Biomed Imaging Interv J 2006; 2(3):e50
© 2006 Biomedical Imaging and
A new approach for volumetric assessment of left ventricular function with MDCT
*, PhD, S Hamada2, MD, PhD,
M Miyamoto3, MSc,
J Masumoto3, PhD,
M Komizu2, PhD,
G Iinuma1, MD, PhD,
N Moriyama1, MD, PhD
1 Research Center for Cancer Prevention and
Screening, Tokyo, Japan
2 Department of Radiology, Osaka University Graduate School of
Medicine, Osaka, Japan
3 Cuscreed Co. Ltd., Tokyo, Japan
Cardiovascular CT is considered the diagnostic standard for
establishing the presence of a functional and dynamic imaging system. It is
difficult, however, to estimate the ventricular motion and volumes that are
processed using hundreds and thousands of CT images, in a few moments.
The main concept and design of our work are two fold � the development of effective
semi-automatic tools for measuring the sequential left ventricular
volumes from the hundreds or thousands of cardiac trans-axial
images, and providing a simple interface with an interactive
diagnostic tool for the volumetry of left ventricle and� valuable
cardiac 4D visulalisation.
We converted ten and more sequential volume data sets of the
heart acquired from retrospective ECG-gating helical scan into 3D images by
volume rendering. These sequential 3D images could be displayed as a movie (4D
cardiac image) file. Furthermore, we developed a method for semi-automatic
calculation of ejection fraction (EF) and cardiac cycle (%)-volume (ml) curve
for estimation of the motion and the volume of the left ventricle. This method
involved the use an interactive selection tool in the region of interest (ROI).
All 3D processing methods, such as, cutting objects, segmentation, and image
fusion were based on mask processing data. We now describe the software
developed for cardiac 4D imaging and the estimation of ventricular volume. � 2006
Biomedical Imaging and Intervention Journal. All rights reserved.
Keywords: ECG-gating, 4D imaging, LV volume, ejection fraction
Multislice computed tomography (MSCT) offers good cardiac
image quality using ECG synchronised technique, producing no motion artefacts
[1�5]. The heart can be visualised by static or dynamic means. Static
visualisation is used to obtain morphological information, while dynamic
imaging permits functional evaluation. Some reports have described the accurate
estimation of ventricular volume and motion with MSCT [6�8]. It is difficult,
however, to estimate the ventricular motion and volumes on the CT apparatus
itself because of the large cardiac volume data required for a high performance
image processing. For reconstructing the time-series images from the ECG
signal, hundreds or thousands of trans-axial images are produced, and the
interactive reading tool for a cardiac CT examination is expected to use these
for efficient diagnosis.
As the development of computer hardware and software has
been incredibly fast and inexpensive, a system of real-time visualisation and
image analysis should provide the user with good quality image and movie
display. First, we developed effective semi-automatic tools for measuring the
sequential left ventricular volumes from the hundreds or thousands of cardiac
trans-axial images. We adopted this technique and made several improvements to
overcome the problem of automatic calculation of the left ventricular volumes
for different motion phases acquired from the retrospective ECG-gating helical
scan. Second, we extended this technique to display 3- and 4D images of the
heart with real-time volume rendering on the personal computer (PC).
By this, we reduced the time and the effort taken for
cardiac function analysis and 4D display. We introduced a design-integrated
system for cardiac data acquisition and various tools for cardiac function
Retrospective gating is needed for helical scanning, and ECG
gating has been used for years in magnetic resonance imaging
(MRI). It consists of contiguous data acquisition with parallel
registration of the patient�s ECG (Figure 1). Subsequent segmentation
of the acquired data enables re-ordering and re-grouping of
certain data in concord with the registered ECG, for clear visualisation
of defined time points in cardiac cycle (Figure 1a). In this
approach, slow table motion during spiral scanning and simultaneous
acquisition of four slices and the digital ECG trace are employed
to perform an over sampling of scan projections (Figure 1b).
The sampling gaps in the raw helical data with ECG-gating were
generated asynchronously between helical pitch (higher helical
pitch) and heart rate (Figure 1c). This retrospective synchronisation
enables the visualisation of the myocardium of the same region
during diastole and systole by using the same data set. The
application of this method in CT opens a multitude of possibilities.
Figure 1 Reconstruction
procedure with retrospective ECG-gating (four slices). (a)
Retrospective ECG-gating is able to overcome the limitation
of prospective ECG-triggering with inconsistent heart phase
scanning when arrhythmia is present. Arbitrary phases of the
heart motion were reconstructed from the continuous raw helical
data; (b) Slow table motion during helical scanning and simultaneous
acquisition of four slices and the ECG trace are employed
to perform an oversampling of scan projections; (c) Higher
helical pitch sets the appropriate sampling gap of the raw
data space due to misalignments between helical pitch and
The advantages of ECG gating over ECG triggering is that the
data acquisition is independent of the patient�s heart rate, and it is possible
to visualise the imaged region during different times in the cardiac cycle.
This permits functional evaluation. The disadvantage is the prolonged data post
processing procedure and the associated higher radiation dose.
MATERIALS AND METHODS
Network System for Cardiac Data Acquisition from Multi-slice
We installed 4D cardiac analysis software on a standard PC
with Pentium 4 3.00 GHz CPU, and 2.00 GB RAM on Microsoft Windows XP and Intel
Core Duo, 2.00 GHz CPU and 2.00 GB RAM on Mac OS X. The processing and the
image rendering tools of the software are based on the open-source libraries
with OsiriX . Cuscreed Co. Ltd. (Tokyo, Japan) did the optional development
for the algorithm of cardiac cycle (%) � LV volume (ml). The software can be
connected to any DICOM 3.0 model database (patient, study, series, image) via
an Ethernet TCP/IP network (100-Mbps Fast Ethernet). The users can transfer the
DICOM images from MSCT (Aquillion VZ: Toshiba, Nasu, Japan) directly to the PC,
with the cardiac analysis software. ECG monitoring systems (Dyna Scope, Model:
DS-2151, Fukuda Denshi, Tokyo, Japan) were implemented on the MSCT. The users
can also export images, ECG-signals, and movies in PC standard format for local
storage, presentation, and print.
Technical Procedure for Cardiac 4D Imaging
ECG leads were placed on both wrists and the left forearm of
the patients to avoid artefacts. Following a scout view for positioning, the
contrast-enhanced CT data were acquired during a single breath-hold. Patients inhaled
3.0 l/min of oxygen prior to the acquisition, while the scan parameters were
established. Fifty seconds after intravehicular injection of the contrast
medium (100 ml of 320 mg I/ml at 1.2 ml/sec: Iohexol 320, Daiichi
Pharmaceutical Co., Ltd., Tokyo, Japan), the scan was started with the
ECG-gating technique. The exact start and end points of the helical scanning
synchronised ECG record were monitored on the multislice CT console. The
parameters used were 0.5 sec per rotation, and the value for 2-mm-detector row
collimation of the helical pitch (length of table translation divided by X-ray
beam width) was 0.2:1. The time of breath hold was about 75 rotations through 12
cm during 37.5 sec. The X-ray tube voltage and current were 140 kV and 160 mA,
respectively. The volume data sets for phases of cardiac motion were prepared
as 10 sets reconstructed for every 1mm interval using 50% overlap
reconstruction from raw-helical CT data. For each patient, 10 sets of volume
data were created by using both half-scan and segment reconstruction based on
the retrospective ECG-gating helical scanning . For the first end-diastolic
phase, the image acquisition window was centred on the peak of the R wave. For
the second data set, the centre was positioned at 10% of the R�R interval, and
for subsequent data sets, the centre of the image acquisition window was moved
toward the end of the cardiac cycle in increments of 10% (Figure 2). The
software can obtain these 10 volume data sets as a DICOM series and can take in
as many as the memory size of the PC hardware enables.
Figure 2 Reconstruction procedure for
4D cardiac imaging using ECG-gating technique. ECG-gating
permits visualisation of multiple time points during the cardiac
cycle out of one helical CT data set. For the first end-diastolic
phase, the image acquisition window was centred on the peak
of the R wave. For the second data set, the centre was positioned
at 10 % of the R–R interval, and for subsequent data
sets, the centre of the image acquisition window was moved
toward the end of the cardiac cycle in increments of 10%.
The groups of slices Z1-10 and Z2-10 or Z1-20 and Z2-20 in
the figure were reconstructed from the same phase of R–R
interval. Each volume set was converted to a 3D image, and
these sequential 3D images were displayed as 4D cardiac images.
IMAGE PROCESSING AND ANALYSIS IN CARDIAC CT EXAMINATION
4D Cardiac Imaging
After loading the 10 sets of volumes for all cardiac
trans-axial slices, the user can easily change the order of the series to make
sequential 4D cardiac image.
To reduce time and effort, the parameters of volume
rendering (transfer function of colour and opacity curve, cutting, panning,
zooming, and others) were automatically synchronised with just one volume
operation. The remaining nine sets of series were processed in sync with a
series of interest. Figure 3 shows the flowchart of 4D cardiac imaging.
Figure 3 Flowchart of cardiac 4D display.
All series produced by the ECG-gating technique were transferred
to the 3D workstation. The 3D-Workstation can load the entire
series and sort it as sequential data. Users can control the
entire series by manipulating just one arbitrary series. The
remaining nine sets of series were processed in sync with
each other by manipulating one series data.
The EF, a parameter of global ventricular function, is
calculated from the volumes at end diastolic EDV and end systolic ESV as:
This is the single most powerful prognostic indicator, and
its value correlates with the risk of morbidity and mortality in different
types and stages of heart disease. The presence of an abnormality in the
regional wall motion suggests ischemic heart disease, the location of the
hypokinesis correlates loosely with the coronary artery that is affected, and
the size of the functional defect suggests the amount of myocardium that is
ischemic or infracted. In our software, semi-automatic EF calculation was
applied with simple segmentation and volume calculation using voxel counting to
avoid the error of segmentation at the level of tricuspid valve.
The procedure to calculate the semi-automated EF is as
1.���� Selection of the arbitrary ROI around the left
ventricular cavity on trans-axial images in end-diastolic phase. (The ROIs were
interpolated between all slices within the selected area). Figure 4 shows the
scene of arbitrary selection of left ventricular region for several slices. Irregular
gaps among the slices were converted to regular intervals by automatic
Figure 4 Segmentation for selection
of the left ventricle. (a) The ROI were manually placed on
the left vetricle with end-diastoric phase. Users can manipulate
the ROI with deformation, panning, and zooming; (b) Selected
ROI on the skipped slice reveals that the slice was interpreted
and cut along the Z axis.
2.���� Copying the ROIs of the end-diastolic phase to all
other phases. Left ventricular cavities with all phases covered by left
ventricular cavity at end-diastolic phase. (Figure 5)
Figure 5 An illustration of the method
involving copying the volume of interest (VOI) from EDV volume
dataset to ESV volume dataset. The ROI on the slice of end-diastolic
phase were copied to the same level of slice for other phases.
3.���� Estimation of threshold Hounsfield Unit (HU) value
for segmentation of left ventricular cavity using histogram analysis applied
Mode method [10,11]. The left ventricular cavity filled with contrast media was
segmented by statistical method (mode value) depending on the HU value
histogram. Threshold HU values were decided as a midpoint value between two
mode values on a bimodal histogram drawing around the ROI of the left
4.���� Automatic drawing of the cardiac cycle (%) � volume
(ml) curve and EF calculation.
RESULTS AND DISCUSSION
The resulting 3D image set consists of 109 slices per
temporal frame and 10 temporal 3D frames per cardiac cycle. The results of the
segmentation of LV volume and cardiac cycle (%) � volume (ml) curve are
displayed in Figure 6. EF can be calculated from the cardiac cycle (%) � volume
(ml) curve. A 4D view of the cardiac motion was reconstructed using the fast
volume rendering technique for each cardiac cycle (Figure 7 and Movie1). Modern
helical CT systems offer a rotation time of 0.4 � 0.5 sec. With this technique,
in combination with ECG-gating, diastolic images almost free of motion
artefacts can be acquired from patients with a moderate heart rate.
Figure 6 Multi-display of the results
of cardiac function analysis. Calculated phase (%)–volume
curve is shown in the figure. The user can easily fix the
segmented area of left ventricle and re-calculate the volumes.
Figure 7 Resultant display
of 4D left ventricular imaging. R–R intervals were divided
into ten phases using retrospective ECG-gating.
One of the most effective techniques for cardiosurgery is
temporal 3D display of prosthetic valve after prosthetic valve replacement
(Figure 8 and Movie 2). The operator could easily check the state of the
closing valve motion in this view. What was once a time-consuming task is
improved by semi-automatic processing of the multi-volume dataset. Most
high-performance 3D workstations offer only a simple measurement tool (e.g., plot
profile, histogram, and filters) applied 2D or one volume dataset. The examples
presented in this article, however, do not represent a completed project. Need
exists for a comprehensive evaluation procedure covering cardiac diseases, such
as, coronary artery disease, myocardial infarction, cardiac anomaly, and others.
Our further research would include the complete development of the software and
the analysis using cardiovascular CT system.
Figure 8 4D view of the prosthetic valve.
The operator can easily check the state of the closing valve
motion following prosthetic valve replacement.
The DICOM-supported software for 4D cardiac imaging and
function analysis with online connection to multislice CT apparatus is useful
to comprehend the left ventricular motion and volumes.
Movie 1 Movie of 4D left
Movie 2 Movie of 4D view
of the prosthetic valve.
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|Received 16 May 2006; received in revised form 1 September 2006, accepted 19 September 2006
Correspondence: Research Center for Cancer Prevention
and Screening, National Cancer Center, 5-1-1 Tsukiji, Chuo-ku,
Tokyo 104-0045, Japan. Tel.: (03) 3542 2511; E-mail: firstname.lastname@example.org
Please cite as: Yamamoto S, Hamada S, Miyamoto
M, Masumoto J, Komizu M, Iinuma G, Moriyama N,
A new approach for volumetric assessment of left ventricular function with MDCT, Biomed Imaging Interv J 2006; 2(3):e50
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