3.63 × N0 + 14.4 × ∆x + 129.9 (µs).

(7)

If the PRF is 4.5 kHz or 6 kHz, Tsngl should be shorter
than ∆T = 222 µs or 167 µs, respectively. When ∆x = 3
and N0 = 70 points in length, which corresponds to thedata length L0 of 70 µs ×c0 /2=52.5 mm in the direction

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1235

TABLE I
Elapsed time for each task. N0 and ∆x are the number ofpoints sampled in one frame data and the evaluation range
in the auto-correlation in Section II B, respectively. The
typical elapsed time for each task in the DSP is when thelength T0 of each frame data is 70 µs (N0 =70 points) andthe range ∆x is three times the spatial resolution ∆xS .

water tank that simulates the small vibration of the ventricle wall superimposed on the motion with a large amplitude of ±7.5 mm caused by the heartbeat. Brieﬂy, forlarge amplitude motion caused by the rotation (1 cycle/1s) of the eccentric cam in the water tank [3], the tracking result of the surface of the rubber plate exactly coincided with the M-mode image. For a small vibration witha peak-to-peak amplitude of about 20 µm generated by asmall vibrator (model 4810 Brüel & Kjær, Nærum, Denmark) on the eccentric cam, evaluation using the squared
magnitude of the coherence function showed that a small
velocity signal on a large motion was successfully detectedin the frequency range from 1 Hz to 1 kHz. In this paper, the developed real-time system is applied to the same
experiments.
As in the previous paper [3], the range ∆x is evaluated,and 1 point is employed as its optimum valve, that is,∆x = 1 point is employed. The longitudinal velocity, c0 ,in the rubber is about 1.54 × 103 m/s. The parametersof f0 = ω0 /2π and the pulse repetition interval ∆T are 3
MHz and 222 µs, respectively.
Fig. 5 shows the results that are displayed in real timeon the CRT of the system. Fig. 5(a) shows the M-mode
image for about 3 s; this image is generated from the magnitude of the received analytic signal y(x; t) in the realtime system. The tracking results x
A (t) of point A on thesurface of the rubber and x
B (t) of point B in the rubber are superimposed on the M-mode image by the whiteline. The tracking results xA (t) and x
B (t) of these points
exactly coincide with the M-mode image.
Fig. 5(b) and (c) show the velocity signals v
A (t) andvB (t), that is, the instantaneous movement, ∆dA (t) and∆dB (t), of the two points, respectively. Fig. 5(e) shows
the velocity signal vlaser (t) obtained by laser Doppler velocimetry (Ono Sokki LV1300, Hakusan 1-16-1, Midori-ku,
Yokohama, Japan), the output of which is connected to
the PCG input terminal of the real-time system in Fig. 3.
Their waveforms of vlaser (t) and v
A (t) are similar even indetail.
In the motion with large amplitude in the M-mode image of Fig. 5(a), however, the small components of thevelocity signal vA (t) with high frequency caused by thegenerator cannot be recognized. One of the purposes ofour method and system is to measure small velocity signals
with high frequency components, which should be within
the thickness of the curved line in Fig. 5(a). To evaluate quantitatively the correlation at each frequency f between the estimated signal v
A (t) in Fig. 5(b) and vlaser (t)in Fig. 5(e), the squared magnitude of coherence function |γlaser↔us (f )|2 [3, eq. (24)] between them is evaluatedfor the D/A output signal of v
A (t) and vlaser (t) using a
two-channel FFT analyzer (Ono Sokki CF930). Because|γlaser↔us (f )|2 between these two signals is almost equal
to 1 in the frequency band up to 1 kHz , there is complete correlation between these signals for each frequency
component f .
On the other hand, the phase characteristics of thetransfer function Hlaser→us (f ) [3, eq. (26)] from vlaser (t)Task
TA/D :

Tcal :

TD/A :

Tsave :

Tdisp :

Tsngl :

A/D
handling& data-type
conversion
generation of
the various
waveforms
data-typeconversion
and D/A
handling
preparationof the data
to be savedon the HD
preparationof the data
to bedisplayed
total timeusing single
DSP chip

Actualelapsedtime(µs)

Arranged
DSP

1.88 × N0
+16.0

147.6

DSP(A)

0.64 × N0 +14.4 × ∆x+65.5
0.64 × N0
+20.4

153.6

DSP(B)

65.2

DSP(B)

0.38 × N0
+26.9

53.5

DSP(C)

0.089 × N0
+0.99

7.2

DSP(D)

Tcal +
TD/A + Tsave+ Tdisp of (7)427.1

By single

Elapsedtime (µs)

of depth, the elapsed time for each task is given as shownin the right-hand side of Table I, and the accumulated
elapsed time, Tsngl , of (7) is given byTsngl = 427.1µs > ∆T,(∆x = 3, N0 = 70),(8)which is much longer than the pulse repetition interval,∆T , and real-time processing cannot be realized by employing a single DSP chip.
By making free use of four DSP chips, pipelining and theparallel processing are employed to increase the throughput. The tasks Tcal and TD/A in Fig. 4 are combined
and the resultant four tasks are distributed to DSP(A),DSP(B), DSP(C), and DSP(D) as shown in the extreme
right of Table I and in Fig. 4. In this pipelining, each of theresultant four tasks is completed within the pulse repetition period, ∆T , which realizes the real-time processing,though these tasks cannot be realized in real time with asingle DSP chip.

IV. Measurable Accuracy EvaluatedUsing A Water Tank
As in our previous paper [3], the principle of the proposed method was conﬁrmed by an oﬀ-line system using a1236

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Fig. 6. A standard B-mode longitudinal-axis image showing the crosssectional area around the detected points preset in the IVS of apresumedly healthy 39-year-old male volunteer. Points A and B areon the RV and LV of the IVS, respectively. The ultrasonic beampassing through the two points is almost perpendicular to the IVS
during the measurements.

Fig. 5. The results for the experiments using the water tank [3].
(a): The estimated object motion x
A (t) and x
B (t) shown by whitelines, superimposed on the M-mode image, (b) and (c) the estimated
velocity signals v
A (t) and v
B (t), (d) the trigger signal generated byapplying the low-pass ﬁlter to the signal in (e) (this signal is used
to rearrange the object positions to xA (t0 ) and xB (t0 )), and (e) thevelocity signal vlaser (t) obtained by a laser Doppler velocimeter.

to v
us (t) are described by an almost straight line in the frequency range up to 1 kHz. By approximating it according
to the straight line θ = −2πf π [rad], and from its gradient∂θ , the group delay time τ from the output of the laser∂fDoppler velocimetry to the real-time system is about 2 ms,
most of which is caused, not by the calculation, but by thedelay in the A/D conversion and D/A conversion in thesystem. The squared magnitude of Hlaser→us (f ) is almost
ﬂat in the frequency range. From these experimental results, it is conﬁrmed that the small vibration on the large
motion can be successfully detected by this system in realtime in the frequency range up to 1 kHz.

V. Measurable Lower Limit EvaluatedUsing A Water Tank
In addition to the previously mentioned experiments,
the lower limit of the measurable velocity and the thickness
change is evaluated using a rubber plate ﬁxed in a watertank. The positions xA (t) and xB (t) of point A on therubber surface and point B in the rubber, respectively,

are manually preset. The distance between these points is
3 mm.
The velocity signals v

A (t) and v
B (t) at points A and B
and the change in thickness, ∆hAB (t), between them are
obtained by the system; each of these three signals shouldbe 0 if the signal-to-noise ratio is inﬁnite. From the actual
experiments, the lower limit |vmin | of the velocity measurement is approximately given as 1 mm/s, which is lessthan 1/350 of the upper limit |vmax | = c0 /(4f0 ∆T ) = 348
mm/s of the measurable velocity. Because |vmax | corresponds to the π radian of the phase-shift during the pulse
repetition interval ∆T , error in the phase-shift detectionis less than 0.5 degree (= 1[mm/s] × 180◦ /348[mm/s]).
Similarly, the lower limit |∆hmin | of the measurable
change in thickness between these two points A and B in
the system is approximately given by 1 µm, and suﬃcientaccuracy and precision have been conﬁrmed.

VI. In Vivo Results for IVS
First, the developed system is applied to the detectionof instantaneous movement and change in thickness of the
IVS of a presumedly healthy 39-year-old male volunteer.
Fig. 6 shows the B-mode image, which was obtained bystandard ultrasonic diagnostic equipment. Points A and B
are set on the surface of the right ventricular (RV) sideand the LV side of the IVS, respectively. The direction of
the ultrasonic beam passing through points A and B isselected so that the beam is almost perpendicular to the
IVS, as shown in Fig. 6.
Fig. 7(d) and (e) show the ECG and the PCG, respectively. The estimates of the tracking results x
A (t) and

kanai et al.: myocardium motion and arterial wall thickening

1237

Fig. 8. A standard B-mode image showing the cross-sectional areaaround the detected points preset in the left common carotid arteryof the same volunteer as in Fig. 6 and 7.

Fig. 7. In vivo experimental results for points A and B on the RV
and LV of the IVS, respectively, in Fig. 6. (a) The tracking resultsxA (t) and x
B (t) of points A and B, which are superimposed on the
M-mode image; (b) and (c) the estimates of the vibration velocity
signals v

A (t) and v
B (t) of points A and B; (d) the ECG and PCG;
end (e) the change in thickness, ∆hAB (t), of the IVS.

\x
B (t) of points A and B are superimposed on the M-mode
image in Fig. 7(a). Figures 7(b) and (c) show the estimatesof the velocity signals v

A (t) and v
B (t) of the tracked pointsx
A (t) and x
B (t), respectively. The vertical axis of Fig. 7(b)and that of Fig. 7(c) are inverted so that the negative valueof the velocity, which is shown above the baseline, corresponds to the situation in which the object moves in the
direction of the ultrasonic transducer on the chest wall,
which is more easily understood.

The change in thickness, ∆hAB (t), of the IVS from thethickness at the timing of the R-wave of ECG is shown inFig. 7(e). The waveform of ∆hAB (t) is also reproducible
for a period of three heartbeats. For the systolic phase, the
IVS becomes about 3 mm thicker than that of the diastolic
phase, where the thickness of the IVS is about 12 mm at
the end diastole.

VII. In vivo Results for the Carotid Artery
Let us apply the developed real-time system to the human carotid artery in the same volunteer as in Fig. 6 and7. The ultrasonic frequency is 7 MHz. Fig. 8 shows a standard B-mode image. Points A and B are preset on theanterior wall and the posterior wall of the left common
carotid artery, respectively. The ultrasonic beam passing
through these two points is perpendicular to the wall during the measurements. Fig. 9(b) and (c) show the velocity
signals v

A (t) and v
B (t), respectively. Their maximum velocity is about 2.5 m/s, which is about 1/20 of that forthe case of the IVS in Fig. 7. The change in diameter,∆dAB (t), of the lumen is estimated as shown in Fig. 9(e).
There is suﬃcient reproducibility for v
A (t) and v
B (t) andeven for a change in diameter as small as about 250 µm.
Next, points A and B are set on the intima and adventitia of the anterior wall of the same carotid artery, respectively. Fig. 10(b) and (c) show the velocity signals, v
A (t)and v
(t),respectively.
Thechangeinthickness,∆hB
AB (t),of the anterior wall is estimated as shown in Fig. 10(e). A
minute change in thickness of about 80 µm is measured
with suﬃcient reproducibility. In the waveforms of Fig.
9(b), (c), and (e) and 10(b), (c), and (e), the dicrotic notch
is obviously observed at the radiation timing of the second
heart sound (II).

VIII. Transient Evaluation of Arterial
Response to NTG
As described in Section I, the real-time system to measure the change in thickness of the arterial wall will oﬀer
new tools for clinical examinations. In this paper, the developed system is applied to the evaluation of a transient
response of the change in thickness of the carotid artery forabout the ﬁrst 160 s after the sublingual administration of
the spray-type NTG. The subject is a 25-year-old healthy
male volunteer. The change in thickness, ∆hAB (t), of the1238

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Fig. 9. In vivo experimental results of the vibration at points A and
B in Fig. 8 of the left common carotid artery. (a) the tracking resultsxA (t) and x
B (t) of points A and B, which are superimposed on the
M-mode image; (b) and (c) the estimates of the vibration velocity
signals v

A (t) and v
B (t) of points A and B; (d) the ECG and PCG;
and (e) the change in diameter, ∆hAB (t), of the lumen of the artery.

\posterior wall of the common carotid artery and the ECG
are continuously measured by the developed real-time system. The blood pressure, p(t), is also continuously andnoninvasively measured at the radial artery using a bloodpressure manometer (Japan Colin, Jentow-7700, Komaki,
Aichi, Japan).
Fig. 11 shows the transient response to the sublingual
administration of NTG. For each heartbeat, the maximumof the change in thickness, ∆hAB (t), is detected and isshown in Fig. 11(d). From about 20 s after the administration of NTG, the pulse rate gradually increases, the maximum blood pressure gradually decreases, and the maximum change in wall thickness increases at the same time.
Thus, the arterial wall becomes compliant during this theperiod.
On the other hand, the maximum change in wall thickness varies widely, especially from about 20 s after the
NTG administration [see the ﬂuctuations in the trend of
the change in thickness of Fig. 11(d)]. As shown in Fig.
12, however, there is a correlation between the maximum
change in wall thickness of Fig. 11(d) and the pulse pressure of Fig. 11(c), which is the diﬀerence between the max-

Fig. 10. In vivo experimental results of the vibration at point A on
the adventitia side, and point B on the intima side of the anteriorwall of the same carotid artery as in Fig. 8 and 9. (a) the tracking
results x
A (t) and x
B (t) of points A and B, which are superimposedon the M-mode image; (b) and (c) the estimates of the vibration
velocity signals v
A (t) and v
B (t) of points A and B; (d) the ECG and
PCG; and (e) the change in thickness, ∆hAB (t), of the anterior wallof the artery.

\imal blood pressure and the diastolic pressure. Thus, thescattering in the maximum change in wall thickness of Fig.
11(d) originates in the scattering in the pulse pressure of
Fig. 11(c). From this preliminary clinical study, the response of the arterial wall to NTG is evaluated directlyby the change in wall thickness for the ﬁrst time. In thismeasurement, the real-time system is indispensable.

IX. Conclusions
In this paper we have demonstrated a novel real-timesystem for simultaneous measurement of velocity signals
at two points preset on an ultrasonic beam by tracking
the large movement of the object during the cardiac cycle.
From the resultant velocity signals, the local change inthickness of the wall of the heart or the artery was also
evaluated in real time. From the experiments using thewater tanks and in vivo experiments, the accuracy andthe performance of the system were conﬁrmed.
The velocity signal measurement by the proposedkanai et al.: myocardium motion and arterial wall thickening

Fig. 11. The transient response of a 25-year-old healthy male subject
to the administration of NTG. (a) The pulse rate detected from theinterval of the R-waves in the ECG, (b) the blood pressure continuously measured at the radial artery by the manometer, (c) the pulsepressure, and (d) the maximum value of the change in thickness,∆hAB (t), of the common carotid artery detected for each heartbeat.

1239

method has the following advantages compared with conventional methods. The measurable frequency band is fromdc to several hundred Hz as evaluated in Section IV; withstandard ultrasonic Doppler equipment and in all of themethods reported in the literature, the measured velocity
and/or the movement have been displayed only in the time
domain. For them, the eﬀective frequency band is less than
20 Hz, and the frequency components higher than 20 Hz
have not been considered at all. However, the dominantcomponent of the change in thickness is in this high frequency band [1]. Thus, for accurate detection of the change
in thickness of the myocardium as shown in Fig. 7, it is essential to measure such frequency components higher than
20 Hz; our method is the ﬁrst to achieve this in real time.
Because the preliminary studies in this paper were performed in healthy subjects with clear echocardiograms,
much work must be done to ﬁnd out how the method canbe applied in a wider range of subjects and to see whether
it can contribute to assessment of diseases and recovery.
Further investigation of this real-time system and its clinical application to the noninvasive local diagnosis of cardiovascular disease, including that in elderly subjects, andcomparison of its ﬁndings with pathological ﬁndings arebeing conducted.

Acknowledgments
The authors are grateful to Prof. Emeritus Noriyoshi
Chubachi and Prof. Emeritus Motonao Tanaka of Tohoku
University; Prof. Floyd Dunn of the Bioacoustics ResearchLaboratory, the University of Illinois; and Prof. Kunio Shirato, and Dr. Yasuhiko Munakata of Tohoku University
School of Medicine for discussion. The authors also acknowledge the contributions of Dr. Masahiko Takano in
our laboratory.

Appendix A: DSP Chips Employed

Fig. 12. The distribution of the maximum change in wall thickness
in Fig. 11(d) versus the pulse pressure in Fig. 11(c).

The DSP chips employed in this paper are four
32-bit ﬂoating-point digital signal processors, TMS320
C40GFL50. Each is in a 325-pin ceramic pin grid array(CPGA) package and is optimized for parallel processing by combining a high performance central processing
unit (CPU) and a direct-memory-access (DMA) controller
with six high speed CP that provide rapid processor-toprocessor communication. The instruction cycle time is 40
ns even for ﬂoating-point multiplication. By transfer of thedata via one of the six CP, eﬀective multiprocessing andI/O-intensive application are realized. By transferring theresultant structure-type data of a task to the CP in theupper stream DSP and by accessing the data in the downstream DSP, the pipelining among the DSP is synchronized. The CPU delivers up to 30 MIPS/60 MFLOPS witha maximum I/O bandwidth of 384 Mbytes/s. The parallel
run-time library is available in C language programming.
Thus, the parallel processor system with pipelining allows

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us to realize the measurement of instantaneous movementof the two objects preset in the heart/arterial walls andreal-time evaluation of the change in thickness of thesewalls by tracking their instantaneous displacement accurately.

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kanai et al.: myocardium motion and arterial wall thickening

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Hiroshi Kanai (A’88–M’91)was born in
Matsumoto, Japan, on November 29, 1958. Hereceived a B.E. degree from Tohoku University, Sendai, Japan, in 1981 and the M.E. and
the Ph. D. degrees, also from Tohoku University, in 1983 and in 1986, both in electricalengineering.
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. Since 1992, he has been an associate
professor in the Department of Electrical Engineering, Faculty ofEngineering, Tohoku University. His present interest is in ultrasonicmeasurement 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 Engineeringof Japan, the Japan Society of Mechanical Engineers, the Japan Society of Ultrasonics in Medicine, Japan Society of Medical Electronics
and Biological Engineering, the Institute of Electrical Engineers ofJapan, the Japanese Circulation Society, and the Japanese College
of Cardiology.

Jianping Zhang was born in Shanghai,
China on July 7, 1962. He received his B.S.
degree from Shanghai University of Scienceand Technology (currently Shanghai University), Shanghai, China, in 1984, and M.A.
degreee from Commerce Graduate School ofCommerce, Waseda University, Tokyo, Japan,
in 1992.
From 1992 to 1998, he was with System
Design Service Corporation as a software engineer. He has been engaged in developing digital signal processing systems in various ﬁelds,such as active noise control, robust adaptive beam forming, andtelecommunications. Almost every system he has developed is a realtime system, and he is experienced in the analysis and design oftime-critical systems using state-of-the-art multiple DSP tasking.

Yoshiro Koiwa was born in Sendai, Japan,
in 1944. He graduated from Tohoku University, Sendai, Japan, in 1969. He received his
M.D. degree from Tohoku University in 1977.
He is presently Associate Professor of theFirst Department of Internal Medicine of Tohoku University. His main research interestis cardiovascular disease, especially cardiac
function and heart failure.
Dr. Koiwa is a member of American Federation for Clinical Research, the Japanese Circulation Society, the Japan Society of Ultrasonics in Medicine, and the Japan Society of Medical Electronics andBiological Engineering.