Abstract-The heart is a mechanical pump that is electrically driven. We have previously shown that the contractility of the cardiac muscle can reliably be used in order to assess the extent of ischemia using myocardial elastography. Myocardial elastography estimates displacement and strain during the natural contraction of the myocardium using signal processing techniques on echocardiograms in order to assess the change in mechanical properties as a result of disease. In this paper, we showed that elastographic techniques can be used to estimate and image both the mechanics and electromechanics of normal and pathological hearts in vivo. In order to image the mechanics throughout the entire cardiac cycle, the minimum frame rate was determined to be on the order of 150 fps in a long-axis view and 300 fps in a short-axis view. The incremental and cumulative displacement and strains were measured and imaged for the characterization of normal function and differentiation from infracted myocardium. In order to image the electromechanical function, the incremental displacement was imaged in consecutive cardiac cycles during end-systole in both dogs and humans. The contraction wave velocity in normal dogs was found to be twice higher than in normal humans and twice lower than in ischemic dogs. In conclusion, we have demonstrated that elastographic techniques can be used to detect and quantify the mechanics and electromechanics of the myocardium in vivo. Ongoing investigations entail assessment of myocardial elastography in characterizing and quantifying ischemia and infarction in vivo

Elisa E Konofagou

Jianwen Luo

Mathieu Pernot

Simon Fung-Kee-Fung

CiteSeerX

 
 
 
 
  
Abstract—The heart is a mechanical pump that is electrically 
driven. We have previously shown that the contractility of the 
cardiac muscle can reliably be used in order to assess the extent 
of ischemia using myocardial elastography. Myocardial 
elastography estimates displacement and strain during the 
natural contraction of the myocardium using signal processing 
techniques on echocardiograms  in order to assess the change in 
mechanical properties as a result of disease. In this paper, we 
showed that elastographic techniques can be used to estimate 
and image both the mechanics and electromechanics of normal 
and pathological hearts in vivo. In order to image the mechanics 
throughout the entire cardiac cycle, the minimum frame rate 
was determined to be on the order of 150 fps in a long-axis view 
and 300 fps in a short-axis view. The incremental and cumulative 
displacement and strains were measured and imaged for the 
characterization of normal function and differentiation from 
infracted myocardium. In order to image the electromechanical 
function, the incremental displacement was imaged in 
consecutive cardiac cycles during end-systole in both dogs and 
humans. The contraction wave velocity in normal dogs was 
found to be twice higher than in normal humans and twice lower 
than in ischemic dogs. In conclusion, we have demonstrated that 
elastographic techniques can be used to detect and quantify the 
mechanics and electromechanics of the myocardium in vivo. 
Ongoing investigations entail assessment of myocardial 
elastography in characterizing and quantifying ischemia and 
infarction in vivo. 
I. INTRODUCTION 
ardiovascular diseases rank as America’s No. 1 killer, 
claiming the lives of over 41.4% of more than 2.4 million 
Americans who die each year. Cancer follows, killing 23%. 
All other causes of death account for about 35.3%. In 
addition, 61.8 million Americans have some form of 
cardiovascular disease. This includes diseases of the heart, 
stroke, high blood pressure, congestive heart failure, 
congenital heart defects, hardening of the arteries and other 
diseases of the circulatory system. Early detection of 
abnormality is thus the key in treating cardiovascular disease 
early and reducing the enormous death toll. The diagnosis of 
myocardial ischemia is often difficult to establish in its early 
stages when treatment is most effective. Patients suffering 
from myocardial ischemia may present to an emergency room 
or acute care facility with typical cardiac symptoms such as 
chest pain, described as tightness, pressure, or squeezing, but 
 
Manuscript received April  24, 2006. This work was supported in part by 
the American Heart Association and the W.H Coulter Foundation. All 
authors are with the department of biomedical engineering of Columbia 
University, New York, NY 10027, USA (e-mail: ek2191@columbia.edu,. 
M.Pernot is currently with  Laboratoire Ondes et Acoustique, ESPCI, Paris, 
France. 
 
some patients may have other symptoms such as arm or chin 
pain, nausea, sweating, or abdominal pain.  Standard 
techniques such as the electrocardiogram (ECG) often provide 
inconclusive findings regarding ischemia, and sometimes may 
even be unable to identify situations, in which ischemia has 
progressed to cell damage and myocardial infarction (MI). 
Elasticity imaging is a relatively new field that has dealt 
with the estimation and imaging of mechanically-related 
responses and properties for detection of pathological 
diseases, most notably cancer [1-3] and has thus emerged as 
an important field complementary to ultrasonic imaging. Only 
recently has the focus of the elasticity imaging field been 
steered towards cardiac applications [4-5]. This technique 
encompasses imaging of any kind of mechanical parameter 
that would highlight the mechanical property of the 
myocardium, such as displacement, strain, strain rate, 
velocity, shear strain, rotation angle, etc. In the same fashion 
as in standard elastography, the parameter that can relate 
directly to the underlying stiffness, and thereby to onset of 
disease, is the strain and the image that depicts the strain is 
called elastogram. Therefore, since assessment of the 
myocardial mechanical parameters has proven to be a crucial 
step in the detection of cardiac abnormalities, Myocardial 
Elastography can help make a significant impact in this field 
by measuring the mechanical response of the cardiac muscle 
at the various phases of the cardiac cycle [4]. Myocardial 
Elastography benefits from the development of techniques 
that can be used for high precision 2D time-shift based strain 
estimation techniques [6] and high frame rate currently 
available in ultrasound scanners [5] to obtain a detailed map 
of the transmural strain in normal [4-5] and pathological cases 
[7] over different phases and over several cardiac cycles. 
More recently, our group has shown that, by combining the 
two components of the strain tensors calculated from the 
two-dimensional displacements, the radial / circumferential / 
principal strains can be calculated as angle-independent 
measurements of the myocardial function [8].  
In this paper, we identify the parameters under which 
myocardial elastography can be used in vivo to highlight the 
mechanics and electromechanics of the heart [9], in the 
absence or presence of disease. 
II. METHODS AND RESULTS 
II.1. MECHANICS 
II.1.1 Frame rate and correlation 
In order to determine the frame rate that ensures the highest 
correlation and thereby most reliable strain estimates, the 
relationship between frame rate and correlation was 
Imaging the mechanics and electromechanics of the heart 
Elisa E. Konofagou, Associate Member, IEEE, Simon Fung-kee-Fung,  
Jianwen Luo, Member, IEEE, and Mathieu Pernot 
C 
Proceedings of the 28th IEEE
EMBS Annual International Conference
New York City, USA, Aug 30-Sept 3, 2006
1-4244-0033-3/06/$20.00 ©2006 IEEE. 6648
 
 
 
 
determined. The posterior wall of a normal human subject 
were imaged in short-axis and long-axis views, respectively, 
using a Vingmed Vivid FiVe (GE Vingmed, Horten, Norway) 
with a 2.5 MHz phased array. IQ (in-phase quadrature) data 
was acquired and transferred to a workstation for off-line 
analysis and converted back to RF. The sampling frequency 
was equal to 20 MHz and the depths and widths scanned 
ranged between 100-150 mm. In order to obtain axial (i.e., 
along the ultrasound beam) displacement and axial strain 
estimates, the cross-correlation method of consecutive RF 
segments was applied using a window equal to 2 mm and a 
window overlap of 80% to ensure high elastographic 
resolution [6]. The original frame rate was equal to 300 Hz 
and was progressively decimated to approximately 40 Hz in 
order to establish the relationship between correlation 
coefficients and frame rate (in frames/s or fps). The results 
from both long-axis and short-axis views are shown in Fig. 1.  
 
From Fig.1, there are several important observations that 
can be made. The correlation coefficient steadily increases 
with frame rate and slowly starts to reach a plateau beyond a 
certain frame rate. In the case of the long-axis view, that frame 
rate value is approximately 150 fps while in the case of the 
short-axis the value is twice higher, i.e., 300 fps. Also, durng 
systole, the correlation coefficient is higher than during 
diastole. This is due to the fast filling phase that introduces 
high decorrelation as the strain rates are highest during that 
phase. Finally, 2D tracking, i.e., 1D kernel search in a 2D 
region, yields slightly higher correlations than 1D tracking. 
The crucial effect that frame rate can have on the strain 
imaged is shown in Fig. 2 in the most accentutated effect, i.e., 
during systole. 
 
II.1.2 Incremental displacements and strains 
Using the same methods and parameters as in the previous 
section, incremental (i.e., frame-to-frame) strains were 
obtained in the posterior wall at 150 fps in a long-axis view. 
Figure 3 shows the incremental displacement and strains 
obtained during systole and diastole.  
 
II.1.3 Cumulative displacements and strains 
The cumulative (i.e., accumulating estimates over time 
starting at end-diastole) strains were obtained in the posterior 
wall at 300 fps in a short-axis view. The cumulative strains 
were obtained by summing over the incremental 
displacements (to obtain the cumulative displacements) and 
then performing the gradient operation on the cumulative 
displacements. The cumulative strain has been previously 
introduced as a higher quality alternative to incremental strain 
(Konofagou et al. 2003b) without any compromise on 
temporal resolution. Figure 4 shows the M-mode cumulative 
displacements and strains as well as correlation images 
obtained.   
 
 
0 50 100 150 200 250 300 350
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Frame Rate (fps)
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or
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SA: 1-D (Systole)
SA: 1-D (Diastole)
SA: 2-D (Systole)
SA: 2-D (Diastole)
LA: 1-D (Systole)
LA: 1-D (Diastole)
LA: 2-D (Systole)
LA: 2-D (Diastole)
 
Figure 1: Correlation coefficient versus frame rate (fps) at 
different frame rate, from short axis view and long axis 
views, in systolic phase and diastolic phases, repectively. 
The errorbar indicates 0.5 standard deviation. 
-5.44
-3.63
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3.63
5.44
 
-2.00
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-0.67
0.00
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2.00
 
                   (a)                                         (b) 
Figure 2: The importance of frame rate on strain accuracy: 
Compressive (blue) strains overlayed onto the long-axis 
echo view during diastole at a) 50 fps and b) 136 fps. Note 
how the quality of the image significantly increases at the 
higher frame rates. 
-0.30
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                  (a)                                            (b) 
-2.00
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                        (c)                                          (d) 
Figure 3: Incremental displacements in a long-axis views 
during a) systole and b) diastole and corresponding strains 
during c) systole and d) diastole. Blue and red 
displacements denote motion away from and towards the 
transducer (top on all images),  respectively.. Blue and red 
strains denote thickening and thinning,  respectively. 
6649
 
 
 
 
 
II.1.4 Imaging for infarct detection 
2D echocardiographic RF data using a portable, laptop 
scanner (Terason 2000, Teratech, Inc) and a 3 MHz phased 
array were acquired continuously during a 2-min induction of 
acute myocardial infarction through ligation of the 
left-ascending, distal (LAD) coronary artery of an 
open-chested dog (respiration was also interrupted). 
Sequences of ultrasound RF images were acquired at 54 fps 
(128 RF lines, sampling frequency: 10 MHz).  Axial 
displacements are estimated from two consecutive RF frames, 
using a 1D cross-correlation algorithm (Size of the correlation 
windows: 6 mm; overlapping: 90%). In this algorithm, 
time-shifts between two consecutive backscattered signals are 
determined by the cross-correlation of small sliding windows 
over the entire 2D ultrasound image. Finally, the strain 
distribution is computed by differentiating the displacement 
map along the axial direction. For the numerical 
differentiation a least-squares regression method was used. 
The results show how elastograms and elastocardiograms (i.e., 
the overlayed echocardiogram and elastogram image, Fig.5) 
can be used to localize the region of the muscle undergoing 
ischemia (denoted by low strain (close to zero) between 3 
o’clock and 6 o’clock, which coincides with the region of the 
LAD ligation. 
 
II.2. ELECTROMECHANICS 
 
II.2.1 Canine example in vivo 
The experiments were performed in an anesthetized 
open-chested dog. The left descending artery (LAD) was 
ligated during surgery in order to induce ischemia. The 
ultrasound images were acquired using a commercial scanner 
(Terason 2000, Teratech, Inc.) with RF-data storage 
capability. The transducer was placed on the anterior wall of 
the left ventricle of the heart, to obtain a short axis view. 
Approximately every two minutes, a sequence of three cardiac 
cycles was acquired during the experiment, with a frame rate 
of 56 fps.  The motion detection technique was based on 
detecting the small displacements of the myocardium that 
occurs between two consecutive frames. Only axial 
displacements (in the direction of the transducer) were 
computed. The time-shifts in the backscatterered signals are 
determined between the two consecutive frames through 
cross-correlation of small sliding windows (correlation 
windows of 3 mm, overlapping 90%) over the entire 
ultrasound image. This technique allows the detection of very 
small displacements on the order of 50 µm. 
  
a)  b)  
c)  d)  
Figure 6: Canine example in vivo - Sequence showing the 
propagation of the contraction at a) 0 ms, b) 18 ms, c) 36 
ms and d) 53 ms after end-systole. The displacements (in 
color) are overlaid onto the grayscale image. Blue and red 
displacements are towards and away from the transducer 
(located at top of the image), respectively. The frame rate 
is 56 images/s. The ischemic zone is located in the central 
bottom side of each image 
  
 
 
-0.25
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0
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                  (a)                                            (b) 
 
 
 
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40
60
 
 
0
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1
   
                         (c)                                         (d) 
Figure 4: M-mode images - Variation over an entire 
cardiac cycle in a normal posterior wall: a) Incremental 
and b) cumulative displacements, c) cumulative strains 
and d) corresponding correlation coefficients. 
  
               
 
 
 
 
                (a)                                            (b) 
               
                         (c)                                         (d) 
Figure 5:  Canine ventricle in vivo: Displacement images 
(a-b) at end-diastole and corresponding elastocardiograms 
(c-d) at the beginning of and after 90 sec of LAD ligation, 
respectively. The strain ranges from +1% (compressive 
strain) to -1% (tensile strain). The ischemic region is shown 
increasing in size between 4 and 7 o’clock, close to the 
location of the LAD ligation. 
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6650
 
 
 
 
On the cine-loop of the displacements, a strong contraction 
wave is clearly detected (Fig.1). The negative (blue) 
displacement indicating contraction of the myocardium 
propagates in the posterior wall from the septum (left side of 
the images) to the lateral wall (right side). The speed of the 
propagation was measured by tracking the contraction 
wavefront in the sequence. An average speed of 1.2m/s was 
found for the normal part of the heart, and 0.7 m/s for the 
ischemic region. 
 
 
II.2.2 Human example in vivo 
A sequence of approximately four cardiac cycles was acquired 
at a very high frame rate of 170 fps using a Vingmed System 
Five for RF image acquisition from a young, normal human 
subject.  In order to reach such a high frame rate, only a small 
part of the heart (the left ventricle) was imaged (80 x 40 mm).  
The axial displacements were processed for each frame.  On 
the displacement cine-loop, two electromechanical waves 
were clearly seen, propagating in the posterior wall of the left 
ventricular (not shown).  Figure 7 shows consecutive 
displacement maps superimposed on the grayscale images in 
order to illustrate the propagation of the mechanical wave at 
the end-systolic phase.  The speed was found to be 0.65 m/s in 
the posterior wall.  The location of the electromechanical 
wavefront is indicated by arrow W in Figs. 7(a)-(d).  
III. CONCLUSION AND DISCUSSION 
In this paper, we showed that elastographic techniques can 
be used to estimate and image both the mechanics and 
electromechanics of normal and pathological hearts in vivo. In 
order to image the mechanics throughout the entire cardiac 
cycle, the minimum frame rate to be used was on the order of 
150 fps in a long-axis view and 300 fps in a short-axis view. 
The incremental and cumulative displacement and strains 
were measured and imaged for the characterization of normal 
function and differentiation from infracted myocardium. In 
order to image the electromechanical function, the 
incremental displacement was imaged in consecutive cardiac 
cycles during end-systole in both dogs and humans. The 
contraction wave velocity in normal dogs was found to be 
twice higher than in normal humans and twice lower than in 
ischemic dogs. In conclusion, we have demonstrated that 
elastographic techniques can be used to detect and quantify 
the mechanics and electromechanics of the myocardium in 
vivo. Ongoing investigations entail assessment of myocardial 
elastography in characterizing and quantifying ischemia and 
infarction in vivo. 
IV.  ACKNOWLEDGMENT 
The authors wish to thank Kana Fujikura, M. D., for 
performing all the echocardiography scans used for this study.  
V. REFERENCES 
[1] K. J. Parker, S. R. Huang, R. A. Musulin and R. M. Lerner, Tissue 
response to mechanical vibrations for Sonoelasticity Imaging, 
Ultrasound Med. Biol, 16, 241-246, 1990. 
[2] J. Ophir, I. Cespedes, H. Ponnekanti, Y. Yazdi, and X. Li, 
"Elastography:  A quantitative method for imaging the elasticity of 
biological tissues," Ultrason. Imaging, vol. 13, pp. 111-134, 1991. 
[3] M.O’Donnell, ,A. R.Skovoroda,  B. M. Shapo, and S. Y.Emelianov, 
Internal displacement and strain imaging using ultrasonic speckle 
tracking, IEEE Trans. Ultrason. Ferroel. Freq. Cont, 41, 314-325, 
1994. 
[4] E.E Konofagou., J. D’hooge and J.Ophir, Cardiac Elastography – A 
feasibility study, IEEE Symposium in Ultrasonics, Ferroelectrics and 
Frequency Control, San Juan, Puerto Rico, 1273-1276, 2000.  
[5] E. E. Konofagou, J. D'hooge, and J. Ophir, "Myocardial elastography - 
A feasibility study in vivo," Ultrasound Med. Biol., vol. 28, pp. 
475-482, 2002. 
[6] E.E. Konofagou and J Ophir,. A New Elastographic Method for 
Estimation and Imaging of Lateral Strains, Corrected Axial Strains and 
Poison's Ratios in Tissues, Ultrasound in Medicine and Biology 24(8), 
1183-1199, 1998. 
[7] E. E. Konofagou, T. Harrigan, and S. Solomon, “Assessment of 
regional myocardial strain using cardiac elastography: Distinguishing 
infarcted from non-infarcted myocardium,” IEEE Ultrasonics Symp. 
Proc., 1589-1592, 2001. 
[8] S. D. Fung-Kee-Fung, W. N. Lee, C. M. Ingrassia, K. D. Costa, and E. 
E. Konofagou, “Angle-independent strain mapping in myocardial 
elastography 2D strain tensor characterization and principal component 
imaging,” IEEE Ultrasonics Symp. Proc., 516-519, 2005. 
[9] M. Pernot and E. E. Konofagou, “Electromechanical imaging of the 
myocardium at normal and pathological states,” IEEE Ultrasonics 
Symp. Proc., 1091-1094, 2005. 
a)  b)  
c)  d)   
Figure 7: Human example in vivo - Sequence showing the 
propagation of the contraction at a) 6 ms, b) 18 ms, c) 30 ms 
and d) 36 ms after end-systole. The frame rate is 170 images/s. 
All the other parameters are the same as in Fig. 6. 
6651


Imaging the Mechanics and Electromechanics of the Heart

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Imaging the Mechanics and Electromechanics of the Heart

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