Abstract— By capturing three-dimensional motions of small

markers on the heart of a small laboratory animal with 1000

fps stereo images, we realized a cardiac motion analysis sys-

tem to quantify the rate of change in the myocardial area of

its heart, which indicates the myocardium’s activity for a

rhythmic expansion/contraction motion in a local area. Using

this cardiac motion capture system, we analyzed the three- dimensional motion distributions in the heart of a rat model

for myocardial infarction, which had heart rate of 4 times/s or

greater. In the analysis, the characteristic cardiac motion in

ischemic heart diseases was spatiotemporally quantified and

it was seen that the infarction area on the heart of the rat

caused by ischemia was spread around its left ventricle.

I. INTRODUCTION

EART disease is the leading cause of death in Europe and

the U.S., killing six hundred thousand persons or more in

the U.S. in 2006 [1]. In response to these statistics, many

types of new drugs for heart disease have been vigorously

developed, such as � blockers [2] to decrease cardiac work-

load and control heart rate and HMG CoA reductase inhibi-

tors [3] to lower blood cholesterol levels. In the development

of such new drugs, animal testing is inevitable for ensuring

drug efficacy and safety quantitatively as a final screening

test before human tests and clinical trials. In particularly, in

the case of drugs for heart disease, in vivo quantification of

the cardiac motions in laboratory animals leads to a more

objective drug efficacy evaluation, because the degree of

heart disease is directly reflected in cardiac motion.

For the early diagnosis and treatment of human heart dis-

ease, many types of noninvasive monitoring devices and

methods for determining cardiac function have been intro-

duced at numerous clinical sites, including electrocardio-

graphy [4], echocardiography [5], coronary catheterization

[6], and radioisotope scintigraphy [7]. These noninvasive

monitoring methods have also been applied to cardiac func-

tion analysis for small animal models of heart disease and

many studies have already been conducted in order to quan-

tify the area of myocardial infarction in laboratory rats by

I. Ishii, T. Okuda, Y. Nie, and T. Takaki are with Hiroshima University,

Hiroshima 739-8527, Japan (corresponding author: Idaku Ishii; phone:

+81-82-424-7692; e-mail: iishii@robotics.hiroshima-u.ac.jp). K. Orito is with Azabu University, Kanagawa 229-8501, Japan

A. Tanaka and H. Matsuda are with Tokyo University of Agriculture and

Technology, Tokyo 183-0057, Japan.

using echocardiogram [8] and SPECT imaging [9]. However,

most of these conventional monitoring technologies are not

always suitable to capture the cardiac motion distribution by

assessing the local myocardial motions at multiple points on a

heart, because there are few surface patterns on a heart,

making it difficult to extract feature points accurately; further,

it is difficult to attach a large number of markers to a heart

without invasion. Compared to cardiac function monitoring

in humans, noninvasiveness is not as severe a requirement in

small laboratory animals. Often, in animal testing for heart

disease, the chests of small animals are opened to generate

heart disease artificially. Therefore, there is little problem

with assessing their cardiac motions by opening their chests

and observing their hearts directly using video cameras.

In this study, we develop a cardiac motion capture system

for the open chest of a small laboratory animal. This system

can capture the three-dimensional (3D) motions of small

markers on the heart using high-frame-rate stereo video

cameras. As a quantification index for ischemic heart disease,

the rate of change in myocardial area (RCMA) is introduced

on the basis of the 3D cardiac motions at multiple points on a

heart. To verify the performance of our cardiac motion cap-

ture system, the cardiac motion of a rat model for myocardial

infarction is actually quantified as the myocardium’s activity

and the time-varying infarction distribution on its heart is

visualized using an RCMA map.

II. CARDIAC MOTION CAPTURE SYSTEM

A. System Concept

To quantify the spatial distribution of the local myocardial

motions at multiple points on the heart of an open-chest small

laboratory animal, a cardiac motion capture system is de-

veloped on the basis of the following concepts.

1) Video capturing at a high frame rate

Generally, the heart rate of a mature laboratory rat is 4~5

beats per second, which is 4 times that of a human. In the case

of standard video capturing at 30 fps for such cardiac motion,

only 6 points or slightly more are sampled per beat cycle,

making it difficult to accurately analyze the waveforms for

cardiac motion. Therefore, we capture the cardiac motion in a

small laboratory animal by using stereo video cameras with a

frame rate of 1000 fps, which is the same level as the sam-

pling rate for an electrocardiogram signal.

2) Attachment of small markers on a heart

Since the surface of a heart has few characteristic patterns,

Cardiac Motion Analysis of a Rat Model for Myocardial Infarction

Using High-Frame-Rate Stereo Images

Idaku Ishii, Toshikazu Okuda, Yuman Nie, Takeshi Takaki

Kensuke Orito, Akane Tanaka, and Hiroshi Matsuda

H

6th annual IEEE Conference on Automation Science andEngineeringMarriott Eaton Centre HotelToronto, Ontario, Canada, August 21-24, 2010

TuA1.3

978-1-4244-5448-8/10/$26.00 ©2010 IEEE 780

the positions of local points on the surface cannot always be

identified accurately in the captured stereo videos using im-

age processing techniques such as feature point tracking.

Moreover, a heart is not suitable for image measurement with

active pattern projection from a projector, because of the

glossy mucus on the heart surface. In many cases of cardiac

function analysis in laboratory animals, there is no problem

with attaching markers to a heart directly, unless the markers

affect the cardiac motion. In order to clearly ascertain the

local points on a heart, we attach small, lightweight markers

to its surface, which have a color that is distinctly different

from that of the heart. Therefore, the 3D motions of the

markers can be accurately captured using the stereo video

images.

3) Area calculation for triangular regions

The 3D positions of the markers attached to a heart change

not only with the beating of the heart but also with body

movement when breathing; the breathing frequency of a la-

boratory rat is 1~2 times per second in a normal state. To

remove such motion artifacts of body movement, we intro-

duce the areas for triangular regions surrounded by neigh-

boring markers. These triangular areas are calculated by using

the 3D positions of the markers and are independent of the

normal vectors on the surface. As a result, we can quantify the

local myocardial expansion/contraction motions at multiple

points on the surface of a heart as its cardiac motions.

B. Configuration

In our cardiac motion capture system, the 3D positions of

small markers attached to the surface of the heart of an

open-chest laboratory animal are captured by using two

high-speed video cameras, as shown in Fig. 1(a).

As the high-speed video camera, FASTCAM MH4-10K of

Photron Limited was used, which simultaneously captures

8-bit color 512 × 512 pixel images at 1000 fps from two

camera heads. The locations of the two camera heads and the

measuring area for the heart of a small laboratory animal are

illustrated in Fig. 1(b). The two camera heads use the same

focal distance lens. The angles from their optical axes to the

vertical direction are 8° and -8°, respectively, and the distance

between the optical centers of their lenses is set to 118 mm.

The origin of the ��� coordinate system in 3D space is 334

mm below the midpoint between the optical centers. The

�-axis is vertical, the �-axis is parallel to the line determined

by the two optical centers, and the �-axis is perpendicular to

both the �-axis and the �-axis. In the experiment, the body of

a laboratory animal is set along the �-axis with its heart near

the origin. The measurement area in the �� space is 31 mm ×

31 mm at � = 0, which is close to the heart. The spatial res-

olutions at the origin are 0.061 mm in all the directions.

Fig. 2(a) shows blue-painted styrene foam spheres with

diameters of 0.50~0.75 mm, the color of which is obviously

different from that of a heart. The markers are attached to a

heart of a small laboratory animal, as shown in Fig. 2(b). On

the sticky surface covered with mucus, the markers remain

fixed at the same places on a heart without slipping even

when the heart is-beating, because the markers are very light.

In this study, we obtained the 3D positions of the markers

by executing the following image processing: 1) hue-based

color extraction to identify marker regions in the images, 2)

labeling to obtain 2D positions of the markers in the images,

3) triangulation to obtain the 3D positions of the markers on

the basis of the parallax between the left and right images.

After calculating these 3D positions, a triangular region is

assigned by selecting three neighboring markers. Let

�(= 1, ⋯ , �) be the number of a triangular region, and let the

3D coordinates of the three markers for the triangular region

� be ���(�), ���(�) , and ���(�) at time � . � denotes the

number of triangular regions to be assigned. The area ��(�) at

time � for triangular region � is calculated to quantify the

local myocardial expansion/contraction motion as

��(�) = 12 ����(�) − ���(�)�����(�) − ���(�)� . (1)

III. QUANTIFICATION INDEX FOR ISCHEMIC HEART DISEASE

In this paper, we introduce a quantification index to indi-

cate how myocardial necrotic regions spatiotemporally transit

on the surface of a heart in the case of ischemic heart disease

such as myocardial infarction. Here, we use the index based

on the abovementioned triangular areas, which can express

local expansion/contraction motion as cardiac motion without

motion artifacts from body movement, because there is no

local motion around a necrotic myocardium.

Fig. 1. Cardiac motion capture system for laboratory animal

illuminator

right high-speed

camera

lefthigh-speed

camera

laboratory animal

heart

334 mm

Z

XY

118 mm

8˚‒8˚

open-chest laboratory animal

heart

(a) overview (b) camera location

Fig. 2. Small markers for capturing cardiac motion

(a) small markers (b) heart with small markers

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[Cardiac motion signal]

Generally, the triangular area ��(�) in Eq. (1) is not uni-

form, because it is difficult to arrange all the markers on a

heart at regular intervals. Therefore, we define the following

normalized area ��(�) as a cardiac motion signal at time � to

indicate myocardial motion at triangular region � on a heart:

��(�) = ��(�)1

� � ��(�)���� !"���

, (� = 1, ⋯ , �). (2)

Here, � = �#$ is assumed as a standard time for normalization.

Divided by the moving average of triangular area ��(�) for

� = �#$ ~ �#$ + �, cardiac motion signal ��(�) is so norma-

lized that the moving average of ��(�) in every triangular

region is set to 1 around the standard time of � = �#$.

[Rate of change in myocardial area (RCMA)]

On the basis of the cardiac motion signal ��(�), RCMA at

time �, '�(�), is defined as a quantification index to indicate

local myocardial expansion/contraction motion in the trian-

gular region � on a heart,

'�(�) = �( �(�) − �) �(�)�̅�(�) , (� = 1, ⋯ , �). (3)

Here, �̅�(�), �( �(�), and �) �(�) are the average, maximum,

and minimum, respectively, of ��(�) for � = � ~ � + �,

�̅�(�) = 1Δ� , ��(-)�-

�!"�

�, (4)

�( �(�) = max23� ~ �!"� ��(-) , (5)

�) �(�) = min23� ~ �!"� ��(-) . (6)

When the local myocardial motion is large, that is, the

difference between the myocardial area in expansion and that

in contraction is large, '�(�) has a positive large value. When

there is no local myocardial motion, such as with necrosis,

'�(�) is approximately zero. Therefore, RCMA can quantify

the local activity of the myocardium to show time-varying

myocardial necrotic regions on a heart spatially in the case of

ischemic heart disease.

IV. EXPERIMENTAL EVALUATION

A. Experimental Settings

To evaluate our cardiac motion capture system, the cardiac

motion of a rat model for myocardial infarction, whose car-

diac function was lowered by ischemia, was spatiotemporally

quantified using RCMA.

In the experiment, we used a rat model for myocardial in-

farction [10], with a silk thread used for the ligation of the left

anterior descending coronary artery, which is often infarcted

in many cases of human myocardial infarction. The labora-

tory rat we used was a 14-month-old SD (Sprague-Dawley)

male rat, whose length and weight were 24 cm (not counting

its tail) and 600 g, respectively. The lengths of the major and

minor axes of its heart were 21 mm and 17 mm, respectively.

To prolong the life of the open-chest rat, the rat was ventilated

with isoflurane anesthesia using a small animal anesthetizer

(MK-V100/R, Muromachi Kikai Co., Ltd.).

Small blue markers were attached to the surface of the

heart as shown in Fig. 3(a), which shows an image captured

by the left-side camera. Seventy-two triangular regions were

used to calculate the cardiac motion signals and RCMAs.

These triangular regions were assigned numbers, as shown in

Fig. 3(b). In Fig. 3(a), the locations of the left ventricle, right

ventricle, and right atrium are indicated, whereas the left

atrium is hidden by the left ventricle in the captured images.

Several triangular regions were sometimes unobservable in

the case of occlusions in the images.

In the experiment, � = 0 min was the ligation time of the

left anterior descending coronary artery, and stereo images in

2.685 s were captured at 1000 fps in ten tests using � = 1, 4, 7,

10, 13, 16, 19, 22, 26, and 30 min. An RCMA map of the

heart was quantified offline by calculating the cardiac motion

signals for the triangular regions on the heart on the basis of

the stereo images. After this, the triangular area ��(�) was

calculated using its 20-ms interval moving average for noise

reduction. For a cardiac motion signal ��(�), the standard

time �#$ was set to � = 1 min, which is the nearest time to the

ligation time, and the interval Δ� used to calculate the average,

maximum, and minimum of ��(�) was set to 2.685 s, ex-

cluding irregular pulses.

B. Captured 3D Cardiac Motions

Fig. 4 shows a polygon display sequence for the 3D shape

of the heart of the rat taken at intervals of 0.085 s, which was

generated by the 3D positions of the markers at � = 1 min.

You can see that our cardiac motion capture system can ob-

serve and visualize the change in the three dimensional shape

of the heart while beating, which cannot be observed in detail

using only the naked eyes.

Fig. 5 shows the 3D position �89:(�) and area �9:(�) of a

triangular region on the right ventricle (� = 47 in Fig. 3(b))

for 2.685 s at � = 1 min. Here, the 3D position �89:(�) was

calculated as the average position of the three neighboring

markers for the triangular region (� = 47). For both the 3D

position and the area, periodical changes at a frequency of

approximately 4 Hz can be observed, corresponding to the

heartbeat of the rat. While the � and � coordinates changed

Fig. 3. Heart of a rat model for myocardial infarction

(b) labeled triangle regions(a) markers

left ventricle

right ventricle

right atrium

ligation point p = 8

p = 47

p = 57

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slightly by body movement from breathing, the triangular

area �9:(�) could be used to extract just the local myocardial

motion during expansion/contraction without motion artifacts

from body movement.

C. Cardiac Motion Signals

Fig. 6 shows the cardiac motion signals �;(�), �9:(�), and

�<:(�) for triangular regions on the left ventricle (� = 8), right

ventricle (� = 47), and right atrium (� = 57) for 2.685 s in the

case of capture at � = 1, 10, and 19 min, respectively. Fig. 7

shows the time-varying transitions of the average �̅�(�) ,

maximum �( �(�), and minimum �) �(�) of the cardiac mo-

tion signals for the triangular regions (� = 8, 47, 57). For all

the cardiac motion signals, periodical changes caused by the

beating of the heart can be observed, although the frequency

decreased slightly over time. After the ligation of the left

Fig. 4. Captured 3D shape of heart of a rat

Fig. 5. 3D position and area for a triangular region on the right ventricle

(� = 47) at � = 1 min.

Z17 mm

XY

17 mm

-17 mm-17 mm

17 mm

-17[mm]

0.085 s

Z17 mm

XY

17 mm

-17 mm-17 mm

17 mm

-17[mm]

0.170 s Z17 mm

XY

17 mm

-17 mm-17 mm

17 mm

-17[mm]

0.255 s

Z17 mm

XY

17 mm

-17 mm-17 mm

17 mm

-17[mm]

0.000 s

(a) � = 1 min

(b) � = 10 min

(c) � = 19 min

Fig. 6. Cardiac motion signals at � = 1 min, 10 min, and 19 min

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anterior descending coronary artery, the amplitude of the

vibration in the cardiac motion signal �;(�) for the left ven-

tricle decreased greatly. At � = 19 min, its maximum �( ;(�)

almost matched its minimum �) ;(�); that is, there was little

local expansion/contraction motion, and the average of the

myocardial area was almost the same as that at � = 1 min. The

amplitudes and waveforms of the vibrations in the cardiac

motion signals for the right ventricle, �9:(�), and right atrium,

�<:(�), were almost unchanged, except for irregular pulses,

which were often observed after � = 19 min, whereas their

averages became slightly lower than 1.

D. RCMA Map for Myocardial Infarction

Finally, an RCMA map for all the triangular regions was

quantified to visualize the spatiotemporal transition of the

infarction on the heart after the ligation of the left anterior

descending coronary artery. Fig. 8 shows the time-varying

transitions of the RCMAs, ';(�), '9:(�), and '<:(�), for the

left ventricle (� = 8), right ventricle (� = 47), and right atrium

(� = 57) at � = 1, 4, 7, 10, 13, 16, 19, 22, 26, and 30 min. Fig.

9 shows a sequence of RCMA maps for all the triangular

regions on the heart. Here, the RCMA maps were created by

mapping RCMA '�(�) on the corresponding triangular region

� of the heart in Fig. 3(b). The white regions in Fig. 9 had

strong local myocardial motion, whereas the black ones were

inactive myocardia. The regions marked with “x” had no

measurements.

(a) left ventricle (� = 8)

(b) right ventricle (� = 47)

(c) right atrium (� = 57)

Fig. 7. Temporal transitions of average, maximum, and minimum for

cardiac motion signals

Fig. 8. Temporal transitions of the RCMAs.

Fig. 9. RCMA maps for rat model of myocardial infarction

t = 30 min

0.0

t = 1 min t = 4 min

t = 7 min t = 10 min

t = 13 min t = 16 min

t = 19 min t = 22 min

t = 26 min t = 30 min

0.5

0.0

0.5

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Among the triangular regions of � = 8, 47, and 57, � = 57

(right atrium) had the largest RCMA (0.50), followed in order

by � = 47 (right ventricle, 0.35) and � = 8 (left ventricle,

0.20) at � = 1 min, just after the ligation. While the RCMAs

around the right ventricle and right atrium gradually became

larger over time, those around the left ventricle gradually

decreased and approached zero at around � = 16 min. Thus,

one can see that inactive myocardial regions on the heart

spread around the left ventricle on the RCMA map over time.

Fig. 10 shows the spatiotemporal transition of the infarc-

tion map =�(�) in which an infarction region is defined as an

inactive myocardial region as follows:

=�(�) = > 1 ('�(�)/'�(�#$) < AB) 0 (otherwise) K , (� = 1, ⋯ , �) (7)

Here, the threshold AB used to determine an infarction was set

to 0.2 in Fig. 10. At � = 1 min, no infarction region was in

existence. The infarction regions gradually spread around the

left ventricle for � = 4~13 min, and the infarction regions for

the entire left ventricle were almost the same after � = 22 min.

This indicates that the myocardia on the left ventricle were

mostly necrotic after � = 22 min.

The time-varying infarction regions on the infarction map

corresponded to the fact that the myocardia around the left

ventricle were necrotic due to the long-term ischemic state by

the ligation of the left anterior descending coronary artery,

which nourishes the left ventricle. Thus, it is obvious that our

cardiac motion capture system can quantify and visualize the

spatiotemporal transition for the infarcted heart of a rat model

of myocardial infarction.

V. CONCLUSION

In this study, we developed a cardiac motion capture sys-

tem for small laboratory animals by using stereo video cam-

eras at 1000 fps. By introducing a quantification index based

on 3D cardiac motions, which indicates the local myocardial

expansion/contraction motion, we succeeded in quantifying

and visualizing the time-varying infarction distribution in a

rat model for myocardial infarction. We next intend to check

the validity of our cardiac motion capture system as an

evaluation system for the efficacy of drugs for heart disease,

and we are preparing for animal tests using various small

animal models for heart disease, such as that for myocardial

infarction.

REFERENCES

[1] M. Heron, D.L. Hoyert, S.L. Murphy, J. Xu, K.D. Kochanek, and B.

Tejada-Vera, “Deaths: final data for 2006,” Natl. Vital Stat. Rep., 57(14), pp.1-134 (2009)

[2] A.M. Pritchett and M.M. Redfield, “Beta-blockers: new standard

therapy for heart failure,” Mayo Clin. Proc., 77(8), pp.839-845 (2002) [3] A. Endo, “The discovery and development of HMG-CoA reductase

inhibitors,” J. Lipid. Res., 33(11), pp.1569-1582 (1992)

[4] G.E. Burch and N.P. DePasquale, A history of electrocardiography, Chicago, Year Book Medical (1964)

[5] W.F. Armstrong and T. Ryan, Feigenbaum's Echocardiography (7th

ed), Lippincott Williams & Wilkins (2010) [6] D.S. Baim, Grossman's Cardiac Catheterization, Angiography, and

Intervention (7th ed), Lippincott Williams & Wilkins (2005)

[7] B.L. Zaret and G.A. Beller, Clinical Nuclear Cardiology: State of the Art and Future Directions: Expert Consult: Online and Print (4th ed),

Mosby (2010)

[8] J.A. Kilvington, H. Coleman, B. Hansen, H. Dierks, and W. Zhang, “Myocardial infarct size estimation by echocardiography in an acute rat

model,” FASEB. J., 21, pp.908-934 (2007)

[9] P.D. Acton, D. Thomas, and R. Zhou, “Quantitative imaging of myo-cardial infarct in rats with high resolution pinhole SPECT,” Int. J.

Cardiovasc. Imag., 22, pp.429-434 (2006)

[10] T.N.P. Johns and B.J. Olson, “Experimental myocardial infarction,” Ann. Surg., 140, pp.675-682 (1954)

Fig. 10. Infarction maps for a rat model of myocardial infarction

t = 1 min t = 4 min

t = 7 min t = 10 min

t = 13 min t = 16 min

t = 19 min t = 22 min

t = 26 min t = 30 min

978-1-4244-5448-8/10/$26.00 ©2010 IEEE 785