Download Comparison of Left Ventricular Ejection Fraction

Comparison of Left Ventricular
Ejection Fraction assessed with
3D Echocardiography and
Cardiac MRI
E.M. Wintjes
October 2008
BMTE 08.42
ID nr: 0536609
Eindhoven University of Technology
Department of Biomedical Engineering
Division: Biomechanics and Tissue Engineering
Supervisors:
ir. J.W.A. Gutteling (MMC)
dr.ir. P.H.M. Bovendeerd (TU/e)
Prof.dr.ir. F.N. van de Vosse (TU/e)
Prof.dr.ir. P.F.F. Wijn (TU/e, MMC)
i
Abstract
Both 3D echocardiography (3DE) and cardiac magnetic resonance imaging (MRI) can be used to determine the cardiac left ventricular ejection fraction. Ejection fraction is the difference between the end
diastolic volume (EDV) and the end systolic volume (ESV) divide by the EDV. Several studies have
tried to determine the similarity between the ejection fractions (EF) calculated with 3DE and MRI. A
literature review of 14 studies showed no significant difference, but the combination of many different
patients, variation of cardiac pathologies and no paired and individual data introduces a large variation
on the EF data, which makes it impossible to determine a significant difference between 3DE and MRI.
This study, done in the MMC in Veldhoven, tries to determine if a difference exists by using both techniques on the same healthy volunteer and determining the EF using several different dedicated software
packages. A total of 9 3D echo’s and 3 MRI’s was made, the software packages used are CAAS MRV
from Pie Medical, and 4D LV Analysis MR for the MRI data, and Qlab 3DQ Advanced from Philips and
4D LV Analysis from Tomtec for the 3DE data. Each 3DE and MRI was analyzed several times by two
observers. This resulted in an average EF for the 3DE data of 0.55 ± 0.05 and 0.65 ± 0.02 for the MRI
data. The p-value of 0.000 of a multifactor ANOVA test shows that this is a significant difference. Both
the observer and the software package used have a significant influence on the EF determined, as does
the acquisition of the 3DE data. The acquisition of the MRI data does not seem to have any effect on the
EF.
Eindhoven University of Technology
ii
Samenvatting
Zowel 3D echocardiografie (3DE) en cardiac magnetic resonance imaging (MRI) kunnen gebruikt worden om de linker hartventrikel ejectie fractie (EF) te bepalen. Ejectie fractie wordt bepaald het verschil
tussen door het einddiastolisch volume (EDV) en het eind systolisch volume (ESV) en dit te delen door
het EDV. Verschillende studies hebben al geprobeerd om de overeenkomst tussen de EF bepaald met 3DE
en MRI te meten. Een literatuur studie van 14 van deze studies laat zien dat er geen significant verschil
is tussen de EF’s, maar de combinatie van veel verschillende patinten, variaties in hart pathologie en een
gebrek aan gepaarde en individuele data zorgen ervoor dat de standaard deviatie of de data zo groot is dat
een eventueel verschil niet aangetoond kan worden. In deze studie, gedaan in het MMC in Veldhoven,
wordt ook geprobeerd om te bepalen of de EF bepaald met 3DE en MRI gelijk zijn, maar hier wordt
maar een gezonde proefpersoon gebruikt. Daarnaast worden een aantal verschillende software pakketten
gebruikt om de 3DE en MRI data te analyseren. In totaal zijn er 9 3DE’s gemaakt en 3 MRI’s. De software pakketten die gebruikt zijn, zijn CAAS MRV van Pie Medical en 4D LV analysis MR van Tomtec
voor de analyse van de MRI data, en Qlab 3DQ Advanced van Philips en 4D LV analysis van Tomtec.
Elke 3DE en MRI is een aantal keer geanalyseerd door 2 analisten. Dit resulteerde in een gemiddelde
EF van 0,55 ± 0,05 voor 3DE en 0,65 ± 0,02 voor MRI. Een multifactor ANOVA toets laat zien dat er
een significant verschil is tussen 3DE en MRI. De waarde van de EF is afhankelijk van de analist en het
software pakket en bij 3DE ook van de acquisitie. Bij MRI is de hoogte van de EF niet afhankelijk van
de acquisitie.
Ellemiek Wintjes
CONTENTS
i
Contents
1
2
3
4
Introduction
1.1 The heart . . . . . . . . . . . .
1.1.1 The cardiac cycle . . . .
1.1.2 Visualization of the heart
1.2 Goal . . . . . . . . . . . . . . .
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Literature Review
2.1 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.1 Results of comparison of volumes and EF’s . . . . . . . . . . .
2.1.2 Comparison of 3DE acquisition hardware and analysis software
2.1.3 Comparison of MRI acquisition hardware and analysis software
2.1.4 Comparison of data analysis methods . . . . . . . . . . . . . .
2.1.5 Reproducibility . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . .
Materials and Methods
3.1 Study setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.1 Software packages . . . . . . . . . . . . . . . . . . . . . . .
3.2 Acquisitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1 MRI Protocol . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.2 RT-3D echocardiography protocol . . . . . . . . . . . . . . .
3.3 Comparisons/Statistics . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.1 Outlier test . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.2 One-way and multifactor Analysis of Variance (ANOVA) test
3.3.3 Multiple range test . . . . . . . . . . . . . . . . . . . . . . .
Results
4.1 Raw data . . . . . . . . . . . . . . . .
4.2 Comparison between 3DE and MRI . .
4.3 Comparison of 3DE software packages .
4.4 Comparison of MRI software packages
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5
Discussion
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Conclusions
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Eindhoven University of Technology
ii
7
CONTENTS
Recommendations
7.1 Acquisitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Bibliography
A Imaging modalities
A.1 Cardiac MRI . . . . . . . . . . . . . . . . . . . . .
A.1.1 Imaging planes . . . . . . . . . . . . . . . .
A.1.2 Synchronization of acquisitions with motion
A.2 Echocardiography . . . . . . . . . . . . . . . . . . .
A.2.1 Reconstructed . . . . . . . . . . . . . . . . .
A.2.2 ECG triggering . . . . . . . . . . . . . . . .
A.2.3 Real-time . . . . . . . . . . . . . . . . . . .
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B Tables
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C Analysis Protocol Caas MRV
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D Matlab files
D.1 Qlab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
D.2 Tomtec . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
D.3 Caas MRV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
53
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E Data
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F Abbreviations
66
Ellemiek Wintjes
1
Chapter 1
Introduction
1.1
The heart
The heart is one of the most important organs in the human body. It is a hollow muscle that pumps
blood through the body. A mammal heart consists of a total of four heart chambers, the two upper
ones are the atria and the two lower ones the ventricles, see figure 1.1. The heart is usually situated
in the middle of the thorax with the largest part of the heart slightly offset to the left, underneath the
breastbone. The heart is enclosed by a sac known as the pericardium and surrounded by the lungs.
Because the left side of the cardiac muscle is stronger, people normally feel their heart on the left
side of the chest. The left ventricle (LV) pumps oxygen rich blood from the lungs to the rest of the
body. The right ventricle (RV) pumps the blood coming from the body to the lungs. The superior
side of the heart is called the base. It contains the semi-lunar aortic and pulmonary valves, the left
atrioventricular (AV) mitral valve and the right AV tricuspid valve. The apex is the blunt point situated
in an inferior direction (pointing down and left).
The apex is located posterior to the 5th intercostal
space in the left mid-clavicular line. In normal
adults, the mass of the heart is 250-350 g, but extremely diseased hearts can weigh up to 1000 g
due to hypertrophy. The heart has a normal stroke
volume (SV) of about 70 ml per beat and a cardiac
output (SV × heart rate) of 5 l/min. The heart rate
is normally around 70 beats per minute.
1.1.1
The cardiac cycle
As can be found in [1]: ”The cardiac events that
occur from the beginning of one heartbeat to the
beginning of the next heartbeat are called the cardiac cycle. Each cycle is initiated by spontaneous
generation of an action potential in the sinus node.
This node is located in the superior lateral wall of
the right atrium near the opening of the superior
vena cava, and the action potential travels from Figure 1.1: Overview of the heart. Taken from Guyton [1], page 97.
here rapidly through both atria and through the A-V bundle into the ventricles. Because of this special
1
arrangement of the conducting system from the atria into the ventricles, there is a delay of more than 10
second during passage of the cardiac impulse from the atria into the ventricles. This allows the atria to
contract ahead of the ventricles, thereby pumping blood into the ventricles before the strong ventricular
contraction begins.”
Eindhoven University of Technology
2
Introduction
Figure 1.2: Summary of events occurring in the heart during the cardiac cycle. (a) Events in the
left side of the heart. An ECG tracing is placed above the graphs of pressure and volume changes so
that they can be related to electrical events occurring at any point. (b) Events of phases 1 through 3
of the cardiac cycle are depicted in diagrammatic views of the heart. Adapted from Marieb [2], page
703.
Ellemiek Wintjes
1.1 The heart
3
Figure 1.2 presents an overview of the events occurring in the heart during the cardiac cycle. This
overview starts with the heart in total relaxation: both atria and ventricles are relaxed, and it is mid-to-late
diastole. The phase indicated by interval 1 in figure 1.2, is the period of ventricular filling. According
to [2]: ”The pressure in the heart is low and blood returning from the circulation is flowing passively
through the atria and the open AV valves into the ventricles below. The semi-lunar valves are closed.
Approximately 70% of ventricular filling occurs during this period and the AV flaps begin to drift upward
toward their closed position. The remaining 30% of the filling is delivered to the ventricles when the atria
contract following depolarization (the P wave of the electrocardiogram (ECG)), compressing the blood
in their chambers. This causes a sudden slight rise in atrial pressure, which propels residual blood out
of the atria into the ventricles. At this point the ventricles are in the last part of their resting phase and
have the maximum volume of blood they will contain in the entire cardiac cycle. This volume is called
the end diastolic volume (EDV). Then the atria relax and the ventricles depolarize (QRS complex on the
ECG). Atrial diastole persists through the rest of the cycle.
As the atria relax, the ventricles begin their contraction phase. Their walls close in on the blood in
their chambers, and ventricular pressure rises rapidly and sharply, closing the AV valves. For about 50
ms, the ventricles are completely closed chambers and blood volume in the chambers remains constant.
This isovolumetric contraction phase is phase 2a in figure 1.2. Ventricular pressures continue to rise and
when they finally exceed the pressure in the large arteries at the other side of the valves, the isovolumetric
stage ends as the semi-lunar valves are forced open and the blood is expelled from the ventricles into the
aorta and pulmonary artery. During this ventricular ejection phase (phase 2b in figure 1.2), the pressure
in the aorta normally reaches up to 120 mm Hg.
During a brief phase following the T wave, the ventricles relax. Because the blood remaining in their
chambers, referred to as end systolic volume (ESV), is no longer compressed, the ventricular pressure
drops rapidly and blood in the aorta and pulmonary artery starts to flow back toward the heart, closing
the semi-lunar valves. This results in phase 3 in figure 1.2 and is called isovolumetric relaxation or early
diastole. Once again the ventricles are totally closed chambers.
During ventricular systole, the atria have been in diastole. They filled with blood and the intra-atrial
pressure has been rising. When the pressure exerted by the blood on the atrial side of the AV valves exceeds that in the ventricles, the AV valves are forced open and ventricular filling, phase 1, begins again.”
The cardiac function can be described using several parameters. In this study the end diastolic volume
(EDV), end systolic volume (ESV) and the ejection fraction (EF) are used as the important parameters.
These are also important prognostic factors [3]. EDV is defined as the volume of the left ventricular cavity at the moment of closure of the mitral valves (the line between phase 1 and 2a in figure 1.2). ESV is
defined as the volume of the left ventricle at the moment of opening of the mitral valves (the line between
phase 3 and 1 in figure 1.2). EF is calculated by subtracting the ESV from the EDV and dividing this
by the EDV. Because this method results in a fraction between 0 and 1, the EF is often multiplied with
100% to create a percentage.
EF =
1.1.2
EDV − ESV
(∗100%)
EDV
Visualization of the heart
It can be very useful to visualize the heart for patients with cardiac problems. This can be done using several different visualization techniques. The two most commonly used techniques are cardiac
magnetic resonance imaging (MRI) (see appendix A.1) and echocardiography. Echocardiography has
Eindhoven University of Technology
4
Introduction
developed from a 1-dimensional M-mode ultrasound twenty-five years ago, to a 2-dimensional (2D)
echocardiography and reconstructed 3-dimensional (3D) echocardiography nowadays. Recently realtime 3-dimensional echocardiography (3DE) was added to this list. 3DE uses a special array transducer
to create a pyramidal shaped volume. An explanation about this technique is given in appendix A.2.
MRI is currently seen as the golden standard for the visualization of the heart and the assessment of
cardiac function. It provides real-time visualization of the heart and the blood flow inside the cardiac
muscle and it is non-invasive. The drawbacks of MRI are that it is not usable in patients with a pacemaker, it cannot be performed at the bedside, it takes a lot of time, it is very expensive and it is difficult to
use in patients with cardiac arrhythmias. The first two drawbacks can be overcome using echocardiography in stead of MRI. Echocardiography is also less expensive and less time consuming. The drawbacks
of 3DE are a lower resolution compared to conventional 2D echocardiography and the problem that enlarged hearts might not fit within the pyramidal shape [4].
Another drawback of echocardiography is that it has to be done with the patient laying the left lateral decubitus position (see appendix A.2). One of the points to consider when using 3DE or any other form of
echocardiography is that laying in the lateral decubitus position for 15 minutes can cause discomfort and
worsen the lung function in patients with chronic heart failure [5]. The effects are much smaller when
laying on the back, so for these patients follow up by MRI would be better. Another problem with 3DE
is that the image quality of 3DE can be a problem in patients with poor acoustic windows, see appendix
A.2. Because the image quality is currently lower than 2DE it might be difficult to detect the endocardial
borders in these patients [6].
1.2
Goal
Because both 3DE and MRI can be used to determine cardiac parameters, the general question of this
study is whether there are differences between the values for left ventricular volumes and EF measured
with MRI and 3DE. Several studies have tried to determine if MRI and 3DE are comparable for the analysis of left ventricular (LV) volumes and ejection fraction (EF). In chapter 2 a literature review of some
of these studies is described. The conclusion of this literature review is that 3DE and MRI appear to be
equally accurate in determining the LV cavity volumes and EF, but there is a large standard deviation
(SD) due to the range of ages of the test subjects, the different cardiac pathologies they suffer from and
the fact that no individually paired data are given, but only average data.
Therefore the goal of this study is to determine if there are significant differences between the EF calculated with 3DE and MRI for when used on one test subject. In addition the interobserver variability, and
the performances of several different analysis software packages are investigated.
Ellemiek Wintjes
5
Chapter 2
Literature Review
Both MRI and 3DE can be used to visualize the heart and analyse the LV function. Several studies have
tried to determine if the volumes between 3DE and MRI are different. This literature review compares
fourteen of those studies. The volumes and EF’s calculated with 3DE and MRI in these studies are
compared, as well as the acquisition hardware and the analysis software are compared.
2.1
2.1.1
Results
Results of comparison of volumes and EF’s
Fourteen studies were selected on the basis of several criteria. The first criterion was that 3D echocardiography had to be used to determine volumes and EF. This resulted in studies published between 2001
and December 2007. The second criterion was that values for the 3DE and MRI data had to be given.
And the third criterion was that the study had to compare 3DE to another imaging modality, preferably
MRI.
Table 2.1 gives the original data of the values for the cardiac parameters found in several studies. Studies
3, 4, 5, 8 and 10 included patients or healthy volunteers with a normal LV function in their study group.
Two lines within one study indicate the use of multiple techniques or analysis methods, see sections
2.1.2 and 2.1.4. None of the papers gave the data of the individual patients; only the mean and standard
deviation (SD) of the group were given. Thus the values used in this study are the average values of the
patient groups used in the papers.
From the fourteen studies on this subject given in table 2.1, four where discarded from further analysis
because they were not executed in the same way as the other ten. Study 11, Busch 2007 [7], was removed
because this research used an 3T MR scanner in stead of the 1.5 T MR scanner used in the other studies
and they compared CT and not 3DE to MR. Using a 3T scanner, should not have any effect on the cardiac
parameters, but there is not enough research on 3T scanners published to be conclusive on this. Study
12, Giakoumis 2007 [8], and 13, Van den Bosch 2006 [9], were removed because the research was done
on much younger patients, age 30 ± 6 years and 31 ± 9 years, respectively, as compared to an average
of 57 years for the other studies (indicated in red on table 2.1), and also because no or not all 3DE values
were given. EF is related to age, in older subjects the EF tends to be lower. Study 14, Mor-Avi 2004
[4], was removed because they only compared MRI and 3DE for LV mass. They did give a value for the
EDV in MR but none of the other cardiac parameters was mentioned.
Figure 2.1 gives the data of the remaining studies. In studies 1,2 and 3 only the mean values are given
because it was unclear how the SD was calculated, indicated in yellow in table 2.1. Analyzing this figure
shows that the weighted average volumes (indicated with ∗ in the left of the figure) are slightly but not
significantly lower for 3DE then for MRI (161 ml ± 62 ml vs. 177 ml ± 62 ml respectively, for EDV
Eindhoven University of Technology
6
Literature Review
Table 2.1: All original data given in the studies. The column Men gives the fraction of male participants. The studies indicated in red (study 12 and 13) are excluded because of the younger patients.
It was unclear how the SD in the studies 1, 2 and 3, indicated in yellow, was calculated. The second
line of study 1 is the result of reconstructed 3D echocardiography (see appendix A.2). The top line
of study 4 is the result of dual triggering and the second line of normal continuous imaging. The
second line in study 6 is the result of the use of a contrast agent. The top line with study 7 is the
result of using full volume reconstruction and the second line of using multiplane interpolation.
Study
1 Jenkins 2007 a
2 Jenkins 2006
3 Jenkins 2004
4 Caiani 2005 a
5 Caiani 2005 b
6 Krenning 2007
7 Soliman 2007
8
9
10
11
12
13
14
Qi 2007
Lee 2001
Nikitin 2005
Busch 2007
Giakoumis 2007
vd Bosch 2006
Mor-Avi 2004
CMR
RT3DE
Age (years)
EDV (ml) ESV (ml) EF (-)
EDV (ml) ESV (ml)
EF (-)
n Mean σ Range Men Mean σ Mean σ Mean σ Mean σ Mean σ Mean σ
30
66
7
0,73 168 54 86 50 50 13 153 31
78
26 49
7
142 33
73
42 46
9
110 63 10
0,85 180 55 93 50 50 13 136 35
72
28 48 10
165 28
83
22 51
8
50
64
8
0,82 172 53 91 53 50 14 168 29
88
18 50
7
20
58 17
0,50 164 64 94 55 47 16 150 65
89
48 42 17
141 57
79
48 47 16
46
53 17
0,59 168 70 99 69 46 19 162 68
96
64 45 17
39
58 15 24-79 0,87 218 70 125 69 45
5 198 60 116 58 43 13
200 67 117 65 44 15
53
56 11
0,53 175 51 74 51 61 17 165 50
69
48 61 18
150 48
63
44 61 18
58
59 17 21-83 0,69 139 59 79 57 47 16 117 53
64
46 48 12
25
51 15
0,68 190 97 93 87 56 15 191 93
97
87 60 15
64
65 12 34-85 0,80 195 72 117 68 44 16 202 74 121 66 43 15
15
51 19
0,87 132 41 58 27 58
9
135 30
6
0,47 138 43 46 21 67
8
32
31
9 19-51 0,59 155 38 62 27
151 36
61
27
19
48 16
0,68 172 14
and 85 ml ± 57 ml vs. 95 ml ± 59 ml for ESV) and that the weighted average EF is the same for both
techniques (49.5 % ± 15.5 % vs. 49.4 % ± 14.4 % for 3DE and MRI Respectively). This corresponds
to the results of most of the studies. Only study 5, Caiani 2005 b [10], study 9, Lee 2001 [11], and
study 10, Nikitin 2005 [12], found no differences between MR and 3DE. The results of the other studies
showed that 3DE LV volumes are lower when compared to MRI but EF are similar. These results are not
the conclusions of the different studies but the results when 3D echo is compared to MRI. Some studies
compare for instance different echo techniques, and conclude that one technique is better then the other,
but in their results they show that both underestimate the volume when compared to MRI.
Figure 2.2 shows the differences between 3DE and MRI compared to the average of the means of the
two methods. This shows that most of the MRI values for the EDV and ESV are higher then those of
3DE. The difference between the MRI and 3DE values is about 9,7 % of the average of the mean MRI
and 3DE values. For EF this difference is 1,7 %.
Ellemiek Wintjes
EF
90
n=53
n=25
80
n=30
Ejection Fraction
n [%]
70
n=110
n=50
n=20
n=58
n=46
*
n=39
n=64
60
MR
3DE
Average MR
50
Average 3DE
40
30
20
EDV
300
250
Volume [mL]
*
200
MR
3DE
Average MR
Average 3DE
150
100
50
ESV
250
200
Volume [mL]
*
150
MR
3DE
Average MR
Average 3DE
100
50
0
0
1
2
3
4
5
6
7
8
9
10
Study
Figure 2.1: Ejection fraction, end-diastolic and end-systolic volumes given by the different studies.
The points are MRI data and the squares 3DE. n gives the number of patients used for each study.
On the left side, indicated with an ∗, a weighted average and weighted SD are shown, the triangle
for the MRI data and the X for the 3DE data. The weighted average and weighted SD are weighted
to the number of patients used for each study. The SD of the 3DE weight average is only calculated from the data with an SD. All data are given with mean and SD except for the 3-dimensional
echocardiography (3DE) data of study 1, Jenkins 2007 a [13], study 2, Jenkins 2006 [14] and study
3, Jenkins 2004 [15]. The numbers on the x-axis coincide with the study numbers given in table 2.1.
8
Literature Review
Bland-Altman Plot EDV
Bland-Altman Plot ESV
50
50
Difference
40
Mean Difference
Mean Difference
30
Difference
40
30
Mean Diff. ± 2SD
Mean Diff. ± 2SD
20
ESV in ml (3DE - CMR)
C
EDV in ml (3DE - CMR)
C
20
10
0
-10
-20
10
0
-10
-20
-30
-30
-40
-40
-50
-50
100
120
140
160
180
200
220
240
60
70
80
90
100
EDV in ml (3DE + CMR)/2
ESV in ml (3DE + CMR)/2
(a)
(b)
110
120
Bland-Altman Plot EF
6
4
EF in % (3DE - CMR)
Difference
2
Mean Difference
Mean Diff
Diff. ± 2SD
0
-2
-4
-6
40
45
50
55
60
65
EF in % (3DE + CMR)/2
(c)
Figure 2.2: Differences between the values for the EDV (a), ESV (b) and EF (c) of the two techniques compared to the average of the two techniques.
Ellemiek Wintjes
2.1 Results
2.1.2
9
Comparison of 3DE acquisition hardware and analysis software
All the studies use real-time 3D transthoracic echocardiography. Jenkins et al. (2007 a) [13] also used
reconstructed 3D echocardiography (second line of study 1 in table 2.1). Table 2.2 gives an overview of
the 3D ultrasound machines and the analysis software used by the different studies. Most studies use a
Philips Sonos 7500 and some the more recent Philips iE33. For the analysis of 3DE images Tomtec’s 4D
analysis is the most popular.
Table 2.2: Overview of devices and software used to acquire and analyse 3DE images.
14
6
Jenkins 2007 a
Jenkins 2006
Jenkins 2004
Caiani 2005 a
Caiani 2005 b
Sugeng 2006
Mor-Avi 2004
Krenning 2007
Ultrasound machine
Philips Sonos 7500
Philips iE33
Philips Sonos 7500
Philips Sonos 7500
Philips Sonos 7500
Philips Sonos 7500
Philips Sonos 7500
Philips iE33 and Philips Sonos 7500
7
Soliman 2007
Philips iE33 and Philips Sonos 7500
13
Philips Sonos 7500
8
Van den Bosch 2006
Qi 2007
9
Lee 2001
10
Nikitin 2005
1
2
3
4
5
Philips iE33
Volumetric Machine (Duke University)
Philips Sonos 7500
Software
4D Analysis Tomtec
3DQ-lab and 4D Analysis Tomtec
4D Analysis Tomtec
3DQ-lab and custom software
Custom software
4D Analysis Tomtec
3DQ-lab
Tomtec Echoview
4D Analysis Tomtec version 1.2 and
version 2.0
4D Analysis Tomtec and Tomtec
Echoview
Tomtec Echoview
Custom software
4D Analysis Tomtec
Caiani et al. (2005a) [16] studied the effect of dual triggering. Dual triggering means that next to the
normal R-wave triggering they also triggered to the end of the T-wave. In the data set acquired with
this dual triggering protocol only end-diastolic and end-systolic frames are present. In table 2.1 the top
line of study 4 gives the dual-triggering data and the bottom line the normal, continuous imaging data.
This entire study was done using a contrast agent. Krenning et al. (2007) [6] also used contrast agents
(bottom line of study 6 in table 2.1). They found that both contrast and non-contrast enhanced techniques
underestimate the cardiac volumes compared with MRI.
2.1.3
Comparison of MRI acquisition hardware and analysis software
Table 2.3 shows the machines and software used to acquire and analyse the MRI data. CIM 4.2 is a software package used and developed by the University of Queensland, Australia [6]. The Tomtec prototype
software used by Sugeng et al. [17] is MRI software that uses long-axis images instead of the normally
used short-axis images.
Several articles presented the LV EDV and ESV index (in [ml/m2 ]) to give the cardiac volumes. The
EDV index and ESV index are calculated by normalizing the cardiac volumes to the body surface area
calculated from the BMI. These indexes are clinically more meaningful than nonindexed volumes, because LV volume correlates with body size [18]. This correlation is only confirmed in the absence of
coronary, valvular, or myocardial heart disease. All studies using these indexes are done on patients with
cardiac diseases, so it is unclear if these indexes can be used and are meaningful in these patients.
Eindhoven University of Technology
10
Literature Review
Table 2.3: Overview of devices and software used to acquire and analyse MRI images.
1
2
3
4
5
14
6
7
13
8
9
10
11
12
2.1.4
Jenkins 2007 a
Jenkins 2006
Jenkins 2004
Caiani 2005 a
Caiani 2005 b
Sugeng 2006
Mor-Avi 2004
Krenning 2007
Soliman 2007
Van den Bosch 2006
Qi 2007
Lee 2001
Nikitin 2005
Busch 2007
Giakoumis 2007
Scanner Type
Siemens 1.5 T
Siemens 1.5 T
Siemens 1.5 T
GE 1.5 T
GE 1.5 T
Siemens 1.5 T
GE 1.5 T
GE 1.5 T
GE 1.5 T
GE 1.5 T
Siemens 1.5 T
Philips ACS 1.5 T and GE 1.5 T
GE 1.5 T
Magnetom Trio 3.0 T (siemens)
GE 1.5 T
Software
CIM 4.2
CIM 4.2
CIM 4.2
Mass analysis (GE)
Mass analysis (GE)
Tomtec prototype and ARGUS (siemens)
Mass analysis (GE)
MASS (Medis)
MASS (Medis)
MassPlus (Medis)
ARGUS (siemens)
custom technique (no software)
MASS (Medis)
ARGUS (siemens)
MASS PLUS (GE)
Comparison of data analysis methods
To analyse the data acquired with 3DE and MRI several different software packages are available.
The 3DE packages use long-axis analysis. In each data set, end-systolic frames and end-diastolic frames
are identified. Around a non-foreshortened LV long axis (LA), the software generates several equiangular long axis apical images for each volume. Foreshortened means to see or draw an object from such an
angle that it appears to be shorter than it really is. With 2D echocardiography it is possible to create an
image of the heart in which the long axis appears to go from the middle of the mitral valve to the point
of the apex, which actually is a slightly foreshortened view because the long axis seen in the image is
slightly canted and shorter than the official long axis and not going through the point of the LV. Apical
means made from the apex, see figure A.3. These long-axis end-diastolic and end-systolic images are
manually traced with help of short-axis frames, or three points are manually marked and the software
automatically generates an ellipse through these points. Trabeculae and papillary muscles can be included or excluded from the volume, this differs per study. EDV, ESV and EF are calculated by software.
For LV mass calculation, an ellipse is traced around the epicardial border in the end-diastolic frames to
provide a 3-dimensional volume. The endocardial volume is subtracted from the epicardial volume and
multiplied by the specific density of heart muscle (1,05 g/ml).
The MRI packages mostly use short-axis (SAx) analysis. LV slices are selected for analysis including the highest basal slice where the LV outflow tract is not visible and the lowest apical slice where the
LV cavity is visualized. Endocardial contours are traced manually in the end-diastolic and end-systolic
frames of each slice. The endocardial contours in the remaining frames are semi automatically traced.
Again the papillary muscles can be included in or excluded from the LV cavity (i.e. included in or excluded from the LV volume) depending on the study. Table 2.4 shows which studies include the papillary
muscles and trabeculae in the LV cavity. Most studies include the papillary muscles in the volume in both
3DE analysis and MRI analysis. From the contours, LV volume is computed throughout the cardiac cycle
using a disk-area summation method (modified Simpson’s rule). The EDV and ESV are then determined.
Soliman et al. [19] evaluated two different 3DE semi-automated border detection algorithms: full volume
Ellemiek Wintjes
2.1 Results
11
Table 2.4: Overview of studies including and excluding the papillary muscles and trabeculae in the
LV volume. All studies use the same convention for MRI and 3DE. Yes means that the papillary
muscles are included in the blood volume and No means that they are excluded. NA means that no
information about in- or exclusion is available.
Papillary muscles in LV volume
Jenkins 2007 a
No
Jenkins 2006
Yes
No
Jenkins 2004
Jenkins 2007 b
Yes
Yes
Caiani 2005 a
Caiani 2005 b
Yes
Yes
Sugeng 2006
Mor-Avi 2004
Yes
Krenning 2007
Yes
Yes
Soliman 2007
Van den Bosch 2006 Yes
Yes
Qi 2007
Lee 2001
NA
No
Nikitin 2005
Busch 2007
Yes and No (CT)
Giakoumis 2007
NA
Total
11 Yes and 3 No and 2 NA
reconstruction (FVR) and multiplane interpolation. Multiplane interpolation is the technique described
previously of taking several, in this case eight, uniformly spaced apical images, rotated 22,5◦ each, around
a non-foreshortened LV long axis image. FVR is a method that uses three planes with manually traced
endocardial borders. Based on these six initial contours (three for EDV and three for ESV) a spatiotemporal spline interpolation model is created by rotational and temporal interpolation of the contours. The
algorithm automatically detects the endocardial border continuously in the entire 4-dimensional data set
and deforms the initial model until it best fits the walls in each frame. The upper row of the 3DE data of
study 7 in table 2.1 are the FVR data and the bottom row the multiplane interpolation data.
MRI is currently seen as the gold standard for assessment of LV volumes and EF. It is not exactly known
if the values measured with MRI are the correct values, because MRI may overestimate the LV cavity
size by filling the space between the trabeculae [13], [14]. Also MRI analysis uses short-axis images
with a disk summation method to obtain a LV volume. This analysis is not optimal near the apex because
of partial-volume artefacts and the mitral valve might be difficult to recognize. Another reason why the
analysis might be wrong is that a part of the aortic root or left atrium might be included in the volume of
the reconstructed disk in the most basal cross-section. These problems could be reduced by increasing
the number of disks or by incorporating long-axis analysis [9], [12], [6].
The acquisition times for 3DE and MRI in the studies compared in this literature review differ significantly. For 3DE the acquisition time is about 1 minute, while for MRI it is at least 15 minutes. Analysis
times for 3DE vary between 4 and 20 minutes, and for MRI they are around 10 minutes. See also table
B.1.
Eindhoven University of Technology
12
2.1.5
Literature Review
Reproducibility
In the studies several techniques are used to determine the reproducibility of the scans and the measurements. Three different definitions are used: test-retest, interobserver and intraobserver variability.
Test-retest variability means repeating the imaging within a certain amount of time with no intervening therapy and comparing the results. The difference between the values measured by two different
sonographers using the same set of 3-dimensional and 2-dimensional images is interobserver variability.
Intraobserver variability is the difference between EF’s and volumes calculated from repeated measurements on the same data set by the same sonographer at different points in time, with randomization of
the order of repeated analysis. Several studies give values for test-retest, interobserver and intraobserver
variability, but it is unclear what these values mean and how they are calculated.
2.2
Discussion and conclusions
The goals of this study were to determine if there are differences between the values for EF, EDV and
ESV measured with MRI and 3DE and how large these differences are, how cardiac parameters like
EF are calculated, and which hardware and software are used for these calculations. Analysis of the
data of the different studies shows that there are differences between the values for EDV and ESV, but
not for EF. This is exactly what is expected. If both techniques are used on the same heart the EF
calculated is expected to be similar, but a difference between the calculated volumes might occur. The
MRI volume could for instance be overestimated, because the trabeculae and papillary muscles might be
added to the blood volume as a result of interpolation and slices thickness, or it might be possible that
3DE underestimates the volume because the LV wall and the valve plane are more difficult to determine.
Trabeculae and papillary muscles are muscles and fiber like structures in the heart to strengthen the valves
and they occupy part of the ventricular cavity. A possible model for this dependence of the volumes is
Vecho = αVM RI + β. The α is an unknown factor but it is caused by the differences between the
techniques and analysis software and the β is a possible offset in the volumes caused by for example the
in- or exclusion of the papillary muscles. If beta is 0, no offset is present, the EF calculated would result
in:
EFEcho =
EDVEcho − ESVEcho
EDVEcho
(2.1)
EFEcho =
αEDVM RI − αESVM RI
= EFM RI
αEDVM RI
(2.2)
The papillary muscles would have the following effect on the EF:
EFpap =
(EDV + Vpap ) − (ESV + Vpap )
EDV + Vpap
(2.3)
EFpap =
EDV − ESV
EDV
∗
EDV
EDV + Vpap
(2.4)
EFpap = EF ∗
EDV
1
= EF ∗
Vpap
EDV + Vpap
1 + EDV
EFpap ≈ EF ∗ (1 −
Vpap
)
EDV
with Vpap the volume of the papillary muscles.
Ellemiek Wintjes
(2.5)
(2.6)
2.2 Discussion and conclusions
13
The difference between the volumes given in this literature review is on average about 9,7 % of the
average value determined by both techniques. This is probably only true for a limited domain. For large
hearts this difference will be probably be smaller. This could be tested by analyzing the MRI and 3DE
data of athletes. Runners and cyclist often have enlarged hearts. For smaller hearts the value will be
different too. This can be determined by performing similar research on children.
The average value for the difference is calculated from the means of the data of the studies. For one
individual study and patient group this value might be different. Most studies give a so-called BlandAltman plot which shows the difference between 3DE and MRI on the y-axis and the MRI or average on
the x-axis, but only Soliman et al. [19] give the percentages of the differences compared to the average.
All others only state the average difference in milliliters. For the full volume reconstruction (FVR) software these are -6% and -9% for EDV and ESV, respectively and for the multiplane interpolation method
-15% and -18%. For the EF they found a mean difference of 1% and 1.3% when using multiplane interpolation and FVR, respectively. This also indicates that the software used to analyse the data sets has a
major influence on the data. This is the reason why the methods used to calculated the LV volumes and
EF should be similar.
The weighted averages of figure 2.1 shows a large SD on the different data. The variance within one
study is also very large. This large SD is probably caused by patient characteristics like age, gender and
pathology, but might also be the result of the used techniques and the variability within these techniques.
The reproducibility of the techniques is not exactly known. To determine the reproducibility it could be
useful to do multiple acquisitions and analysis of the same person for both MRI and 3DE.
In summary, several studies have compared the LV volumes determined with 3DE and MRI, but the
combination of many different subjects and cardiomyopathies makes it impossible to determine if there
are any differences between these variables. Only given one MRI and one 3DE study was performed
on each patient. Because the acquisition of the data might already influence the results (foreshortening,
imaging planes) it might be possible that some data are extremely low or high as a result of the acquisition. Another problem is the way in which the data are analyzed in the studies. The exact methods are
often unclear. In this study only one healthy test subject will be used and all acquisitions and analyses
are done several times. Only one test subject is used, because it is difficult to compare the EF’s of two
different subjects, no more time was available to test another subject and the second subject tested proved
to give non-analyzable 3DE data.
Eindhoven University of Technology
14
Ellemiek Wintjes
Literature Review
15
Chapter 3
Materials and Methods
3.1
Study setup
The goal of this study is to compare the EF’s calculated with MRI and 3DE, the interobserver variability,
and the different analysis software packages. No comparison between the volumes calculated with both
techniques is done because the EF is a combination of these volumes and EF is clinically more relevant
than volume.
To determine the reproducibility and the interobserver variability the heart of one healthy person was
studied several times with MRI and real time 3D echocardiography (3DE) using a standardized protocol.
These studies where then analyzed by two different observers (EW and JG). For the analysis several
software package are used, each of which will be described later. To determine the amount of variability
caused by each software package, every dataset was analyzed several times by each observer.
3.1.1
Software packages
For the analysis of the MRI and ultrasound data sets, several different software packages are used. Pie
medical CAAS MRV and Tomtec 4D LV-Analysis MR are used for MRI data, and Philips QLAB ultrasound quantification software and Tomtec 4D LV-Analysis for the ultrasound data. A short introduction
to each of these packages is given in this section.
Pie Medical CAAS
CAAS (Cardiovascular Angiography Analysis System) is a quantitative analysis software package for
cardiology and radiology from Pie Medical Imaging. In this particular study, CAAS MRV (Magnetic
Resonance Ventricular analysis) is used. In this package there are 4 different methods to create the
contours to determine the EDV, ESV and EF: a completely automated method, a long axis (LA) based
automated method, a semi-automatic method and a completely manual method.
The first one is a completely automated contour detection system. This system automatically determines
the ED frame and the ES frame and which short axis (SAx) slices contain the apex and base. The software then draws epicardial, endocardial and papillary muscle contours. These contours are then used to
calculate the EDV and ESV and subsequently the EF.
The second method is the automatic LA based method. This method is almost the same as the automatic
method, except the ED and ES frame have to be determined manually. The basal and apical slices are
determined from endocardial and epicardial contours in the ED and ES frame of both the 2 chamber and
the 4 chamber view (8 contours), see appendix A.1. The other purpose of these contours is interpolation
and volume correction of the short axis (SAx) based contours. Interpolation is necessary because the
SAx slices have a thickness of 1 cm. These contours are also used for a correction of the apex curvature.
Eindhoven University of Technology
16
Materials and Methods
One SAx ED endocardial contour has to be drawn in the slice with the largest LV diameter. The software
then automatically draws all the other contours and determines EDV and ESV.
The third method is a semi automatic method. With this method one endocardial contour has to be drawn
somewhere in between the ED and ES frame in every slice. This contour is then propagated forwards
and backwards in time and the software automatically draws the papillary muscle contours. The ED and
ES frame have to be determined manually as in the previous method, and again the 8 LA contours have
to be drawn.
The last method is completely manual. In every ED and ES slice the endocardial and papillary muscle
contours have to be drawn and the EDV and ESV are calculated from these contours. The 8 LA contours
have to be drawn first. It is important for all methods to correctly identify the ED and ES frame. If this
identification is not performed correctly, the calculated ED and ES volumes will not be correct, because
these are not the actual EDV and ESV. Consequently, the EF will also be incorrect.
Because Caas MRV has 4 different ways to analyse a dataset a test was performed to see which method
would be the best and most efficient way. The results of this test are shown in appendix C. Based on the
test, only the semi automated (SA) and manual analysis method were used.
Tomtec 4D LV-Analysis MR
The second software package used to analyse the MR data sets is a completely new software package.
With the Tomtec MR package one first has to correctly assign the 2, 3 and 4 chamber views by rotating
the dataset. The next step is drawing an endocardial ED and ES contour in each of the three views, so 6
contours in total. These contours are used to determine the contours in all phases and can be adjusted. A
4D model (3D moving in time) of the LV is created from these contours and the EDV, ESV and EF are
calculated, as well as several other parameters.
Philips QLab
Philips Qlab has a 3D echo package called 3DQ adv. First the 2 and 4 chamber view have to be determined correctly, so the LA is non-foreshortened. Secondly five reference points have to be indicated in
the ED and ES frame. The reference points are indicated as the SALI points. SALI stands for the septal,
anterior, lateral and inferior side of the mitral valve. The fifth point is the apex. 3DQ adv. uses these
five references points to detect the 2 and 4 chamber ED and ES contour. The ED frame is the first frame
because of ECG triggering, see appendix A.2.2. The ES frame has to be determined manually. These
contours are interpolated into a 3D volume in all frames. The contours can be adjusted manually.
TomTec 4D LV-Analysis
The other software package for the analysis of the echocardiography data sets is 4D LV analysis by
TomTec. This software uses contour detection. First correct, non-foreshortened 2 chamber, 3 chamber
and 4 chamber views have to be selected. In each view an ED and ES contour has to be drawn. The
software uses these contours to calculated the LV volume. It creates a 4D model of the LV. This model
can be adjusted manually. The ED and ES phase are automatically determined, but can be corrected
manually.
3.2
Acquisitions
3.2.1
MRI Protocol
In order to make the MR data acquisitions compatible with the TomTec MR software, some changes to
the standard acquisition protocol used in MMC Veldhoven had to be made. The standard MRI protocol
Ellemiek Wintjes
3.3 Comparisons/Statistics
17
is given in appendix A.1. TomTec requires every dataset to have a stack of short axis (SAx) images and
three equiangular long axis views (a 2 chamber, 3 chamber and 4 chamber view), which means that they
are rotated over 60◦ around the LA. This LA runs through the apex and the center of the mitral valve.
Another requirement is that the number of frames in the LA images and the SA images is the same.
For the planning of the equiangular long axis views a template was used, because radial scanning is not
available on the scanner used. This template is placed on the computer screen.
The standard protocol for the MRI acquisition in this study is the following: every view has 50 phases,
the SAx stack has 12 slices which are 1 cm thick, no gap, one slice per breath hold and a FOV of 40 by
40 cm for the SAx and 2 and 3 chamber view, and 45 by 45 cm for the 4 chamber view with a matrix of
256 by 256 pixels. A B-TFE sequence was used with a SENSE body coil. The TR and TE times were
3,31 ± 0,06 ms and 1,66 ± 0,03 ms respectively for the LA views and TR=3,47 ± 0,07 ms and TE=1,74
± 0,03 ms for the SAx views. This results in cine loops containing 50 frames for the LA axis slices and
12 times 50 frames for the SAx stack.
A problem with MRI is the determination of the EDV and ESV. Because the moment of closure of
the mitral valves is difficult to determine in MRI (partial volume effects and interpolation of several cardiac cycles), the EDV is usually taken as the volume of the LV cavity in the frame just before closure of
the mitral valve, or just after the QRS peak on an ECG, or when the LV cavity is largest. For the ESV the
volume of the LV with the smallest LV cavity size is taken. In this study EDV is defined as the volume
in the first frame of the cine MRI loop. For more information see appendix A.1.2.
3.2.2
RT-3D echocardiography protocol
With RT-3D echocardiography, 9 ultrasound data sets where acquired from the test subject. The number
of frames in each dataset is different, although for the creation of the 9 data sets each time the same
settings on the iE33 ultrasound machine were used. The number of frames in each dataset is given in
table B.2. This table also shows the ES phase selected in Qlab. The ED phase is always the first phase.
The settings used were medium density and four subvolumes. For more information about these settings
see appendix A.2. The data sets were made with the subject in the lateral decubitus position and during
end-expiratory breath hold.
3.3
Comparisons/Statistics
For an easy classification of the analysis data the following system is used. Each value of the EF within
one method can be described with 4 parameters. The first parameter is the software package, the second
is the observer, the third is the analysis number and the fourth is the acquisition number. So each EF
can be classified as EFmethod (software package, observer, analysisnr, aquisitionnr). Method can be 3DE
or MRI. Acquisitionnumber nac = 1, 2, . . . , Nac with Nac = 9 for 3DE and Nac = 3 for MRI. The
software package can be Qlab or Tomtec Echo for 3DE, and Tomtec MR, CAAS SA and CAAS Manual
for MRI. Observer can be EW or JG. The analysisnumber nan = 1, 2, . . . , Nan is dependent on both
observer and software package. Table 3.1 gives an overview of Nan .
¯ indicates an average. So
A • indicates that all possible values for a specific parameter are used and EF
Echo
th
EF
(Qlab, EW, •, nac ) are all analysis of the nac acquisition done by EW in Qlab, and EFEcho (Tomtec
Echo (CAAS SA, EW, •,
echo, JG, nan , •) is the nth
an analysis of all acquisitions in Tomtec echo by JG. EF
•) means all analysis of all acquisitions by EW in CAAS SA, resulting in a total of Nac × Nan = 3 × 5 =
15 ejection fractions.
Eindhoven University of Technology
18
Materials and Methods
Table 3.1: Number of analysis done per observer on the data sets.
Nan EW JG
Qlab 10
Tomtec Echo 10
3
Tomtec MR 10
4
Caas SA
5
3
Caas Manual
5
3
¯ method (software
The SE of EF
√
package, observer, •, •) is the SD of EFmethod (software package, observer, •, •) divided by Nan × Nac .
The standard error (SE) of a given set of data is calculated with SE =
3.3.1
SD
√ .
n
Outlier test
After the analyses of the datasets all data were collected and extracted from the results files. The programs to extract the data from the different files are given in appendix D. The next step is the removal of
the outliers from EFmethod (software package, observer, •, •). This is done with the outlier tests available
in Statgraphics Centurion XV. Statgraphics is a computer program that performs and explains basic and
advanced statistical functions. One of the tests done is a Grubbs’ test which detects one outlier at a time.
This outlier is expunged from EFmethod (software package, observer, •, •) and the test is iterated until no
outliers are detected. According to [20]: ”Grubbs’ test is defined for the hypothesis:
H0 : There are no outliers in the data set
Ha : There is at least one outlier in the data set
The Grubbs’test statistic is defined as:
G=
max|Yi − Ȳ |
s
(3.1)
with Ȳ and s denoting the sample mean and standard deviation, respectively. The Grubbs’ test statistic
is the largest absolute deviation from the sample mean in units of the sample standard deviation.
For the two-sided test, the hypothesis of no outliers is rejected at significance level α if
v
u
t2α ,N −2
N − 1u
2N
t
√
G>
N − 2 + t2α ,N −2
N
(3.2)
2N
with t2α ,N −2 denoting the upper critical value of the t-distribution with N-2 degrees of freedom and a
2N
α
significance level of 2N
.”
Ellemiek Wintjes
3.3 Comparisons/Statistics
3.27
-1.66
5.50
6.15
0.41
9.76
9.76
20.00
4.85
6.31
5.70
19
Example of Grubbs outlier test. This is a list of 10 normally distributed values (µ = 5.0 and σ = 3.61) and one outlier (20) to demonstrated
the Grubbs outlier test. For the total set of 11 values the µ, or in this case Ȳ ,
α
is 6.6363 and σ is 5.67. α is taken to be 0.05. This results in 2N
≈ 0.0025.
The test statistic is
G=
max|Yi − Ȳ |
20 − 6.3636
=
= 2.40
s
5.67
(3.3)
= t20.0025,9 = (3.69)2 = 13.61
(3.4)
And
t2α
2N
,N −2
(The value of 3.69 is taken from statistic compendium [21], page 36)
This results in:
v
u
r
t2α ,N −2
N − 1u
13.61
10
2N
t
√
= 2.3395 < G = 2.40(3.5)
=√
2
N − 2 + t α ,N −2
11 9 + 13.61
N
2N
which shows that 20 is a significant outlier when α = 0.05.
3.3.2
One-way and multifactor Analysis of Variance (ANOVA) test
This subsection explains the basic one-way and multifactor Analysis of Variance (ANOVA) test. In
the next chapter the test will be further explained using the classification system given at the beginning
of this section. To determine the difference between software packages and observers and the effect of
analysis and acquisition two tests are used. The first is the Analysis of Variance (ANOVA) test. There are
several different types of ANOVA test, but the one-way and multifactor ANOVA will be used here. The
one-way ANOVA procedure is designed to construct a statistical model describing the impact of a single
categorical factor X with multiple levels on a dependent variable Y . Tests are run to determine whether
or not there are significant differences between the means an variances of Y at the q different levels of
X. The multifactor ANOVA procedure is designed to construct a statistical model describing the impact
of two or more categorical factors Xj on a dependent variable Y . The results of the test to determine
whether or not the factors X or Xj have a significant effect on the dependent variable Y , are given in
an ANOVA table. An ANOVA table of a one-way ANOVA divides the overal variability among the n
measurements into two components: a ”between group” component and a ”within group” component.
The ”between group” component measures the variability amongst the q different levels of X and the
”within group” component measures the variability within one level, qj , of X. The ANOVA table of a
multifactor divides the variability amongst the n measurements in several other components: the ”main
effects” components and a residual component. For each components five parameters are given. These
parameters are: Sum of squares, Degrees of freedom (Df), Mean square, F-ratio and P-value. Table
3.2 gives the formulas used to calculate the first 4 parameters in a one-way ANOVA. In a multifactor
ANOVA the ”between groups” formulas are used for every ”main effects” component. The F-ratio tests
the hypothesis that the mean response for all samples is the same. [20], [22]
H0 : µ1 = µ2 = . . . = µq
Ha : not all µj equal
Eindhoven University of Technology
20
Materials and Methods
If F is sufficiently large the null hypothesis is rejected. This can be determine from the P-value. If the
P-value is less than 0.01, the null hypothesis of equal means is rejected at the 1% significance level. If
the P-value is less than 0.01 not every mean has to be different from every other mean. It implies that not
all means are the same. A multiple range test can determine which means are actually different. [20],
STATGRAPHICS – Rev. 8/3/2006
[22]
Calculations
Table 3.2: Formulas used to calculated data in One Way ANOVA. j are the number of levels of the
Analysis
of Variance
component X. Ȳ is the average of Y . nj is the number of points within level j. [20], [22]
Source
Sum of Squares
Between
groups
q
D.F.
(
SS between = ∑ n j Y j − Y
j =1
Within
groups
q
nj
(
SS within = ∑ ∑ Yij − Y j
j =1 i =1
q
nj
(
SS total = ∑ ∑ Yij − Y
Total
j =1 i =1
)
2
)
2
)
Mean Square
df between = q − 1
q
(
)
df within = ∑ n j − 1
j =1
MSbetween =
SSbetween
df between
MS within =
SS within
df within
F-Ratio
F=
MSbetween
MSwithin
2
n-1
3.3.3 Multiple range test
Cochran’s Test
The test to determine which means are different is the multiple range test. The results of a multiple
range test are displayed with two tables. In the first table gives the estimated sample means in increasing
The statistic displayed is calculated by
order of magnitude. Count is the number of observations, mean is the estimated sample mean and
homogeneous groups is a graphical illustration of which means are significantly different from which
2
others, based on themax
99%sTukey
HSD test. In the multifactor ANOVA the multiple range test table shows
j
A =sigma
LS Mean and LS
q instead of Mean. The LS Mean is the estimated least squares mean and LS sigma (17)
is the estimated standards 2jerror of the least squares mean. In Homogenous groups each column of X’s
j =1
indicates a group of means,
within which there are no statistically significant differences. The second
table gives the difference between two means and identifies the ones which are significantly different.
Two means
difference if the difference ± a limit does not contain 0. The difference is
To testare
forsignificantly
statistical significance,
calculated with
( )
∑
⎛
ˆ =CY=
¯j1 −
∆j1j2
q −Y¯j2
1⎜
)⎝ 1 −AA ⎞⎟⎠
(
(3.6) (18)
with Y¯j the estimated sample mean of sample j. and the limits are calculated with
s
is compared
to an F distribution with (n/q - 1) and (n/q - 1)(q - 1) degrees of freedom.
1
1
M M Swithin (
+
)
(3.7)
nj1 nj2
Test
with Bartlett’s
M a constant
dependent on a certain procedure. In this study M = Tα/2,q,n−q with Tukey’s T .
Tukey’s method is used when the observations being tested are independent and the means are from
The distributed
statistic displayed
is calculated
by is based on a formula very similar to that of the t-test,
normally
populations.
Tukey’s test
except that it corrects for experiment-wise error rate. This means that when there multiple comparisons
q
⎡
⎤
are being made, the1probability
of making a type I error 2increases
and Tukey’s will test correct for that,
(
)
B
=
dfe
ln
MSE
−
(
n
−
)
ln
s
1
⎢
j
j ⎥
and is thus more suitable
for
multiple
comparisons
than
doing
a
number
of t-tests would be. [20], [22] (19)
C
j =1
( )
⎣
where
Ellemiek Wintjes
∑
( )⎦
21
Chapter 4
Results
In section 4.1 the results of the analysis of the raw data of this study are given. In section 4.2 the comparison between 3DE and MRI is described. Section 4.3 and section give the results of the comparison
of the 3DE and MRI software packages, respectively.
4.1
Raw data
Figure 4.1 and 4.2 give an example of the acquisition data used in the software packages. Figure 4.1 was
obtained using 3DE data and figure 4.2 using MRI data. The images are constructed in Tomtec Echo and
Tomtec MR, respectively. The order of the images is the same as the overview of the standard imaging
views in figure A.2 in appendix A.1. Left top: SAx view, right top: 4 ch view, left bottom: 2 ch view and
right bottom: 3 ch view. In figure 4.1 the heart is rotated over 180◦ , the apex is at the top and the base
at the bottom. The SAx view is made at the height of the horizontal white line with the double arrows
in the other three views. The vertical colored lines are the long axis in each of the views. The LA goes
through the apex and the center of the valve. In the 4 ch view a small part of the right ventricle is visible
at the left side of the septum, and the lateral cardiac wall is not very clearly defined possibly resulting
wrong contour detection. In 4 ch view of figure 4.2 the LV, and right ventricle (RV) can be seen. The RV
is on the right side of the LV. In the 3ch view the RV is on the left side of the LV. This has to do with the
phase encoding gradients used in the acquisition of the MRI data. In some MRI data the RV is on the left
side of the LV in the 3ch view. This has no effect on the results of the analysis.
Appendix E gives the analyses data. Each table in this appendix contains the analyses data of one
observer and one software package, EFmethod (software package, observer, •, •). So the first two tables
contain the analyses data of 10 analysis of the 9 different 3DE data sets analyzed by EW in QLab and
Tomtec, respectively. The third table contains the data of 3 analysis of the same 9 3DE analyzed by
JG in Tomtec. As stated before the first step of the data analysis is the removal of outliers. The outlier
test was performed on all EF, EDV and ESV data of one observer with one software package and one
method, EFmethod (software package, observer, •, •), EDVmethod (software package, observer, •, •) and
ESVmethod (software package, observer, •, •). If a value was identified as an outlier in either EF, EDV
or ESV, the value was removed from all three. In further analysis • means all data of a given parameter
without the outliers. Table 4.1 gives the Nan of each observer and software package and Nan × Nac
after the removal of the outliers. This table shows that no outliers were present in the Tomtec echo data,
although most analysis were done with this software. It also shows that CAAS is much more vulnerable
to outliers as 4 data points of a total of 48 were removed.
Eindhoven University of Technology
Figure 4.1: Example of 3DE data used for analysis. Made in Tomtec Echo. The order of the images
is the same as the overview of the standard imaging views in figure A.2 in appendix A.1. Left top:
SAx view, right top: 4 ch view, left bottom: 2 ch view and right bottom: 3 ch view. In the 4 ch view
the lateral cardiac wall is not very clearly defined possibly resulting in wrong contour detection.
Figure 4.2: Example of MRI data used for analysis. Reconstructed from images made in Tomtec
MR. The order of the images is the same as the overview of the standard imaging views in figure A.2
in appendix A.1. Left top: SAx view, right top: 4 ch view, left bottom: 2 ch view and right bottom:
3 ch view.
4.1 Raw data
23
Table 4.1: Nan per observer and Nan × Nac after the removal of the outliers.
Nan
Nan × Nac
EW JG EW
JG
Qlab
10
88
10
3
90
27
Tomtec Echo
Tomtec MR
10
4
30
11
5
3
15
8
Caas SA
Caas Manual
5
3
13
8
Table 4.2: Overview of the average and SD of the 3DE’s and MRI’s of the subject. The percentage
between brackets is the relative error of the SD compared to the average. The ejection fraction is
given as a fraction.
Qlab (Echo)
Tomtec (Echo)
Tomtec (MR)
Caas Semi Auto
Caas Manual
EW 0.60±0.04(6.0%) 0.52± 0.02( 4.5%) 0.67±0.01(1.3%) 0.64±0.01(1.7%) 0.64±0.01(1.2%)
JG
0.54± 0.05( 9.0%) 0.67±0.01(1.1%) 0.66±0.01(1.3%) 0.66±0.01(1.2%)
EDV(ml) EW130.9 ±7.2 (5.5%)141.3 ± 7.1 ( 5.0%)181.9 ±1.4 (0.8%)203.9 ±5.7 (2.8%)215.9 ±5.9 (2.8%)
JG
127.9 ±15.4 (12.0%)181.2 ±3.5 (1.9%)203.8 ±1.8 (0.9%)203.9 ±2.4 (1.2%)
ESV(ml) EW 52.8 ±3.9 (7.4%) 67.4 ± 3.9 ( 5.7%) 59.3 ±1.5 (2.6%) 74.1 ±1.3 (1.8%) 77.0 ±1.9 (2.4%)
JG
58.9 ± 9.5 (16.1%) 60.0 ±1.6 (2.6%) 70.0 ±1.6 (2.3%) 68.3 ±1.4 (2.0%)
EF(-)
¯ method (software package, observer, •, •), EDV
¯ method (software
Table 4.2 gives an overview of EF
method
¯
package, observer, •, •) and ESV
(software package, observer, •, •), the standard deviation (SD)
and the relative error of the SD compared to the average. Figure 4.3 gives a graphical overview of the
¯ method (software package, observer, •, •) data. This figure shows the means and the standard error
EF
¯ method (software package, observer, •, •) is the SD of EFmethod (software package,
(SE). The SE of EF
√
¯ method (software package, observer,
observer, •, •) divided by Nan × Nac . Table 4.3 gives the SE of EF
method
¯
•, •) compared to the average of the SE of EF
(software package, observer, •, nac ). This table
method
¯
shows that the SE of EF
(software package, observer, •, •) is in most cases smaller than the average
SE, and that the SE of observer JG in Tomtec 3DE is significantly larger than all others, indicating JG
has some difficulty with this software package.
¯ method (software package, observer, •, •) compared to the average SE of
Table 4.3: SE of EF
¯ method (software package, observer, •, nac ).
EF
Qlab EW
Tomtec 3DE EW
Tomtec 3DE JG
Tomtec MR EW
Tomtec MR JG
CAAS SA EW
CAAS SA JG
CAAS Manual EW
CAAS Manual JG
SE of total
0.004
0.003
0.009
0.002
0.002
0.003
0.003
0.002
0.003
Average SE
0.009
0.006
0.023
0.002
0.004
0.005
0.003
0.007
0.005
Eindhoven University of Technology
24
Results
Means and Standard Errors (internal s)
69
66
Mean
63
60
57
54
MR Caas Manual JG
MR Caas Manual EW
MR Caas Semi Auto JG
MR Caas Semi Auto EW
MR Tomtec JG
MR Tomtec EW
Echo Tomtec JG
Echo Tomtec EW
Echo Qlab EW
51
Figure 4.3: Means and standard error of EFmethod (software package, observer, •, •) ×100. The SE
is √N SD
.
×N
an
4.2
ac
Comparison between 3DE and MRI
The summary statistics and a one way ANOVA test for EF• (•, •, •, •) are shown in table 4.4. The column
¯ method (•, •, •,
Count gives the number of observations, Nac × Nan for each methode, average gives EF
•). Sum of squares is determined by the formulas given in table 3.2. For Between groups, this results in
¯
205 ∗ (EF
3DE
•
¯ (•, •, •, •))2 + 86 ∗ (EF
¯
(•, •, •, •) − EF
M RI
= 205 ∗ (0.556 − 0.587)2 + 86 ∗ (0.659 − 0.587)2 = 0.645
•
¯ (•, •, •, •))2 (4.1)
(•, •, •, •) − EF
(4.2)
Table 4.4 indicates that the average EF of 3DE is significantly different from the EF of MRI, P-value <
¯ method (software package, observer, •,
0.01. A multiple range test was performed to determine which EF
•) differs significantly from all others, based on the 99% Tukey HSD test. The results of this test are
given in table 4.5 and 4.6. Figure 4.4 gives a graphical overview of the multiple range test. These tables
and the figure show that the 3DE data differ significantly from the MRI data, the MRI EF values are
¯ MRI (software package, observer, •, •) do not differ significantly. Two samples
higher and that the EF
differ significantly if the difference ± the limit does not contain 0.
Ellemiek Wintjes
4.2 Comparison between 3DE and MRI
25
Table 4.4: Summary statistics, one way ANOVA table and Tukey 99% HSD multiple range test for
the two different methods, 3DE and MRI.
Count
Average
Standard
deviation
205
0.556
0.048
MRI
86
0.659
0.017
2.61%
0.623
0.688
0.065
Total
291
0.587
0.063
10.69%
0.464
0.688
0.224
Sum of Squares
Df
Mean Square
F-Ratio
P-Value
Between groups
0.645
1
0.645
375.74
0.000
Within groups
0.496
289
0.002
Total (Corr.)
1.141
290
Method
3DE
Coeff. of
variation
8.64%
0.464
0.664
0.2
Minimum Maximum Range
ANOVA Table for EF by Method
Source
Method: 99,0 percent Tukey HSD
Count
Mean
3DE
205
0.556
MRI
86
0.659
Contrast
Sig.
Method
3DE - MRI
Homogeneous Groups
X
X
Difference +/- Limits
*
-0.103
0.014
Table 4.5: List from Statgraphics of estimated sample means in increasing order of magnitude.
Count is the number of observations, mean is the estimated sample mean and homogeneous groups
is a graphical illustration of which means are significantly different from which others, based on the
99% Tukey HSD test. Each column of X’s indicates a group of means within which there are no
statistically significant differences.
Method: 99,0 percent Tukey HSD
Count
Homogeneous Groups
Mean
Echo Tomtec EW
90
0.522
X
Echo Tomtec JG
27
0.540
X
Echo Qlab EW
88
0.596
MR Caas Semi Auto EW
15
0.636
X
MR Caas Manual EW
13
0.643
X X
MR Caas Semi Auto JG
8
0.656
X X
MR Caas Manual JG
8
0.665
X X
MR Tomtec JG
11
0.669
X X
MR Tomtec EW
30
0.674
X
X
Eindhoven University of Technology
26
Results
Table 4.6: Differences between two samples. An asterisk is placed next to any difference that is
statistically significantly different from 0 at the 99% significance level, in other words any interval
that does not contain 0.
Difference
Sig.
Value
+/- Limits
Echo Qlab EW - Echo Tomtec EW
*
0.074
0.015
Echo Qlab EW - Echo Tomtec JG
*
0.056
0.023
Echo Qlab EW - MR Tomtec EW
*
-0.078
0.022
Echo Qlab EW - MR Tomtec JG
*
-0.073
0.033
Echo Qlab EW - MR Caas Semi Auto EW
*
-0.040
0.029
Echo Qlab EW - MR Caas Semi Auto JG
*
-0.061
0.038
Echo Qlab EW - MR Caas Manual EW
*
-0.047
0.031
Echo Qlab EW - MR Caas Manual JG
*
-0.069
0.038
-0.017
0.023
Echo Tomtec EW - MR Tomtec EW
*
-0.151
0.022
Echo Tomtec EW - MR Tomtec JG
*
-0.146
0.033
Echo Tomtec EW - MR Caas Semi Auto EW
*
-0.114
0.029
Echo Tomtec EW - MR Caas Semi Auto JG
*
-0.134
0.038
Echo Tomtec EW - MR Caas Manual EW
*
-0.121
0.031
Echo Tomtec EW - MR Caas Manual JG
*
-0.142
0.038
Echo Tomtec JG - MR Tomtec EW
*
-0.134
0.027
Echo Tomtec JG - MR Tomtec JG
*
-0.129
0.037
Echo Tomtec JG - MR Caas Semi Auto EW
*
-0.097
0.033
Echo Tomtec JG - MR Caas Semi Auto JG
*
-0.117
0.041
Echo Tomtec JG - MR Caas Manual EW
*
-0.104
0.035
Echo Tomtec JG - MR Caas Manual JG
*
-0.125
0.041
0.005
0.036
Echo Tomtec EW - Echo Tomtec JG
MR Tomtec EW - MR Tomtec JG
MR Tomtec EW - MR Caas Semi Auto EW
0.038
0.033
MR Tomtec EW - MR Caas Semi Auto JG
*
0.017
0.041
MR Tomtec EW - MR Caas Manual EW
0.031
0.034
MR Tomtec EW - MR Caas Manual JG
0.009
0.041
MR Tomtec JG - MR Caas Semi Auto EW
0.032
0.041
MR Tomtec JG - MR Caas Semi Auto JG
0.012
0.048
MR Tomtec JG - MR Caas Manual EW
0.025
0.042
MR Tomtec JG - MR Caas Manual JG
0.004
0.048
MR Caas Semi Auto EW - MR Caas Semi Auto JG
-0.020
0.045
MR Caas Semi Auto EW - MR Caas Manual EW
-0.007
0.039
MR Caas Semi Auto EW - MR Caas Manual JG
-0.028
0.045
MR Caas Semi Auto JG - MR Caas Manual EW
0.013
0.046
MR Caas Semi Auto JG - MR Caas Manual JG
-0.008
0.051
MR Caas Manual EW - MR Caas Manual JG
-0.022
0.046
Ellemiek Wintjes
4.2 Comparison between 3DE and MRI
27
Means and 99,0 Percent Tukey HSD Intervals
71
67
Mean
63
59
55
MR Caas Manual JG
MR Caas Manual EW
MR Caas Semi Auto JG
MR Caas Semi Auto EW
MR Tomtec JG
MR Tomtec EW
Echo Tomtec JG
Echo Tomtec EW
Echo Qlab EW
51
Figure 4.4: Means and 99% Tukey HSD intervals of EF data. A pair of intervals that do not overlap
indicate a statistically significant difference between the means. The y-axis shows 100*EF.
Eindhoven University of Technology
28
4.3
Results
Comparison of 3DE software packages
The outcome of the EF in 3DE depends on several different factors. These factors probably are the
software package, the observer, the analysis and the acquisition. The model used here to described these
factors is
Yi,j,k,m = EF0 + αi + βj + γk + δm + i,j,k,m
(4.3)
with EF0 the average EF in 3DE, αi the effect of the analysis software , βj the variability of the observer, γk the effect of multiple analysis and a possible learning curve, δm the noise introduced with the
acquisition of the dataset and a random error [22]. In order to determine whether or not the factors
have a significant effect on the EF, an analysis of variance (ANOVA) is performed on EF3DE (•, •, •, •).
Table 4.7 gives the ANOVA table of this test. This table shows that the acquisition, the observer and the
software package have an effect on the EF, because the p-value for these three factors is lower than 0.01.
The order of the analysis has no effect on the EF. This indicates that no learning curves is present. The
order of the acquisitions was randomized for each analysis to avoid a possible learning curve.
To determine the effect of the different 3DE software packages a multiple range test on EF3DE (•, •,
•, •) is used. Table 4.8 gives the result of this multiple range test and shows that there is a statistic
significant difference between the Qlab and the Tomtec Echo software. The differences between the acquisitions are shown in table 4.9 and figure 4.5. This table and figure show that acquisition 3 and 7 result
in a significant lower EF than acquisition 1.
To determine the interobserver variability of Tomtec Echo, a one way ANOVA is done on the Tomtec
Echo data, EF3DE (Tomtec Echo, •, •, •). The F-ratio of this test is 6.33 and the P-value 0.0133 > 0.01,
indicating that there is no difference between the observers. This is also shown with the Tukey 99%
HSD multiple range test which gives a difference of -0.017 between EW and JG with limits of 0.018.
Table 4.7: ANOVA table of 3DE data. A P-value less than 0.01 indicates that these factors have a
statistically significant effect on EF at the 99% confidence level.
Source
Sum of
Squares
Df
Mean
Square
0.238
1
0.238
F-Ratio P-Value
MAIN EFFECTS
A:Software
254.33
0.000
B:Observer
0.005
1
0.005
4.94
0.028
C:AnalysisNr
0.006
9
0.001
0.71
0.702
5.67
0.000
D:AcquisitionNr
0.043
8
0.005
RESIDUAL
0.173
185
0.001
TOTAL (CORRECTED)
0.471
204
The ANOVA test indicated that the acquisitions had an significant effect on the EF. Table 4.9 gives the
multiple range test for acquisition number and figure gives a graphical overview of these results.
Ellemiek Wintjes
4.3 Comparison of 3DE software packages
29
Table 4.8: Differences between the two software packages. The difference and interval indicate that
there is a significant difference between Qlab and Tomtec Echo at the 99% confidence interval.
Software
LS Sigma Homogeneous Groups
Count
LS Mean
Tomtec Echo
117
0.531
0.004
Qlab
88
0.604
0.005
Contrast
Sig.
Qlab - Tomtec Echo
*
X
X
Difference +/- Limits
0.073
0.012
Means and 99,0 Percent Tukey HSD Intervals
0,62
0,6
EF
0,58
0,56
0,54
0,52
1
2
3
4
5
6
7
8
9
AcquisitionNr
Figure 4.5: Means and 99% Tukey HSD intervals of 3DE EF data by Acquisition number. A pair
of intervals that do not overlap indicate a statistically significant difference between the means.
Eindhoven University of Technology
Table 4.9: Differences between the acquisitions. The differences and intervals indicate that some
acquisitions differ significantly from the others, indicate with ∗.
Method: 99,0 percent Tukey HSD
Homogeneous Groups
AcquisitionNr
Count
LS Mean
LS Sigma
3
23
0.544
0.007
X
7
23
0.548
0.007
X X
8
21
0.561
0.007
X X X
9
23
0.562
0.007
X X X
6
23
0.571
0.007
X X X
5
23
0.572
0.007
X X X
2
23
0.578
0.007
X X
4
23
0.579
0.007
X X
1
23
0.591
0.007
X
Contrast
Sig.
Difference
+/- Limits
0.013
0.033
*
0.047
0.033
1-4
0.012
0.033
1-5
0.019
0.033
1-6
0.021
0.033
0.044
0.033
1-8
0.030
0.034
1-9
0.029
0.033
1-2
1-3
1-7
2-3
*
0.034
0.033
2-4
*
-0.001
0.033
2-5
0.006
0.033
2-6
0.007
0.033
2-7
0.030
0.033
2-8
0.017
0.034
2-9
0.016
0.033
-0.035
0.033
3-5
-0.028
0.033
3-6
-0.026
0.033
3-7
-0.003
0.033
3-8
-0.017
0.034
3-9
-0.018
0.033
4-5
0.007
0.033
4-6
0.008
0.033
4-7
0.032
0.033
4-8
0.018
0.034
4-9
0.017
0.033
5-6
0.002
0.033
5-7
0.025
0.033
5-8
0.011
0.034
5-9
0.010
0.033
6-7
0.023
0.033
6-8
0.009
0.034
6-9
0.009
0.033
7-8
-0.014
0.034
7-9
-0.015
0.033
8-9
-0.001
0.034
3-4
*
4.4 Comparison of MRI software packages
4.4
31
Comparison of MRI software packages
For MRI the same model can be used as for 3DE.
Yi,j,k,m = EF0 + αi + βj + γk + δm + i,j,k,m
(4.4)
with αi the noise introduced by the analysis software , βj the variability of the observer, γk the analysis,
δm the noise introduced with the acquisition of the dataset and a random error [22]. In order to determine whether or not the factors have a significant effect on the EF, an ANOVA is performed on EFMRI (•,
•, •, •). Table 4.10 gives the ANOVA table of this analysis. This table shows that only the software and
the observer have an effect on the EF. The acquisition of the MRI’s has no effect on the EF, although
three MRI’s is not enough to determine a effect of the acquisition. A different set of data containing 6
MRI’s also indicates that the EF is not depending of the acquisition. The reason that the analysis number
does not have an effect on the EF has to do with the fact that the order of the acquisitions was randomized
for each analysis.
To determine the effect of the different MRI software packages a multiple range test is used. Table
4.11 gives the result of this multiple range test. This table shows that there is a significant difference
between Tomtec MR and CAAS at the 99% confidence interval, but no significant difference between
the two methods used in CAAS.
Table 4.10: ANOVA table of MRI data. A P-value less than 0.01 indicates that these factors have a
statistically significant effect on EF at the 99% confidence level.
Sum of
Squares
Source
Mean
Df Square
F-Ratio P-Value
MAIN EFFECTS
A:Software
0.011
2
0.006
47.88
0.000
B:Observer
0.001
1
0.001
11.72
0.001
C:AnalysisNr
0.001
9
0.000
0.49
0.8768
D:AcquisitionNr
0.001
2
0.000
2.28
0.1094
RESIDUAL
0.008
71
0.000
TOTAL (CORRECTED)
0.025
85
Table 4.11: Differences between the two software packages. The difference and interval indicate
that there is a significant difference between Tomtec MR and CAAS at the 99% confidence interval,
but no significant difference between the two methods used in CAAS.
LS Sigma Homogeneous Groups
Software
Count
LS Mean
CAAS SA
23
0.646
0.003
X
CAAS Manual
22
0.654
0.003
X
Tomtec MR
41
0.675
0.002
Contrast
Sig.
CAAS Manual - CAAS SA
X
Difference +/- Limits
0.008
0.010
CAAS Manual - Tomtec MR
*
-0.021
0.009
CAAS SA - Tomtec MR
*
-0.029
0.009
To determine the interobserver variability of Tomtec MR a one way ANOVA is done on the Tomtec
Eindhoven University of Technology
32
Results
MR data, EFMRI (Tomtec MR, •, •, •). The F-ratio of this test is 3.07 and the P-value 0.0878, indicating
that there is no difference between the observers. This is also shown with the Tukey 99% HSD multiple
range test which gives a difference of 0.005 between EW and JG with limits of 0.008.
To determine the interobserver variability of CAAS a one way ANOVA is done on the CAAS data
EFMRI (CAAS SA and CAAS Manual, •, •, •). The F-ratio of this test is 49,60 and the P-value 0.0000,
indicating that there is a significant difference between the observers. This is also shown with the Tukey
99% HSD multiple range test which gives a difference of -0.021 between EW and JG with limits of
0.008. A one way ANOVA to determine a difference between the observers was also done on the two
different CAAS methods, also showing a significant difference between the two observers.
Ellemiek Wintjes
33
Chapter 5
Discussion
The difference between the average EF of 3DE and MRI is about 16% of the average of the two methods.
This is not what was expected as explained in the literature review, see section 2.2. The difference can be
caused by two things: an actual difference between the real EF’s or a difference caused by the difference
in the analysis of the data. An actual difference between the EF’s may be caused by the difference in
position between MRI and 3DE. MRI is done with the patient laying on his/her back and 3DE with the
patient in the left lateral decubitus position, in other words laying on his/her side.
Another reason for an actual difference is a difference in heart rate between the acquisitions of the 3DE
and the MRI data. In the data used in this study the heart rate of the subject was average 5 beats per
minute higher in MRI than in 3DE.
Another actual difference in EF can occur when the MRI’s and 3DE would not be made on the same day.
In this study they are made on the same day so this factor is not expected to have an major influence.
The fact that MRI requires longer breath holds might also have an effect, because the heart will start
pumping faster to get more oxygen to the organs which has an effect on the EDV and ESV.
A difference in the EF can also be caused by, for instance, the different analysis techniques and contour detection methods. Contour detection and tracking in MRI is easier because the contrast between
blood pool and cardiac wall is clear and the wall is clearly defined, although the interpolation and partial
volume effects make it more difficult to determine the actual location of the cardiac wall. In echocardiography speckle tracking is required to perform contour tracking. No information about the actual contour
detection and tracking algorithms is acquired from the manufactures of the software packages. So it is
not clear is this technique is used in the packages analyzed in this study. As indicated in the top right
quarter of figure 4.1 the heart of the test subject seems to have a double cardiac wall which results in a
faulty detection of the contours in the 3DE software packages. But even when the contours are modified
to fit the outer wall, the EF with 3DE stays smaller then with MRI.
Another possible reason for a difference between the EF in MRI and 3DE is the contrast and visibility
of the papillary muscles. In 3DE the papillary muscles may be identified as cardiac wall because the
contrast between blood and (cardiac and papillary) muscle is small.
A third possible difference might occur from the fact that MRI cine images are not realtime, but interpolated over multiple, average about 20, heartbeats per cine image. One MRI dataset contains a minimum
of three LA and 12 SAx slices, so the EF calculated is an average of about 15 × 20 = 300 heartbeats.
One 3DE dataset is acquired in 8 heartbeats.
For this study only one test subject was used. The reasons for taking only one test subject were that
the EF differs from person to person and that MRI scanner time and analysis time were limited. It would
have been better to have two or more test subjects, because the results for variability be better validated
and the differences between the EF’s in 3DE and MRI better explained and tested.
Eindhoven University of Technology
34
Discussion
The differences between the acquisition methods of 3DE and MRI make one method more suitable
in a given situation. 3DE should be us in patients with a pacemaker, because the magnetic field or MRI
might interfere with the pacemaker. 3DE should also be used in patients with severe cardiac arrhythmias,
because the triggering of the MRI sequences results in extreme long breath holds when arrhythmias are
present. In patients with enlarge hearts or a small intercostal space, MRI is preferred, because in an
enlarged heart the LV might no fit in the 3DE pyramid and in patients with a small intercostal space the
ribs interfere with the ultrasound resulting in poor quality images.
The difference between the CAAS MRI and Tomec MR software could be caused by a difference between in- and exclusion of the papillary muscles. CAAS excludes the papillary muscles and Tomtec
normally includes them, but appears to exclude them when the papillary muscles touch the cardiac wall.
In other words, Tomtec includes papillary muscles in ED, resulting in a higher EDV than in reality, and
might often exclude them in ES, resulting in the real ESV. If the CAAS packages does the same, the
average EDV would increase with about 5 ml and the ESV would remain the same. This could result
in an higher EF for CAAS, and in no significant difference between the EF’s in CAAS and Tomtec. In
CAAS it is only possible to include the papillary muscles in both ED and ES, not only in ED, and in
Tomtec the papillary muscles cannot be defined separately. This makes it impossible to deal with the
papillary muscles in the same way in both software packages.
Qlab and Tomtec Echo are significantly different. This is probably the result of the difference in calculation and contour detection techniques. The analysis of 3DE data in Qlab is almost fully automated,
leaving very little room for manual corrections of the contour detection. Because automated contour
detection in 3DE images is more difficult than in MRI images, manual correction is often needed.
It is difficult to determine if Tomtec MR or CAAS should be used in further studies. The SE of both
packages appear to be equal so other factors like analysis time, interobserver variability, ease of use and
clinical usefulness should be used to determine which package is recommendable. The time needed in
Tomtec to analyse one dataset is significantly shorter than in CAAS. One analysis in Tomtec MR takes
about 3 minutes, in CAAS the analysis of the same dataset takes about 8 minutes for the semi-automated
method and 12 minutes for the manual method indicating that the semi-automated method should be used
in further studies. The SA method is less labor intensive than the manual method. CAAS uses short axis
based analysis and Tomtec uses long axis based analysis as do the 3DE packages. This difference might
explain the substantial difference between the results of CAAS and Tomtec. When comparing 3DE and
MRI data the same type of analysis should be used to avoid extra differences. Another advantage of
Tomtec is that it requires much less explanation and training. The interobserver variability of Tomtec
appears to be smaller, because no significant difference between the observers in Tomtec is found but
in CAAS there is a significant difference between the observers, probably caused by amount of manual
input needed for CAAS. A drawback of Tomtec is that the software is new and not yet fully clinically
validated. The CAAS software has more options besides LV function analysis which make it more useful
than Tomtec.
In this study only two observers have analyzed the data. These two observers were layman, which
means that the results of this study have to be verified for an experienced observer. More observers are
also needed to given a definitive conclusion about the interobserver variability of the different software
packages.
Ellemiek Wintjes
35
Chapter 6
Conclusions
• The overal conclusion of this study is that the EF determined with 3DE differs significantly from
the EF determined with MRI for the one test subject used in this study. The difference between the
EF of 3DE and MRI is about 16% of the average of the two methods.
• There is a significant difference in EF between the CAAS MRI software and the Tomtec MRI
software.
• The two analysis methods used in CAAS do not differ significantly.
• Qlab and Tomtec Echo are significantly different.
Eindhoven University of Technology
36
Ellemiek Wintjes
Conclusions
37
Chapter 7
Recommendations
From the results of this study, it has been shown that specific aspects of the acquisition and analysis influence the EF. To further improve measurements, several modifications and improvements are required.
7.1
Acquisitions
To improve and maintain a good quality of the acquisitions several items have to be taken into account
and possible modified. These are:
1. MRI and 3DE on same day
2. 3DE first, MRI second
3. Precise and clear 3DE acquisition protocol
4. Test if 3DE can be performed while laying on back
MRI and 3DE on same day
Preferably the MRI and 3DE examination are done on the same day, because the EF of a subject changes
from day to day. To avoid small differences between the 3DE and MRI EF it is important to keep time
interval between both examinations as small as possible and the levels of stress and activity kept ow and
equal for both examinations.
3DE first, MRI second
Performing the 3DE first may eliminated superfluous MRI examinations, because if the analysis of the
3DE data is difficult or impossible, the MRI examination will not have to be performed.
Precise and clear 3DE acquisition protocol
Currently no clear and precise 3DE acquisition protocol is available in the MMC in Veldhoven. A
protocol is required if different analysts are acquiring the different 3DE datasets. The effects of different
analysts is not tested in this study, so a separate test to identify the effect of different analysts has to be
performed. It might be useful to include a method to see whether part of the LV is blocked by a rib, like
manually rotating the transducer through all possible views.
Eindhoven University of Technology
38
Recommendations
Test if 3DE can be performed while laying on back
To eliminate real effects between the EF of MRI and 3DE a test to see if it is possible to perform 3DE
while the patient is laying on his/her back might be performed. It is impossible to perform an MRI
examination while laying in the left lateral decubitus position. This difference might have a substantial
influence and should be tested.
7.2
Analysis
To increase the reliability of the analysis the following things are important to keep in mind when designing a new study.
1. Multiple subjects
2. More observers
3. One MRI software package
Multiple subjects
Multiple subjects will increase the statistical power of the analysis, possibly resulting in a more definitive
answers on whether or not there is a difference between the EF in MRI and 3DE. To insure comparable
results, select subjects with similar cardiac pathologies and from the same age range.
More observers
For a reliable overal conclusion on the interobserver variability of different software package, multiple
observers are required. The difference between experienced and non-experienced observers has to determined. Using multiple observers requires a clear and tested analysis protocol and training in the used
software package.
One MRI software package
The effect of different software package can be substantial, indicating that only one software package
per method should be used. If Tomtec MR is selected as the MRI software package, the MRI acquisition
protocol has to be modified to meet the requirements of Tomtec MR. CAAS has are wider range of uses
and analysis methods, requiring a clear analysis protocol and adequate training. The analysis times of
CAAS are significantly higher than in Tomtec MR, indicating that if the number of analysis and test
subjects is high, Tomtec MR is a better candidate.
Ellemiek Wintjes
BIBLIOGRAPHY
39
Bibliography
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[10] E. G. Caiani, C. Corsi, J. Zamorano, L. Sugeng, P. MacEneaney, L. Weinert, R. Battani, J. L. Gutierrez, R. Koch, I de Perez, V. Mor-Avi, and R. M. Lang. Improved semiautomated quantification of
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18(12):1292–1298, 2005.
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2006.
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Kirschbaum, A. M. Anwar, T. W. Galema, W. B. Vletter, and F. J. Ten Cate. Quantification of left
ventricular volumes and function in patients with cardiomyopathies by real-time three-dimensional
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and Sons, 3th edition, 2003.
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[24] Book chapter: What is Echo? Further details unkown.
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three-dimensional echocardiography. Cardiovasc. Ultrasound, 1:12, 2003.
Eindhoven University of Technology
42
Imaging modalities
Appendix A
Imaging modalities
The left ventricle of the heart is often seen as an object with two main axes: the long and the short
axis. The long axis is defined as the line that passes through the center of the mitral valve orifice and
the left ventricular apex. In a long axis view the left ventricle has a kind of U shape. The short axis is
perpendicular to the long axis and shows a circular or elliptical cross section of the left ventricle.
A.1
Cardiac MRI
For the creation of a cardiac MRI dataset several steps are required. First a the subject has to be prepared
for a cardiac MRI study. This preparation involves placing of MRI compatible electrocardiogram (ECG)
leads, and the placement of the coil. The coil can be a special cardiac coil or a body coil. The ECG
leads are required for the gating of the acquisition as will be explained in section A.1.2. During the
next step the scanning parameters have to be set. These parameters involve the shimming plane, the
imaging planes, the slice thickness, the number of cardiac phases and several other parameters. This step
is followed by the actual scanning and storage of the acquired data.
A.1.1
Imaging planes
One of the first steps in LV function analysis MRI study is the selection of the region of interest (ROI) and
main imaging planes. The ROI is the heart and is a combination of slices through the three main planes of
the heart. These planes depict the left ventricle in three orthogonal planes: the horizontal long axis (fourchamber view), vertical long axis (two-chamber view), and short axis planes. Regularly an additional
fourth view is used: a three-chamber view or left ventricular outflow tract (LVOT). A schematic overview
of these four planes can be seen in figure A.1. [23] The process of obtaining the desired planes a complex
routine. This has to do with the fact that, in contrast to most other MRI applications, the imaging planes
used in cardiac MRI are defined with respect to the orientation of the heart. These imaging planes are
double oblique relative to the conventional axial, sagittal and coronal axes of imaging, and they differ
from subject to subject depending on the particular orientation of the left ventricle, which can vary with
respect to the body.
The actual selection of the imaging planes is done with the help of the interactive scan mode. This
routine consists of 5 steps for the three main planes and 1 additional step for the three-chamber view.
[23]
Step 1: Finding a transverse image through the left ventricle and septum. The approach starts
with routine scout images, which include standard coronal images of the chest. From this coronal view,
a transaxial image is positioned through the heart. This image depicts both left and right ventricles and
the interventricular septum.
Ellemiek Wintjes
A.1 Cardiac MRI
43
Figure A.1: Conventional imaging planes of the heart. On the left, a whole heart view depicts
the plane defining the short axis view, as shown on the right, together with the planes defining the
horizontal, vertical and three chamber long axis views. Taken from Lee [23], page 267.
Step 2: Defining a two-chamber scout from the transverse image. Based on the axial image identified in step 1, an oblique coronal slice is positioned through the left ventricle that is parallel to the
interventricular septum and passes through the left ventricular apex. This will produce a long axis view
of the heart referred to as a two-chamber scout view.
Step 3: Obtaining a short axis view from the two-chamber scout and the transverse image. In
subjects whose hearts are vertically orientated, the two chamber scout view may serve as a good vertical
long axis view. In general, for true vertical long axis, additional adjustment is needed (see Step 5).
A plane aligned perpendicular to the long axis of the heart on both the two-chamber scout view
and the original transverse image gives a short axis view. The short axis view is used for subsequent
positioning of the long axis.
Step 4: Defining a horizontal long axis view from a short axis and two-chamber scout. Using the
short axis and the two-chamber scout, the horizontal long axis (four chamber view) can be positioned
by bisecting the left ventricle in the horizontal plane. As a guide to the horizontal plane, the line should
bisect both the left and right ventricles and be parallel to the diaphragm.
Step 5: Obtaining a vertical long axis view from the horizontal long axis and short axis. Using the
horizontal long axis view (four-chamber) and the short axis view, a true vertical long axis view can be
defined by bisecting the left ventricle in the vertical plane. The resulting image shows the left ventricle,
left atrium and mitral valves.
Three-chamber view. The three-chamber view can be acquired by positioning a long axis view orthogonal to the short axis view, similar to the four-chamber view but tilted obliquely through the left
ventricular outflow tract. [23]
Eindhoven University of Technology
44
Imaging modalities
Figure A.2: Left ventricular wall regions identified on the standard imaging views. Taken from Lee
[23], page 270.
Figure A.2 gives a schematic overview of the imaging planes and an identification of the left ventricular wall regions.
A.1.2
Synchronization of acquisitions with motion
After the positioning of imaging planes the actual acquisition can start. The k-space data are typically collected across multiple heart beats. For some sequences, such as spin echo anatomic imaging
or contrast-enhanced infarct imaging, data are typically collected at the end of the cardiac cycle, when
there is minimal motion during diastole. For functional imaging, such as cine gradient echo imaging or
phase contrast flow quantification, data are collected throughout the cardiac cycle and then partitioned
into separate k-space frames. Each k-space frame corresponds to a short segment of the cardiac cycle and
reflects a snapshot of the heart during the cardiac cycle. When viewed together in a cinematic loop these
produce a beating heart video clip. In this way cine MRI enables the viewer to assess cardiac motion. [23]
To achieve optimal MR images the scanned object has to be as motionless as possible. The heart is
far from motionless and as it is located in the chest cavity it is also influenced by breathing. This results
in a modified scanning procedure which synchronizes the acquisition with cardiac and breathing motion.
Synchronization with breathing is achieved by scanning during end expiratory breath holds. Before a
Ellemiek Wintjes
A.1 Cardiac MRI
45
scan starts the subject is instructed to inhale, exhale and to suspend respiration. Because the time respiration can be suspended is normally limited to 15 to 20 seconds, the duration of a scan is limited.
Electrocardiogram
Because the k-space data are collected across several heart beats and all cardiac phases need to be imaged the acquisition has to be synchronized with cardiac motion. If this synchronization is optimal the
images produced accurately reflect the state of the heart during its different stages of contraction and
relaxation and have minimal motion artifacts. Synchronization with cardiac motion is achieved with
electrocardiographic (ECG) gating or triggering.
Gating versus triggering. The terms gating and triggering can be confusing. They are often used
interchangeably. Generally, gating refers to any means relating MR data acquisition to the phase of the
cardiac cycle during which the data were acquired. Gating can be either prospective or retrospective.
Triggering is one form of prospective gating, whereby the MR sequence is initiated with the R wave.
When the data acquisition for the given R-R interval is completed, the scanner waits for the next R wave.
Imaging that begins immediately after the R wave starts just before the onset of ventricular systole.
For some sequences diastolic images may be desired. To obtain diastolic images with R-wave triggering, a trigger delay can be introduced. This delay of at least 150-250 msec is introduced between the
detection of the R wave and the start of imaging. [23]
Retrospective gating Many ECG-gated sequences can also be performed with retrospective gating.
Retrospective gating means that the data are acquired continuously, along with a recording of the ECG
tracing. After the acquisition, the imaging data are retrospectively sorted based on the time of the echoes
relative tot the R-wave. Retrospectively gated sequences provide information about imaging through the
entire cardiac cycle, including the full duration of diastole, provided that the patient’s heart rhythm is
sufficiently regular. Compared to prospectively gated sequences, the image reconstruction of retrospectively gated sequences is more complex and computationally intensive.
With retrospective gating, the temporal spacing of the frames can be defined by the user, regardless of
the true or effective TR of the sequence.
An electrocardiogram (ECG) tracing depicts the electrical activity of the heart. A P-wave, QRS complex
and T wave are often identifiable. The P-wave represents atrial depolarization and the onset of atrial
contraction. The QRS complex reflects the electrical activity associated with ventricular depolarization
preceding systole. The onset of left ventricular systolic contraction occurs about 50 msec after the R
wave, and contraction lasts for about 150-250 msec. The T wave represents repolarization of the ventricle. Until the next QRS, the ventricle remains in diastole.
There are two main reasons why the synchronization may fail in the scanner: patient arrhythmias and
failure of the system to detect the R wave for triggering.
For ECG-triggered sequences, data acquisition assumes a regular heart rate. Following the R wave, the
system begins collecting data, portions of which are assigned to different k-space domains corresponding
to different time points in the cardiac cycle. If the heart rate is regular, then all the data collected shortly
after the R wave will reflect the left ventricle in systole, while the data toward the end of the R-R interval
will image the ventricle in diastole. If the heart rate is irregular and a second heartbeat comes much
earlier as expected, it is possible that the data collected toward the end of the acquisition window which
should correspond to diastole, will instead reflect systole. This corrupts the data as the k-space of the
images which should depict diastole now contains a mix of systolic and diastolic data. The acquisition
time in subjects with irregular heart rates is also longer than expected, because not not all heartbeats can
Eindhoven University of Technology
46
Imaging modalities
be used to collect data. Although an occasional irregular beat is tolerable, frequent irregularities cause
poor quality and misleading images. [23]
The most problematic source of artifactual triggering is due to the magnetohydrodynamic effect of moving blood within the magnetic field. Electrical charges moving through a magnetic field induce a voltage.
Blood contains many charged particles like Na+ and Cl− , among others. When these ions move through
blood vessels in the setting of a magnetic field, a voltage can be detected, particularly during systole or
the ST portion of the ECG tracing. Distortion of the ST portion and peaking or elevation of the T waves
results in faulty triggering wherever the T wave is higher than the R wave. Triggering off the T wave
means that much of systole is missed.
Vectorcardiographic (VCG) triggered or gated approaches reduce artifactual triggering from the magnetohydrodynamic effect. With VCG, the electrical activity of the heart is depicted both temporally and
spatially, using measured signal from all three leads. Because the orientation of the electrical axis of the
heart is different from the artifacts associated with the magnetohydrodynamic effect, the vectorcardiogram is more accurate at detecting cardiac activity.
Occasionally, adequate ECG tracings cannot be obtained, perhaps because of a subject’s body habitus or other interference with signal measurement, such as a large pericardial effusion. Peripheral pulse
gating is a viable alternative when central gating is not possible. Like plethysmography, peripheral pulse
gating detects the pulse wave of blood as it transits trough the fingers. Typically peripheral pulse gating
monitors are clipped to the fingertips or toes. Only MR-compatible peripheral pulse monitors should be
used. [?]
A.2
Echocardiography
A cardiac imaging modality used in this study is real-time 3D echocardiography. This technique uses
ultrasound to create 3-D moving images of the heart. Echo studies are carried out using specialized
ultrasound machines. Ultrasound of different frequencies (in adults usually 2 to 4 MHz) is transmitted
from a transducer (probe) which is placed on the subjects anterior chest wall. This is transthoracic echo
(TTE). The subject usually lies in the left lateral decubitus position and ultrasound gel is placed on the
transducer to provide good conduction. The left lateral decubitus position means that the patient is laying
on his/her left side. Continuous electrocardiograph (ECG) recording is performed to time cardiac events.
There are a number of standard positions on the chest wall for the transducer. These are echo windows or
acoustic windows that allow good penetration by ultrasound without too much masking and absorption
by lung or ribs. Figure A.3 gives an overview of the most commonly used acoustic windows.
A.2.1
Reconstructed
Reconstructed 3D echocardiography indicates that a 3D volume is generated from a set of 2D images.
These 2D images are made using one of the following techniques: freehand scanning, linear acquisition, fan-like scanning, stepwise rotational scanning or continuous rotational scanning, see figure A.4.
Freehand scanning uses a device that locates the ultrasound transducer and the imaging planes. These
devices allow free movement of the transducer at one acoustic window or at different acoustic windows.
A linear acquisition is performed by a computer-controlled movement of the ultrasound transducer in a
linear direction. With fan-like scanning a pyramidal shaped data set is obtained by moving the ultrasound
transducer in a fan-like arc at prescribed angles. In stepwise rotational scanning the transducer is rotated
around its central axis, resulting in a conical volume data set. Continuous rotational scanning is done
with an internally rotating array. The 2D data set are transformed into a 3D data set. These 3D data sets
are then used to calculated the different cardiac volumes. [25].
Ellemiek Wintjes
A.2 Echocardiography
47
Figure A.3: The main acoustic windows. [24]
A.2.2
ECG triggering
A.2.3
Real-time
In real-time 3D scanning a phased-array matrix transducer is used. In this transducer, multiple recordings are automatically performed to cover the full left ventricle [25]. The pyramidal shaped data set is
often divided into 4 different parts, each part rotated over a certain amount of degrees and made in one
heartbeat. The parts are triggered to every other R-wave on an ECG to allow recalibration of the transducer and storage of the data. One entire volume is made in a single end-expiratory breath-hold lasting
about 10 seconds. To allow for the data to be used for volume and EF analyse the 3DE has to be made
from the apical window. This ensures that the entire left ventricle is enclosed in the data set. Sometimes
ultrasound contrast is used to enhance the images acquired with 3DE. Ultrasound contrast agents are
gas-filled microbubbles that are administered intravenously to the systemic circulation.
iE33 Settings
The iE33 ultrasound machine has 3 different settings for the density in the 3D mode. The three density
levels are: Low, Medium and High. This density is related to the image resolution, or line density. The
line density sets the volume of the image displayed and the pyramidal shaped volume. The higher the
density, the smaller the volume. Other settings for the 3D mode include Full Volume Optimization (FV
Opt) Live 3D and Non-triggered Full Volume. FV Opt control enables a change in resolution of the
image to see a larger volume. The FV Opt control has three settings : Volume Size, Frame Rate and
Acq Beats. The range of these settings is dependent on the density settings. Volume Size increases the
number of acquisition beats and increases the volume size for all density settings. The highest setting is
only available when Density is set to Low and Allow Large 3D Volume Acquisition is selected. Frame
Rate increases the number of acquisition beats so that each subvolume is approximately halved, enabling
an enhancement in frame rate. Acq Beats minimizes the number of acquisition beats, decreasing the time
Eindhoven University of Technology
48Cardiovascular Ultrasound 2003, 1
Imaging modalities
http://www.cardiovascularultrasound.com/content/1/1/12
Figure 1 methods of data acquisition for transthoracic 3D-echocardiography
Different
Figure
A.4:ofDifferent
methods
of data acquisition
for transthoracic
3D-echocardiography.
Real-time
Different
methods
data acquisition
for transthoracic
3D-echocardiography.
Continuous
rotation results, unlike
stepwise
imaging
provides
a pyramidal
dataset
instantly.
Taken from
Krenning
rotational
scanning,
in a curved
shape of the
original
images. Real-time
imaging
provides[25].
a pyramidal dataset instantly.
it takes
to acquire a Full Volume. Table A.1 gives an overview
of the effects of the FV Opt settings.
static part of the transducer. The original images are transheart without the need for ECG and respiratory gating
ferred to a workstation for reconstruction of the datasets
and semi-automated analysis of the LV endocardial contours [10]. This allows rapid calculation of LV volumes,
ejection fraction and wall motion analysis. Such a special
dedicated system offers advantages for follow-up studies,
stress echocardiography and during interventional procedures (e.g. resynchronisation therapy).
Initial experience indicates that this near real-time
approach is an alternative to real-time volumetric systems
for global and regional wall motion analysis of the LV.
Real-time imaging
The ideal way of three-dimensional echocardiography is
on-line acquisition of a three-dimensional dataset of the
avoiding spatial motion artefacts.
The first real-time 3D system has been developed by Von
Ramm et al. [11] at Duke University and most experience
is with this system (Volumetric Medical Imaging). This
system makes use of a sparse matrix phased array transducer of 512 elements to scan a 60° × 60° pyramidal tissue volume using parallel processing technology which
permits the reception of 16 lines for each transmitted signal (16:1) at a rate of 17 volumes/sec with a depth of 16
cm. Image display for analysis consists of 2 independent
B-modes or 3 C-mode scans (these are cross-sections parallel to the transducer face which are displayed simultaneously in selected orientations. LV volumes are calculated
with dedicated analytic software from either a series of
parallel C-scans (short-axis views) or a series of rotated
Page 3 of 7
(page number not for citation purposes)
Ellemiek Wintjes
A.2 Echocardiography
Density
Low
Medium
High
49
Table A.1: Overview of the effects of the FV Opt settings
Effects of FV Opt Settings
Volume Size
Acquisition Beats Frame Rate
Largest volume
Large volume and Fast with large
medium
image volume
and
quality
medium
image
quality
Large volume and Medium volume Fast with medium
good image qual- and good image volume and good
ity
quality
image quality
Medium volume Small volume and Fast with small
and best image best image quality volume and best
quality
image quality
Eindhoven University of Technology
50
Tables
Appendix B
Tables
Table B.1: Overview of times used for acquisition and analysis of the data of the literature review.
Time (Minutes)
Jenkins 2007 b
Jenkins 2007 a
RT-3DE
Acquisition Analysis
20
1 to 2
10,5 ± 1
1
CMR
Acquisition Analysis
15
10
15 ± 2,5
4 to 6
Jenkins 2006
1
15 to 20
10 to 15
40 to 50
10 to 15
4
10,5 ± 1
Jenkins 2004
1
10,5 ± 1
6±2
Soliman 2007
15 ± 5
Van den
2006
Bosch
4±2
Remarks
Online RT-3DE analysis
(Qlab)
Offline RT-3DE analysis
(Tomtec)
Full volume reconstruction (Tomtec 4D analysis
version 2.0)
Multiplane interpolation
(Tomtec 4D analysis version 1.2)
17 ± 5
Table B.2: Number of frames in each 3DE of subject 1 and the ES phase selected in Qlab
Number of ES frame
Study
Qlab
frames
1
16
7
2
17
7
3
17
7
4
18
8
5
16
8
6
18
8
7
18
8
8
17
7
9
18
8
Ellemiek Wintjes
51
Appendix C
Analysis Protocol Caas MRV
The 6 MRI’s made from subject 2 were analyzed once with the four different analysis methods in CAAS
MRV. Figure C.1, figure C.2, and figure C.3 show the EF, EDV and ESV calculated with the 4 different
methods. The fully automated and automated with LA correction showed unexpected results and a
higher variability. This resulted in an analyses protocol which included the semi-automated and the
manual analyses methods.
EF
0,75
0,70
0,65
Ejection Fraction
n
0,60
Auto
Auto LA
0,55
Semi Auto
Manual
0,50
0,45
0,40
0,35
1
2
3
4
5
6
Research
Figure C.1: Ejection Fraction calculated with the 4 different methods.
Eindhoven University of Technology
52
Analysis Protocol Caas MRV
EDV
250
200
150
Volume [ml]
Auto
Auto LA
Semi Auto
Manual
100
50
0
1
2
3
4
5
6
Research
Figure C.2: End-diastolic volumes with 4 different methods.
ESV
120
100
Volume [ml]
80
Auto
Auto LA
60
Semi Auto
Manual
40
20
0
1
2
3
4
5
Research
Figure C.3: End-systolic volumes with 4 different methods.
Ellemiek Wintjes
6
53
Appendix D
Matlab files
D.1
Qlab
Combining multiple Qlab files
%File to combine data from multiple analysis in Qlab.
%Data must be saved when the volume curves are not visible.
%Save file as: measurement number and analysis number. 31.xls for third
%data set and first analysis.
clear all
close all
aantalmetingen=9; %number of measurements
aantalanalyses=10; %Number of analysis
ejectiefractie=[];
edvolume=[];
esvolume=[];
for i=1:aantalmetingen
for j=1:aantalanalyses
k=num2str(i);
l=num2str(j);
filename=strcat(k,l,’.xls’);
[ejfractie,edvol,esvol,ejfractieest,esvolest]=
Qlabdataanalyse(filename);
%function to extract data from Qlab xls file.
ejectiefractie(i,j)=ejfractie;
%measurements in rows (row 1: measurement 1, row 2: measurement 2)
%analysis in columns (column 1: first analysis)
edvolume(i,j)=edvol;
esvolume(i,j)=esvol;
ejectiefractieest(i,j)=ejfractieest; %value estimated by program
esvolumeest(i,j)=esvolest; %value estimated by program
end
end
ejectiefractie
edvolume
esvolume
ejectiefractieest
esvolumeest
xlswrite(’Qlabresultaten.xls’,ejectiefractie,’ejectionfraction’,’B1’);
%xls file with data on different tabs.
xlswrite(’Qlabresultaten.xls’,ejectiefractieest,’ejectionfraction’,’B11’);
xlswrite(’Qlabresultaten.xls’,edvolume,’end diastolic volume’,’B1’);
Eindhoven University of Technology
54
Matlab files
xlswrite(’Qlabresultaten.xls’,esvolume,’end systolic volume’,’B1’);
xlswrite(’Qlabresultaten.xls’,esvolumeest,’end systolic volume’,’B11’);
Import data from Qlab file
function[ejfractie,edvolume,esvolume,ejfractieest,esvolumeest]= Qlabdataanalyse(filename)
fid = fopen(filename, ’r’);
for k=1:500
tmp=fscanf(fid,[’%s’’%e’]);
nieuw(k,:)=cellstr(tmp);
end
fclose(fid);
strings=char(nieuw(220:260,:));
ejfractiebeginstr=str2num(strings(20,2:4));
%The value is a value containing a point. This routine make a number out of it.
ejfractieeindstr=str2num(strings(20,8:10));
ejfractiebeginstr=num2str(ejfractiebeginstr);
ejfractieeindstr=num2str(ejfractieeindstr);
ejfractiebeginstr=strcat(ejfractiebeginstr(1),ejfractiebeginstr(4));
ejfractieeindstr=strcat(ejfractieeindstr(1));
ejfractiestr=strcat(ejfractiebeginstr,’.’,ejfractieeindstr);
%punt getal maken
ejfractie=str2num(ejfractiestr);
edvolumeeindtest=str2num(strings(7,8:10));
% sum = 0 if a number cannot be made because a . is present,
%and there are 3 digits before the point.
if sum(edvolumeeindtest) == 0
%edvolume can contain 2 or 3 digits before the point.
edvolumebeginstr=str2num(strings(7,2:6));
%3 digits before point
edvolumeeindstr=str2num(strings(7,10));
edvolumebeginstr=num2str(edvolumebeginstr);
edvolumebeginstr=strcat(edvolumebeginstr(1),edvolumebeginstr(4),edvolumebeginstr(7));
else
edvolumebeginstr=str2num(strings(7,2:4)); % 2 digits before point
edvolumeeindstr=str2num(strings(7,8:10));
edvolumebeginstr=num2str(edvolumebeginstr);
edvolumebeginstr=strcat(edvolumebeginstr(1),edvolumebeginstr(4));
end
edvolumeeindstr=num2str(edvolumeeindstr); %insert point
edvolumeeindstr=strcat(edvolumeeindstr(1));
edvolumestr=strcat(edvolumebeginstr,’.’,edvolumeeindstr);
edvolume=str2num(edvolumestr);
% esvolumeeindtest=str2num(strings(33,8:10));
% if sum(esvolumeeindtest) == 0
%
esvolumebeginstr=str2num(strings(33,2:6));
%
esvolumeeindstr=str2num(strings(33,10));
%
esvolumebeginstr=num2str(esvolumebeginstr);
%
esvolumebeginstr=strcat(esvolumebeginstr(1),esvolumebeginstr(4),esvolumebeginstr(7));
% else
esvolumebeginstr=str2num(strings(33,2:4));
esvolumeeindstr=str2num(strings(33,8:10));
esvolumebeginstr=num2str(esvolumebeginstr);
esvolumebeginstr=strcat(esvolumebeginstr(1),esvolumebeginstr(4));
% end
esvolumeeindstr=num2str(esvolumeeindstr);
Ellemiek Wintjes
D.2 Tomtec
55
esvolumeeindstr=strcat(esvolumeeindstr(1));
esvolumestr=strcat(esvolumebeginstr,’.’,esvolumeeindstr);
esvolume=str2num(esvolumestr);
%-------------------------------------------------------------------------%estimated data
ejfractieestbeginstr=str2num(strings(27,2:4));
ejfractieesteindstr=str2num(strings(27,8:10));
ejfractieestbeginstr=num2str(ejfractieestbeginstr);
ejfractieesteindstr=num2str(ejfractieesteindstr);
ejfractieestbeginstr=strcat(ejfractieestbeginstr(1),ejfractieestbeginstr(4));
ejfractieesteindstr=strcat(ejfractieesteindstr(1));
ejfractieeststr=strcat(ejfractieestbeginstr,’.’,ejfractieesteindstr);
ejfractieest=str2num(ejfractieeststr);
esvolumeestbeginstr=str2num(strings(40,2:4));
esvolumeesteindstr=str2num(strings(40,8:10));
esvolumeestbeginstr=num2str(esvolumeestbeginstr);
esvolumeestbeginstr=strcat(esvolumeestbeginstr(1),esvolumeestbeginstr(4));
esvolumeesteindstr=num2str(esvolumeesteindstr);
esvolumeesteindstr=strcat(esvolumeesteindstr(1));
esvolumeeststr=strcat(esvolumeestbeginstr,’.’,esvolumeesteindstr);
esvolumeest=str2num(esvolumeeststr);
D.2
Tomtec
Combining multiple Tomtec echo files
%program to combine multiple Tomtec txt files.
clear all
close all
aantalmetingen=9; %number of data sets
aantalanalyses=3; %number of analysis
analyseset=’medium’ %name of folder
ejectiefractie=[];
edvolume=[];
esvolume=[];
for i=1:aantalmetingen
for j=1:aantalanalyses
k=num2str(i);
l=num2str(j);
filename=strcat(analyseset,’\’,k,l,’.txt’);
[ejfractie,edvol,esvol]= Tomtecdataanalyse(filename);
ejectiefractie(i,j)=ejfractie;
edvolume(i,j)=edvol;
esvolume(i,j)=esvol;
end
end
ejectiefractie
edvolume
esvolume
xlswrite(’Tomtecresultaten.xls’,ejectiefractie,’ejectionfraction’,’B1’);
xlswrite(’Tomtecresultaten.xls’,edvolume,’end diastolic volume’,’B1’);
xlswrite(’Tomtecresultaten.xls’,esvolume,’end systolic volume’,’B1’);
Eindhoven University of Technology
56
Matlab files
Import data from Tomtec echo file
%function file to extract data from tomtec txt files.
function[ejfractie edvolume esvolume]=Tomtecdataanalyse(filename)
fid = fopen(filename, ’r’);
for k=1:16
tmp=fscanf(fid,[’%s’’%e’]);
nieuw(k,:)=cellstr(tmp);
end
fclose(fid);
strings=char(nieuw);
ejfractie=str2num(strings(15,:));
edvolume=str2num(strings(7,:));
esvolume=str2num(strings(3,:));
D.3
Caas MRV
Combining multiple Caas files
%file must be saved as dataset number, analysisnumber, analysis type.
clear all
close all
aantalmetingen=3; %number of data sets
aantalanalyses=5; %number of analysis
analysetype =’1’; % 1 = semi-automatisch 2= manual
ejectiefractie=[];
edvolume=[];
esvolume=[];
for i=1:aantalmetingen
for j=1:aantalanalyses
k=num2str(i);
l=num2str(j);
filename=strcat(’resultaten\’,k,l,analysetype,’.csv’);
[ejfractie,edvol,esvol,esphase]= Caasdataanalyse(filename);
ejectiefractie(i,j)=ejfractie;
edvolume(i,j)=edvol;
esvolume(i,j)=esvol;
esphase(i,j)=esphase;
end
end
ejectiefractie
edvolume
esvolume
esphase
xlswrite(’Caasresultaten.xls’,ejectiefractie,’ejectionfraction’,’B1’);
xlswrite(’Caasresultaten.xls’,edvolume,’end diastolic volume’,’B1’);
xlswrite(’Caasresultaten.xls’,esvolume,’end systolic volume’,’B1’);
xlswrite(’Caasresultaten.xls’,esphase,’end systolic phase’,’B1’);
Import data from Caas file
function[ejfractie,edvolume,esvolume,esphase]= Caasdataanalyse(filename)
Ellemiek Wintjes
D.3 Caas MRV
57
fid = fopen(filename);
test = fscanf(fid,’%s’);
fclose(fid);
strings=[];
%empty matrix for string parts
remain=test;
%see strtoken
for k=1:100
[token, remain] = strtok(remain, ’;’);
strings=strvcat(strings,token);
end
data=strings(54:65,:); %The data are always on the same location in the file,
%in between these lines.
%esphase
esphasestr=str2num(data(3,2:4));%Make numbers out of string with phase
esphasestr=num2str(esphasestr); %make string from number (to remove extra white spaces)
esphasestr=strcat(esphasestr(1),esphasestr(4)); %To combine the digits
esphase=str2num(esphasestr);
%phase number
%ejfractie
ejfractiebeginstr=str2num(data(10,2:4));
ejfractieeindstr=str2num(data(10,8:14));
ejfractiebeginstr=num2str(ejfractiebeginstr);
ejfractieeindstr=num2str(ejfractieeindstr);
ejfractiebeginstr=strcat(ejfractiebeginstr(1),ejfractiebeginstr(4));
ejfractieeindstr=strcat(ejfractieeindstr(1),ejfractieeindstr(4),ejfractieeindstr(7),
ejfractieeindstr(10));
ejfractiestr=strcat(ejfractiebeginstr,’.’,ejfractieeindstr);
ejfractie=str2num(ejfractiestr);
%edvolume
edvolumeeindtest=str2num(data(11,8:14));
if sum(edvolumeeindtest) == 0
edvolumebeginstr=str2num(data(11,2:6));
edvolumeeindstr=str2num(data(11,10:18));
edvolumebeginstr=num2str(edvolumebeginstr);
edvolumebeginstr=strcat(edvolumebeginstr(1),edvolumebeginstr(4),edvolumebeginstr(7));
else
edvolumebeginstr=str2num(data(11,2:4));
edvolumeeindstr=str2num(data(11,8:16));
edvolumebeginstr=num2str(edvolumebeginstr);
edvolumebeginstr=strcat(edvolumebeginstr(1),edvolumebeginstr(4));
end
edvolumeeindstr=num2str(edvolumeeindstr);
edvolumeeindstr=strcat(edvolumeeindstr(1),edvolumeeindstr(4),edvolumeeindstr(7),
edvolumeeindstr(10));
edvolumestr=strcat(edvolumebeginstr,’.’,edvolumeeindstr);
edvolume=str2num(edvolumestr);
%esvolume
esvolumeeindtest=str2num(data(12,8:14));
if sum(esvolumeeindtest) == 0
esvolumebeginstr=str2num(data(12,2:6));
esvolumeeindstr=str2num(data(12,10:18));
esvolumebeginstr=num2str(esvolumebeginstr);
esvolumebeginstr=strcat(esvolumebeginstr(1),esvolumebeginstr(4),esvolumebeginstr(7));
else
esvolumebeginstr=str2num(data(12,2:4));
esvolumeeindstr=str2num(data(12,8:16));
esvolumebeginstr=num2str(esvolumebeginstr);
esvolumebeginstr=strcat(esvolumebeginstr(1),esvolumebeginstr(4));
Eindhoven University of Technology
58
Matlab files
end
esvolumeeindstr=num2str(esvolumeeindstr);
esvolumeeindstr=strcat(esvolumeeindstr(1),esvolumeeindstr(4),esvolumeeindstr(7),
esvolumeeindstr(10));
esvolumestr=strcat(esvolumebeginstr,’.’,esvolumeeindstr);
esvolume=str2num(esvolumestr);
Ellemiek Wintjes
59
Appendix E
Data
Each table in this appendix contains the analysis data of one observer and one software package. So the
first two tables contain data of 10 analyses of the 9 different 3DE data sets analyzed by EW in QLab
and Tomtec, respectively. The third table contains the data of 3 analyses of the same 9 3DE analyzed
by JG in Tomtec. On the right side of each table an average and SD of the data per 3DE is given, the
average taken over EF method (software package, observer, •, nac ), and for the EF data also the standard
error (SE) defined as √SD
. On the bottom right of each table the total average and SD and for EF SE of
N
an
EF method (software package, observer, •, •) is given. Data that are framed are outliers.
Eindhoven University of Technology
60
Data
Table E.1: subject 1: Ejection fraction, raw data
Echo Qlab Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
EW
1
2
3
4
5
6
7
8
9
10
s
SE
Echo1
0.578
0.664
0.626
0.656
0.628
0.601
0.579
0.609
0.618
0.650
0.621
0.030
0.010
Echo2
0.620
0.606
0.620
0.609
0.626
0.577
0.596
0.624
0.583
0.642
0.610
0.020
0.006
Echo3
0.623
0.558
0.604
0.540
0.582
0.583
0.627
0.584
0.530
0.595
0.583
0.032
0.010
Echo4
0.637
0.625
0.594
0.598
0.614
0.632
0.600
0.628
0.612
0.569
0.611
0.021
0.007
Echo5
0.613
0.584
0.632
0.648
0.653
0.640
0.608
0.583
0.635
0.646
0.624
0.026
0.008
Echo6
0.638
0.633
0.617
0.579
0.558
0.595
0.574
0.597
0.567
0.608
0.597
0.027
0.009
Echo7
0.536
0.554
0.584
0.584
0.525
0.539
0.559
0.510
0.549
0.571
0.551
0.024
0.008
Echo8
0.540
0.549
0.569
0.581
0.591
0.581
0.625
0.545
0.499
0.607
0.580
0.028
0.010
Echo9
0.567
0.503
0.558
0.563
0.620
0.578
0.643
0.634
0.539
0.627
0.583
0.046
0.015
Total
0.596
0.036
0.004
s
SE
Echo Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
Tomtec EW
1
2
3
4
5
6
7
8
9
10
Echo1
0.557
0.499
0.529
0.555
0.571
0.537
0.538
0.513
0.570
0.548
0.542
0.024
0.007
Echo2
0.567
0.546
0.544
0.549
0.533
0.539
0.539
0.522
0.521
0.518
0.538
0.015
0.005
Echo3
0.497
0.493
0.506
0.506
0.505
0.479
0.464
0.493
0.489
0.492
0.492
0.013
0.004
Echo4
0.522
0.490
0.551
0.529
0.503
0.501
0.508
0.523
0.543
0.506
0.518
0.019
0.006
Echo5
0.496
0.498
0.529
0.488
0.485
0.512
0.537
0.527
0.513
0.502
0.509
0.018
0.006
Echo6
0.527
0.533
0.564
0.542
0.537
0.527
0.565
0.523
0.525
0.520
0.536
0.016
0.005
Echo7
0.534
0.547
0.517
0.547
0.530
0.544
0.538
0.548
0.510
0.538
0.535
0.013
0.004
Echo8
0.529
0.517
0.518
0.509
0.535
0.517
0.492
0.571
0.482
0.502
0.517
0.025
0.008
Echo9
0.538
0.502
0.519
0.523
0.529
0.526
0.490
0.499
0.531
0.492
0.515
0.017
0.005
Total
0.522
0.023
0.002
Average
s
SE
Echo Analysis Analysis Analysis Tomtec JG
1
2
3
Echo1
0.628
0.556
0.540
0.575
0.047
0.027
Echo2
0.480
0.504
0.575
0.520
0.049
0.029
Echo3
0.495
0.492
0.531
0.506
0.021
0.012
Echo4
0.575
0.579
0.632
0.596
0.032
0.019
Echo5
0.488
0.553
0.543
0.528
0.035
0.020
Echo6
0.471
0.510
0.567
0.516
0.048
0.028
Echo7
0.471
0.515
0.492
0.493
0.022
0.013
Echo8
0.608
0.528
0.538
0.558
0.043
0.025
Echo9
0.497
0.619
0.579
0.565
0.062
0.036
0.540
0.048
0.009
s
SE
Total
MR Tomtec Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
1
2
3
4
5
6
7
8
9
10
EW
MR1
0.669
0.663
0.659
0.668
0.679
0.663
0.656
0.661
0.665
0.660
0.664
0.007
0.002
MR2
0.688
0.680
0.684
0.677
0.675
0.682
0.681
0.685
0.675
0.674
0.680
0.005
0.002
MR3
0.683
0.677
0.685
0.670
0.677
0.672
0.674
0.684
0.669
0.682
0.677
0.006
0.002
Total
0.674
0.009
0.002
Ellemiek Wintjes
61
MR Tomtec Analysis Analysis Analysis Analysis JG
1
2
3
4
Average
s
SE
MR1
0.662
0.673
0.663
0.666
0.666
0.005
0.002
MR2
0.676
0.665
0.669
0.655
0.666
0.009
0.004
MR3
0.693
0.672
0.676
0.678
Total
MR Caas Analysis Analysis Analysis Analysis Analysis Semi Auto 1
2
3
4
5
EW
0.675
0.009
0.005
0.669
0.007
0.002
Average
s
SE
MR1
0.641
0.645
0.634
0.654
0.627
0.640
0.010
0.005
MR2
0.656
0.633
0.636
0.628
0.626
0.636
0.012
0.005
MR3
0.628
0.623
0.625
0.640
0.649
Total
MR Caas Analysis Analysis Analysis Semi Auto 1
2
3
JG
0.633
0.011
0.005
0.636
0.011
0.003
Average
s
SE
MR1
0.662
0.655
0.661
0.659
0.004
0.003
MR2
0.665
0.657
0.670
0.664
0.006
0.004
MR3
0.648
0.646
0.648
0.647
0.001
0.001
0.656
0.009
0.003
Average
s
SE
Total
MR Caas Analysis Analysis Analysis Analysis Analysis Manual EW
1
2
3
4
5
MR1
0.645
0.693
0.638
0.659
0.637
0.645
0.023
0.012
MR2
0.656
0.637
0.638
0.643
0.648
0.644
0.008
0.003
MR3
0.648
0.643
0.641
0.630
0.616
0.640
0.013
0.006
0.643
0.008
0.002
Average
s
SE
Total
MR Caas Analysis Analysis Analysis Manual JG
1
2
3
MR1
0.652
0.667
0.667
0.662
0.009
0.005
MR2
0.657
0.665
0.679
0.672
0.011
0.008
MR3
0.663
0.660
0.666
Total
0.663
0.003
0.002
0.665
0.008
0.003
Eindhoven University of Technology
62
Data
Table E.2: subject 1: End-diastolic volume, raw data
Echo Qlab Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
EW
1
2
3
4
5
6
7
8
9
10
s
Echo1
125.30
136.70
133.60
133.70
131.70
137.50
132.50
135.10
127.30
132.60
132.60
3.82
Echo2
139.10
132.70
139.20
138.00
145.20
128.90
131.30
143.00
127.30
142.70
136.74
6.29
Echo3
126.90
116.40
129.80
120.80
128.90
126.80
137.70
140.00
119.60
126.00
127.29
7.46
Echo4
139.50
130.00
134.30
139.10
136.60
134.80
129.70
143.40
127.30
125.60
134.03
5.79
Echo5
131.40
133.70
126.30
140.30
133.80
133.90
137.00
125.10
134.70
140.40
133.66
5.10
Echo6
139.70
136.40
133.10
122.80
134.60
140.50
136.20
136.00
128.80
130.90
133.90
5.30
Echo7
129.50
134.90
130.20
127.70
122.10
137.40
129.40
123.30
126.60
134.90
129.60
5.01
Echo8
112.00
119.40
123.00
117.70
116.90
124.60
117.30
104.50
106.90
117.70
118.58
3.89
Echo9
127.30
123.50
125.90
122.40
127.30
123.10
137.90
137.20
131.20
135.60
129.14
5.95
Total
130.89
7.16
Echo Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
Tomtec EW
1
2
3
4
5
6
7
8
9
10
s
Echo1
141.52
126.98
141.35
162.59
145.09
134.71
131.76
137.01
143.12
133.60
139.77
9.80
Echo2
146.29
154.81
148.75
143.85
143.81
138.45
139.40
142.60
134.73
132.09
142.48
6.69
Echo3
125.28
134.93
139.96
135.77
143.62
141.66
133.77
145.09
141.98
144.03
138.61
6.16
Echo4
146.40
141.96
146.09
140.00
140.81
144.37
137.62
137.45
147.29
144.02
142.60
3.58
Echo5
124.77
128.98
141.60
138.62
136.16
151.76
143.62
141.73
142.03
142.83
139.21
7.70
Echo6
141.40
145.20
145.29
145.70
138.51
145.71
147.45
142.32
136.64
142.71
143.09
3.47
Echo7
153.71
149.18
154.08
150.29
146.77
145.69
139.37
148.54
150.81
144.54
148.30
4.43
Echo8
127.10
140.18
127.12
130.48
137.37
130.49
137.11
138.48
130.35
134.19
133.29
4.80
Echo9
145.82
148.62
134.17
143.70
144.23
138.67
147.24
152.63
138.85
146.12
144.00
5.44
Total
141.26
7.05
Average
s
Echo Analysis Analysis Analysis Tomtec JG
1
2
3
Echo1
146.89
148.56
136.33
143.93
6.63
Echo2
136.65
147.06
123.43
135.71
11.84
Echo3
122.21
111.96
129.77
121.32
8.94
Echo4
133.50
134.22
129.35
132.35
2.63
Echo5
148.50
151.89
145.80
148.73
3.05
Echo6
124.35
129.00
120.53
124.63
4.24
Echo7
124.92
136.44
128.22
129.86
5.93
Echo8
109.86
92.67
119.19
107.24
13.46
Echo9
101.83
104.30
116.59
107.57
7.90
127.93
15.40
Total
MR Tomtec Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
1
2
3
4
5
6
7
8
9
10
EW
s
MR1
181.00
180.20
178.70
184.00
183.20
179.50
182.80
180.00
182.10
182.40
181.39
1.76
MR2
182.10
180.10
181.70
181.80
181.20
183.40
181.70
182.40
181.60
182.90
181.89
0.91
MR3
183.50
180.80
183.20
180.40
180.80
184.10
183.10
181.80
182.60
182.90
182.32
1.29
Total
181.87
1.37
Ellemiek Wintjes
63
MR Tomtec Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
JG
1
2
3
4
5
6
7
8
9
10
s
MR1
177.20
182.20
186.20
184.60
182.55
3.93
MR2
178.70
181.50
181.80
177.40
179.85
2.15
MR3
175.30
177.40
179.20
186.50
181.03
4.82
181.15
3.48
Average
s
Total
MR Caas Analysis Analysis Analysis Analysis Analysis Semi Auto 1
2
3
4
5
EW
MR1
206.11
205.85
203.87
214.04
196.42
205.26
6.29
MR2
206.79
198.86
200.49
198.24
199.49
200.77
3.47
MR3
204.89
199.47
199.38
212.13
213.01
205.78
6.60
203.94
5.71
Average
s
Total
MR Caas Analysis Analysis Analysis Semi Auto 1
2
3
JG
MR1
206.59
203.91
211.80
205.25
1.90
MR2
201.26
203.47
205.89
203.54
2.32
MR3
204.34
201.89
203.22
203.15
1.23
203.82
1.81
Average
s
Total
MR Caas Analysis Analysis Analysis Analysis Analysis 2
3
4
5
Manual EW
1
MR1
215.79
219.94
214.75
229.66
219.36
219.89
6.81
MR2
219.21
211.82
218.44
203.86
216.12
213.89
6.30
MR3
219.18
211.51
213.01
214.05
217.90
Total
MR Caas Analysis Analysis Analysis Manual JG
1
2
3
214.44
3.33
215.90
5.94
Average
s
MR1
203.66
204.74
207.37
205.26
1.91
MR2
190.86
201.23
205.66
203.45
3.13
MR3
201.25
201.41
205.56
202.74
2.44
203.86
2.36
Total
Eindhoven University of Technology
64
Data
Table E.3: subject 1: End-systolic volume, raw data
Echo Qlab Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
EW
1
2
3
4
5
6
7
8
9
10
s
Echo1
52.90
45.90
49.90
46.00
48.90
54.80
55.80
52.90
48.70
46.40
50.22
3.68
Echo2
52.80
52.20
52.80
53.90
54.30
54.50
53.10
53.80
53.10
51.00
53.15
1.05
Echo3
47.80
51.50
51.40
55.60
53.80
52.90
51.30
58.20
56.10
51.10
52.97
3.03
Echo4
50.70
48.70
54.50
55.90
52.70
49.70
51.90
53.40
49.40
54.20
52.11
2.43
Echo5
50.90
55.60
46.50
49.40
46.50
48.20
53.60
52.20
49.20
49.80
50.19
2.95
Echo6
50.60
50.10
51.00
51.70
59.50
56.90
58.00
54.80
55.70
51.30
53.96
3.44
Echo7
60.10
60.20
54.10
53.10
58.00
63.30
57.00
60.40
57.10
57.90
58.12
3.05
Echo8
51.50
53.90
53.00
49.30
47.80
52.20
44.00
47.60
53.60
46.30
49.75
3.50
Echo9
55.10
61.40
55.70
53.50
48.40
52.00
49.30
50.30
60.50
50.60
53.68
4.51
Total
52.75
3.90
Echo Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
Tomtec EW
1
2
3
4
5
6
7
8
9
10
s
Echo1
62.73
63.67
66.62
72.32
62.23
62.38
60.83
66.71
61.50
60.38
63.94
3.66
Echo2
63.36
70.32
67.87
64.92
67.19
63.79
64.28
68.15
64.60
63.68
65.82
2.38
Echo3
63.03
68.46
69.16
67.10
71.07
73.84
71.74
73.61
72.59
73.17
70.38
3.45
Echo4
69.92
72.33
65.54
65.90
69.96
71.99
67.65
65.62
67.24
71.08
68.72
2.65
Echo5
62.90
64.80
66.64
70.94
70.12
74.02
66.49
67.08
69.12
71.15
68.33
3.35
Echo6
66.92
67.86
63.38
66.77
64.08
68.94
64.19
67.88
64.87
68.43
66.33
2.03
Echo7
71.57
67.59
74.35
68.11
68.99
66.37
64.40
67.20
73.87
66.76
68.92
3.30
Echo8
59.86
67.72
61.30
64.13
63.87
63.03
69.68
59.46
67.55
66.78
64.34
3.52
Echo9
67.44
73.97
64.52
68.54
67.92
65.79
75.06
76.50
65.14
74.18
69.91
4.54
Total
67.41
3.86
Average
s
Echo Analysis Analysis Analysis Tomtec JG
1
2
3
Echo1
54.65
65.93
62.75
61.11
5.81
Echo2
71.04
72.95
52.44
65.47
11.33
Echo3
61.72
56.84
60.90
59.82
2.61
Echo4
56.74
56.50
47.54
53.59
5.24
Echo5
76.04
67.83
66.57
70.14
5.14
Echo6
65.73
63.17
52.16
60.35
7.21
Echo7
66.05
66.13
65.15
65.78
0.54
Echo8
43.09
43.71
55.09
47.30
6.76
Echo9
51.21
39.70
49.08
46.66
6.12
58.91
9.46
Total
MR Tomtec Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
1
2
3
4
5
6
7
8
9
10
EW
s
MR1
59.90
60.80
60.90
61.20
58.70
60.50
62.90
61.00
61.10
62.00
60.90
1.12
MR2
56.80
57.70
57.40
58.70
58.90
58.30
57.90
57.50
59.10
59.60
58.19
0.88
MR3
58.10
58.40
57.80
59.50
58.40
60.40
59.70
57.50
60.50
58.20
58.85
1.08
Total
59.31
1.54
Ellemiek Wintjes
65
MR Tomtec Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Average
JG
1
2
3
4
5
6
7
8
9
10
s
MR1
59.90
59.50
62.80
61.70
60.98
1.55
MR2
57.90
60.70
60.10
61.30
60.00
1.48
MR3
53.80
58.10
58.10
60.10
58.77
1.15
60.02
1.58
Average
s
Total
MR Caas Analysis Analysis Analysis Analysis Analysis Semi Auto 1
2
3
4
5
EW
MR1
74.00
73.13
74.61
73.97
73.24
73.79
0.61
MR2
71.18
72.96
72.96
73.68
74.54
73.07
1.24
MR3
76.20
75.26
74.71
76.32
74.86
75.47
0.75
74.11
1.34
Average
s
Total
MR Caas Analysis Analysis Analysis Semi Auto 1
2
3
JG
MR1
69.89
70.27
71.70
70.08
0.27
MR2
67.37
69.73
68.02
68.37
1.22
MR3
71.90
71.48
71.46
71.61
0.25
70.01
1.64
Average
s
Total
MR Caas Analysis Analysis Analysis Analysis Analysis 2
3
4
5
Manual EW
1
MR1
76.59
67.62
77.71
78.20
79.71
78.05
1.30
MR2
75.48
76.86
79.03
72.78
76.16
76.06
2.26
MR3
77.18
75.53
76.52
79.17
83.66
Total
MR Caas Analysis Analysis Analysis Manual JG
1
2
3
77.10
1.54
76.99
1.86
Average
s
MR1
70.92
68.23
68.95
69.37
1.39
MR2
65.45
67.46
66.03
66.74
1.01
MR3
67.82
68.55
68.64
68.34
0.45
68.32
1.39
Total
Eindhoven University of Technology
66
Abbreviations
Appendix F
Abbreviations
3DE
AV
ECG
EDV
EF
ESV
FVR
LA
LV
SA
SAx
SD
SE
SV
RV
Ellemiek Wintjes
3D Echocardiography
Atrioventricular
Electrocardiogram
End diastolic volume
Ejection fraction
End systolic volume
Full volume reconstruction
Long axes
Left ventricle/ ventricular
Semi-automated
Short axes
Standard deviation
Standard error
Stroke volume
Right ventricle/ ventricular