Download Left ventricular PV loop estimation using 3D echo

Left ventricular PV loop estimation using
3D echo
A feasibility study to generate PV loops from 3D echo
inter- intraobserver variability analysis on end systolic and
end diastolic volumes and on calculated Emax
BMTE 07.42
F.J. van Slochteren, P.F. Grundeman, A.J. Teske, P.H.M. Bovendeerd
ABSTRACT
Objective: A non invasive method to determine myocardial contractility can be of great use in daily
clinical practice. PV loops contain contractility information. Volume and pressure measurements can be
used to generate PV loops. 3D echo can be used to determine the left ventricular volume non invasively.
During this research project invasively measured ventricular pressures are combined with non invasively
measured volumes to construct PV loops.
Methods: First a method to generate PV loops from volumes that are measured by 3D echo is developed.
The accuracy of the PV loops, and the accuracy of the contractility information that is subtracted from the
PV loops, are investigated. The results of these investigations in case of a porcine cardiac failure model
are discussed in this document.
Results: The intra observer variability of the measured volumes shows a significant reliability. The inter
observer variability of the measured volumes shows poor reliability. The range of the calculated Emax
values is too wide to represent a physiological situation.
Conclusion: PV loop generation from invasively measured pressure and 3D echo measured volumes is
possible. The quality of the obtained echo data and the volumes that result from the observer analysis
influence the outcomes significantly.
Keywords: Cardiac dysfunction, PV loop, 3D echo, ESPVR, Contractility, Inter observer variability, Intra
observer variability
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CONTENTS
Topic
page
INTRODUCTION
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METHOD
Animal model
Volume measurement
Pressure measurement
Combining the pressure and volume data sets
Emax calculation
Statistics
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RESULTS
Volume results
Pressure results
Combining the pressure and the volume data sets results
Emax calculation results
Statistical results
Volume
Emax
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DISCUSSION
Method
Animal model
Volume
Pressure
Combining the pressure and the volume data sets
Emax
Statistics
Results
Volume
Pressure
Combining the pressure and the volume data sets results
Emax
Volume statistics
Emax statistics
Considerations
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CONCLUSION
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RECOMMENDATIONS
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REFERENCES
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INTRODUCTION
Cardiac dysfunction is a disease that decreases the intrinsic force that can be delivered by a cardiac muscle
to eject blood. Cardiac dysfunction is induced by several pathologies of the heart. Cardiac ischemia and
dilation of the ventricle are a few diseases that affect the ability of the myocardium to generate force.
Inotropy (contractility) of the myocardium is a load independent measure that expresses the ability of the
cardiac muscle to generate force. It can be used to quantify cardiac (dys)function. Quantification of cardiac
dysfunction is necessary to be able to determine the most suitable treatment for a patient. The slope of the
end systolic pressure volume relation (ESPVR) of the left ventricle can be used as an estimation of the
inotropy of the left ventricle. The slope of the ESPVR is hereafter referred to as Emax. The inotropy of the
myocardium alters during exercise through neural and hormonal regulation mechanisms. During a stable
period of the patient the inotropic state of the myocardium can be assumed stable. Assessment of the Emax
during a stable phase qualifies the momentary inotropic state of the myocardium. When this is done in
different inotropic states (exercises) insight in the cardiac regulatory mechanisms can be generated. An
easy way to assess the inotropy can be of great use in daily clinical practice.
To generate insight into the inotropic state of the myocardium a few methods are clinically available. A
short overview of these methods with their pro’s and cons is given in the next section.
Emax is a parameter that represents the relation between the left ventricular pressure and volume at end
systole. When the pressure and the volume measurements are combined, a pressure volume loop (PV loop)
is generated. From a PV loop Emax can be derived. In Figure 1 a PV loop is drawn. The different methods
to assess a PV loop differ in the way LV volume is measured. Currently the left ventricular pressure is
measured invasively because there is no other method available at this time. Three different methods to
determine the left ventricular volume are discussed below.
1.
LV volume can be acquired through a Baan catheter. This Catheter is placed in the left ventricle
and uses the conductance of the blood in the ventricle to determine the amount of blood in the
ventricle. Due to its invasiveness the procedure of the Baan catheter is highly demanding for the
patient.
2.
MRI or CT can be used to acquire an image of the ventricle. The shape and size of the ventricle
can be calculated from the images. Due to the positioning in the scanner and the radiation during a
CT scan, these techniques are demanding for the patient.
3.
Echo cardiography is a non invasive technique that uses ultrasound to examine the heart.
Information about flow, size (volume), and shape can be extracted from echo data. The most
recent echo equipment can generate moving 3D images. These images contain volume and time
information of one heart cycle.
The main subject of this study is to investigate the ability to construct a PV loop from volumes that are
derived from 3D echo data, combined with invasively measured pressures.
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The accuracy of the constructed PV
loops and the factors that influence
the accuracy will be investigated as
well. In this pilot study the intraand interobserver variability of the
measured end systolic volume
(ESV) and end diastolic volume
(EDV) are investigated.
How these volumes, and the
coupling of the pressure to the
volume curves, affect the Emax of
the left ventricle is also investigated.
When the left ventricular pressure is
measured or estimated by a non
invasive method as well, a complete
non invasive method to have insight
into the inotropic state of the
myocardium is generated.
Figure 1: Theoretical PV loop
METHOD
Animal model
The 3D echo measurements are performed in a porcine model. The porcine model is subjected to a nonischemic surgical radius enlargement on the beating heart. In the pigs, the shape and radius of the LV are
altered by inserting a pericardial patch supported by a woven graft on the beating heart.
Due to the shape of a porcine thorax, a thorough trans thoracic scan of the left ventricle can not be made. A
3D oesophageal probe is not available yet. For this reason the echoes need to be acquired during the
termination phase of the pig, three months after the enlargement operation. In this phase the sternum is
almost completely removed to have full access to the heart. The echo probe can then be placed directly on
the heart. A lot of different probe positions can be tried during acquisition. A drawback of the probe
positioning directly on the heart is that it is difficult to catch the complete region of interest in the echo
window due to the small size of the echo window in the region that is near the echoprobe.
Volume measurement
The echocardiographic equipment that is used during this study is the Philips iE33. The 3D probe (X3-1)
is used. This echo probe contains 2400 elements that can send and receive ultrasound signals with a
frequency of 1.3 to 4 MHz. The frame rate is 22 Hz. Due to the fixed frame rate the volume curve of one
heart cycle at a high heart rate is represented in fewer frames than a volume curve of a ventricle beating at a
lower heart rate. A heart rate of maximal 80 beats per minute is necessary to generate a sufficient temporal
resolution. It is necessary to be able to have access to the whole heart when images are acquired directly
from the heart during the open thorax surgery. Therefore the size of the triangle shaped window where the
echo data is acquired is set to maximal. The spatial resolution decreases due to this.
A complete dataset of one heartbeat is acquired during 4 consecutive heartbeats. In each step (RR
interval) the echo beam measures ¼ of the total volume of the eventual dataset. The stepwise measuring
process is triggered on the ECG signal. To avoid interference lines it is important that the measurement
setup (probe positioning) is not changed during the measurement period. The 4 segments are added
together to make up the complete dataset of the volume that is measured. Volume information of a
complete cardiac cycle is reconstructed. The dataset is saved in a Dicom format.
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The 3D dataset that is acquired is analyzed in the quantification software Qlab 3D Advanced (version
4.2.1.). The user interface of this software is shown in figure 2. This package contains an image analysis
function through which volumes of the heart compartments can be calculated.
Figure 2: echo data representation in the Qlab 3DQ Advanced quantification software. Perpendicular long axis views (top
left and right) and short axis view (bottom left) The color of the lines that surround the images indicate the planes in the
other images. The result of the volume calculation is shown in a 3D representation (bottom right). The ECG of the four
subsequent heartbeats used for this analysis are shown at the right bottom of this image. In the column on the right the
values of the EDV, ESV, Stroke volume and Ejection fraction are presented.
Figure 3: Volume curve as calculated by the Qlab 3DQ quantification software
In the quantification software the Dicom file that contains the echodata is opened. The data can be viewed
from different viewpoints. The data can be represented in three perpendicular planes, as depicted in figure
2. In this view traces can be drawn over the endocardial borders in the perpendicular planes. For correct
processing it is important that the position of the mitral valve annulus and the apex are marked carefully.
This needs to be done for both the end systolic and end diastolic frames. The end systolic and end diastolic
frames can be recognized from analysis of the ECG signal and from analysis of the shape of the ventricle.
When both the end systolic and end diastolic trace are determined, the software automatically draws the
endocardial border in all the frames that are in between, and calculates the volumes of these frames. During
the process of drawing and optimization of the trace of the endocardial border, the quantification software
uses a knowledge database to determine the ‘most likely’ shape of the ventricle. At last the volume curve is
interpolated to obtain a smooth volume curve. The resulting volume curve is represented in figure 3.
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Pressure measurement
The left ventricular pressure is measured invasively through a miller catheter (5 French; 1.67mm). The
catheter is positioned during echo measurements to obtain good placement. The pressure is measured at a
samplerate of 383.4Hz. The pressure data is acquired by the CardiacSoft system version 3.4.1 by
Sonometrics.
For PV loop generation it is necessary to obtain pressure data of one cardiac cycle. Data from one cardiac
cycle is obtained by comparing the left ventricular and the aortic pressures. The interval between two points
where the left ventricular pressure rises over the aortic pressure is taken as one cardiac cycle. To smooth
the pressure data a 14 points convolution filter is applied. This filter sufficiently removes the measurement
noise from the signal and maintains the characteristic shape of the pressure curve.
Combining the Pressure and the Volume data sets
To obtain PV loops the pressure and the volume data during one cardiac cycle must be combined. This is
most easily done when measurements of both signals are triggered on the ECG signal and performed by the
same equipment. Unfortunately this feature did not function properly on the equipment that was used
during this project. For that reason the measurements needed to be performed on two different
measurement systems. The pressure is measured during the whole episode in which the echo measurements
are performed. In this way a normal shaped pressure curve can be chosen from the complete episode and
can be used during the PV loop generation. PV loop generation can only be done when the pressure and the
volume signals contain the same number of data points. Since the measurements of the pressure and the
volume are done at different sample frequencies, the data must be processed to level out the number of data
points. The shorter of the two signals is subjected to an interpolation algorithm to make it fit to the longer
of the two signals.
The two signals can be combined together when characteristic points of the pressure and the volume curves
are taken into account. Theoretically the pressure and volume curves can be subdivided in 4 phases. These
phases are depicted in figure 4. a: the ventricular filling phase. b: the isovolumetric contraction phase. c: the
ventricular ejection phase. d: the isovolumetric relaxation phase.
Combining the pressure and the volume
curve is done manually. Based upon the
characteristic phases of the pressure and
the volume curves a criterion is defined to
combine the pressure and the volume data.
In the criterion the focus is on the
isovolumic contraction and relaxation
phases. The most optimal PV loop is
assumed to be the PV loop when both the
isovolumic contraction and relaxation
phases are most vertical. This process is
optically optimized to obtain the most
reliable shape.
Figure 4: Theoretical relation between pressure and volume
Emax calculation
ESPVR is defined as the end systolic pressure volume relation. Emax is the slope of the ESPVR. Since
Emax is the parameter of interest, the combining of the pressure and volume curves is guided mainly by the
isovolumetric relaxation phase at end systole. The overall shape of the PV loop is another guideline to the
most optimal pressure volume coupling. The ESPVR line connects the points with the highest P/V ratio of
a series of PV loops that are drawn in different load situations of the left ventricle. Emax can be calculated
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from the fitting of a linear function through the points of maximum P/V ratio. To be able to draw this line
at least 2 PV loops must be available. In this project three load situations of the left ventricle are examined.
These are: Head up (low LV volume), Horizontal (mean LV volume) and Head down (high LV volume).
The different loads result in different positions and shapes of the PV loops.
The calculation of Emax depends highly on the coupling of the pressure and the volume curve. The error
that can be introduced by the coupling needs to be investigated. This is done by shifting the pressure curve
with respect to the volume curve. Both a forward shift of the pressure as a backward shift of the pressure
over 52 milliseconds (20 datapoints) is applied. In that case each PV loop of each volume stage has 3
versions (backward shifted, normal, and forward shifted pressure curve). The influence of this shift of the
pressure curve on the PV loop can then be investigated.
Statistics
In the process of PV loop generation and Emax calculation some major observer influences can be noticed.
The manual tracing of the endocardial wall determines the values and shape of the volume curve. The
coupling of the pressure and the volume curves determines the shape of the PV loop. Both the tracing and
the coupling influence the Emax value. To examine the influences of these observer decisions, inter- and
intra observer analysis are performed on the determined ESV and EDV and on the Emax value. An
ANOVA test is done to examine whether the influences of the observers and the coupling are significant.
The processing of the echo data to determine the EDV and ESV, and to calculate the volume curve, is
done by three observers. Each observer processes the data three times. An ANOVA test is applied to
determine the significance of the variance that is introduced by the observers. The effect of the error that is
introduced when the pressure and volume curves are coupled is investigated through a fixed shift of the
pressure curve with respect to the volume curve. Fixed shift intervals are applied on each PV loop and the
influence of this on the Emax value is calculated through an ANOVA test.
The Emax value is calculated from three PV loops and three shift intervals are applied to each PV loop.
Therefore the PV loops that are used to construct Emax are selected from a total amount of 9 PV loops. For
each repetition of an observer 3 PV loops to the power of 3 shifts (33 = 27) Emax values can be calculated.
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RESULTS
Volume results
When the echo data is processed a volume curve is acquired as depicted in figure 5. This curve is the result
of an interpolation routine. In figure 5 the volumes of all the frames are marked in the total volume curve.
The echoframes are measured with a
frequency of 22 Hz. The heart rate
during the measurement is 60 bpm.
The EDV is 80 ml and the ESV is
44 ml. The Ejection fraction is 45%.
No isovolumic phases at end systole
and end diastole can be recognized
in the volume curve.
Figure 5: interpolation of a volume curve
Pressure results
The Left ventricular pressure curve that is obtained during the echo measurement is filtered. The raw signal
and the filtered signal are represented in figure 6.
From the figure can be noticed that
both the diastolic pressure and the
systolic pressure have low values.
The diastolic pressure is
approximately 10 mmHg and the
systolic pressure is approximately
100 mmHg. The pressure range
therefore is approximately 90
mmHg. The applied convolution
filter smoothes the signal.
Figure 6: Filtered and raw pressure signal of a single heartbeat
Combining the pressure and the volume data sets results
When the pressure and the volume curves are combined, a most optimal fit is made based upon the shapes
of the pressure and the volume curves and of the shape of the PV loop. These are shown in figure 7.
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Figure 7: Relation between pressure and volume (left) and the corresponding PV loop.
When the pressure and volume curves that are presented on the left of figure 7 are combined, the PV loop on the
right hand side is obtained. It can be seen that the pressure range of 90 mmHg in the pressure curve corresponds to
the pressure range of the PV loop. The ejected volume of 36 ml in the volume curve corresponds to the ejected
volume in the PV loop as well.
The effect of the error that is introduced when the pressure and volume curves are coupled is investigated through
the shift of the pressure curve with respect to the volume curve. This is shown in figure 8.
Figure 8: Shifted pressure curves with respect to volume curve (left) and PV loop when pressure curve shifted with respect to volume curve
(right). The applied shifts are -52 ms (black) and 52 ms (red) with respect to the green curve (0 ms).
It can be noticed from figure 8 that a shift of the pressure curve over 52 ms influences the PV loop in all phases
where the pressure is not constant. The end systolic points of the PV loops and therefore also the Emax values
alter due to the applied pressure shift. This can clearly be noticed from the different positions of the upper left
corners of the PV loops that are shown at the right side of figure 8.
Emax calculation results
From at least two PV loops that are recorded at different volume loadings the ESPVR can be estimated. The slope
of the estimated ESPVR is the Emax value. This is depicted in figure 9 and 10.
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Figure 9: Emax based on three filling volumes of the left ventricle
(animal 1)
Figure 10: Emax based on two filling volumes of the left ventricle
(animal 2)
The line of ESPVR is fitted through the points at end systole according to a linear function. In figure 9 the fit
could be based on the ESPVR of three PV loops that were recorded at different volume loadings. In figure 10 the
head down loading situation prominently affects the ESPVR and Emax. It was decided to exclude this loading
situation from the algorithm to calculate ESPVR. ESPVR of animal 2 was derived from two PV loops.
Statistical results
Volume
Since the measurements are performed on two animals, the intra- and interobserver analysis are performed on two
animals independently. The outcome of the intra- and interobserver analysis are represented in Table 1 and 2.
Here the mean and standard deviation of the end diastolic and end systolic volumes are presented. An ANOVA
test is performed to indicate whether the differences between the means of the different groups are significant.
This is indicated with the p value. When a threshold of 0.05 is applied it can be stated that there is 95% confidence
that the means of the compared populations differ significantly when the p value is under 0.05. The outcomes of
the ANOVA tests of animal 1 and 2 are depicted in table 1 and 2 respectively. The p (pos) column indicates the
difference between the mean values that are measured at the different positions (head up, horizontal, head down)
The p (rep) column indicates the difference between the mean values that are measured in each repetition. This is
the intra observer reliability. The p (obs) row indicates the difference between the mean values that are measured
by each observer in each position. This is the inter observer reliability.
Observer EDV mean (sd) [ml]
ESV mean (sd) [ml]
head up
horizontal
head down p (pos)
A
60 (7)
81 (1.5)
94.5 (1.5)
<0.001
B
50 (2)
77.5 (1)
92.5 (3.5)
<0.001
C
45.5 (3.5)
72.5 (8.5)
85.5 (4)
<0.001
p (obs)
0.025
0.184
p (rep)
head up
horizontal
head down p (pos)
0.945
42 (9)
43 (3)
47 (1.5)
0.534
0.995
28 (1.5)
36 (0.5)
39 (1)
<0.001
0.946
0.827
27 (3.5)
36 (1.5)
38 (3)
0.004
0.881
0.043
0.029
0.004
Table 1: Mean EDV and ESV at different positions measured by different observers (animal 1)
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0.002
p (rep)
0.194
Observer EDV mean (sd) [ml]
ESV mean (sd) [ml]
head up
horizontal
head down p (pos)
A
76 (6)
121 (1.5)
129.5 (1)
<0.001
0.987
B
65.5 (0)
101 (0)
113.5 (0.5)
<0.001
1
C
75.5 (3.5)
108 (3)
117 (6.5)
<0.001
0.95
p (obs)
0.032
<0.001
p (rep)
head up
horizontal
head down p (pos)
47 (2.5)
71.5 (1.5)
81 (3)
<0.001
0.996
45 (2)
63.5 (0.5)
69 (3)
<0.001
0.996
46 (2.5)
59 (2.5)
60 (8.5)
0.031
0.673
0.005
0.1
<0.001
p (rep)
0.009
Table 2: Mean EDV and ESV at different positions measured by different observers (animal 2)
The EDV and ESV values are also represented in the box plots of figure 11. Here the mean values of the three
observers are presented in the boxes. The volume is placed along the vertical axis, and the different positions are
placed along the horizontal axis. EDV is depicted in blue and ESV is depicted in green. The difference between
EDV and ESV in the different positions can clearly be seen. The difference between animal 1 and animal 2 can
also be seen when the figures on the left and the right side are compared.
EDV
ESV
100
EDV
ESV
140
120
Volume [ml]
Volume [ml]
80
60
100
80
40
60
20
40
Head up
Horizontal
Head down
Head up
Position
Horizontal
Head down
Position
Figure 11: The mean EDV and ESV of the different observers are represented in the boxes. Animal 1 is depicted in the boxplot on the left
and Animal 2 is depicted in the boxplot on the right.
Emax
The influences of the observers on the calculated Emax value is determined by an ANOVA test. The influences of
the observers through the volume measurements and the influences of the coupling through a shift parameter are
indicated. The results of this analysis are presented in Table 3 and 4.
Observer Emax mean (sd) [mmHg/ml]
Emax mean (sd) [mmHg/ml]
no shift
min
max
A
5.5 (3)
2.5 (0.5)
30 (33)
B
3 (0.5)
2 (0.5)
C
4.5 (1.5)
2 (1)
p (obs)
0.289
0.388
p (shift)
no shift
min
max
0.239
2. (0.5)
1.5 (0)
3 (1)
0.014
5 (0.5)
<0.001
2.5 (0.5)
1.5 (0.5)
3.5 (1.5)
0.095
10.5 (7)
0.119
4 (1)
2.4 (0.5)
12 (10)
0.164
0.323
Table 3: Mean Emax value by different observers (no shift).
Mean minimal (min) and maximal (max) Emax value when shift
is applied. Animal 1.
0.054
0.038
P (shift)
0.19
Table 4: Mean Emax value by different observers (no shift).
Mean minimal (min) and maximal (max) Emax value when
shift is applied. Animal 2.
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The mean and standard deviation of the Emax values that are calculated from the PV loops when no shift of the
pressure curve with respect to the volume curve is applied, are presented in the ‘no shift’ column. In the ‘min’
column the mean and standard deviation of the smallest Emax values that are calculated when the shift of the
pressure curve is applied, are presented. In the ‘max’ column the mean and standard deviation of the largest Emax
values that are calculated when the shift of the pressure curve is applied, are presented. The largest and the
smallest Emax values are selected from a total amount of 81 Emax values. 3 repetitions of each observer times 27
Emax values.
The p (shift) column of table 3 and 4 indicates the possibility that the mean Emax value that is presented in the
columns ‘no shift’, ‘min’ en ‘max’ differ significantly. The p (obs) row indicates the possibility that the mean
Emax value of the observers differ significantly.
DISCUSSION
Method
Animal model
The measurements that are used for this project are acquired from an anti dor batista animal model. Due to the
irregular shape of the ventricle it was expected that measurement of the PV relation by means of a conductance
catheter would give unreliable results. An alternative method was found in the PV loop measurement through 3D
echo derived volumes. The analysis of the echo data and the calculation of the volumes was a difficult and time
consuming task. Out of 4 animals that were subject of study the echo data of 2 animals was suitable to be used for
further processing. The use of a pathological porcine model for this study is not obvious, but it meets the
requirements to study the measurement principles. Since no measurements are performed that can be used for
comparison it is impossible to draw any quantitative conclusions from the outcome of this project.
Volume
The Volume measurements and analysis are done on the Philips iE33 and Qlab software. This equipment is used
because this is the only equipment that has the 3D volume measurement options, and that is clinically available.
The measurements are performed according to the guidelines that were given by the manufacturer. Due to the use
of a pathological animal model for this research, accurate tracing of the endocardial borders is difficult. The
implemented knowledge database is not suitable for these irregular shapes. Due to this the defining of the EDV
and ESV was a very time consuming task.
Pressure
Since the left ventricular pressure can not be measured non invasively at this moment, this pressure is measured
invasively during the surgery. More signals are measured during the surgery: ECG, right ventricular pressure,
aortic pressure, right atrial pressure, aortic flow. The left ventricular pressure of one cardiac cycle is necessary to
draw a PV loop. Since the surgery caused tremendous effect on the physiology of the heart, it is not chosen to use
the ECG signal as a trigger for the cardiac cycle. A left ventricular pressure cycle is determined from the points
where the left ventricular pressure rises over the aortic pressure. To distinguish the effects of noise, the pressure
signals are appropriately filtered with a convolution filter. The results of this are depicted in figure 6.
Combining the pressure and the volume data sets
To be able to couple the pressure and the volume data, the signals that ought to match must have the same lengths.
Due to the different measurement frequencies and post processing the signals differ in length. Equalizing the
lengths is done through the appliance of an interpolation algorithm to the shortest signal. It is chosen to lengthen
the shortest in stead of shortening of the longest to avoid spilling of the data. To process the short volume curves
that are measured during a high heart rate reliably, it is inevitable to lengthen the shortest signal.
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Emax
The ESPVR can only be drawn when at least two PV loops with different loadings are available. It is chosen to
use three maneuvers with the operation table to influence the loading of the ventricle. When the head up position
is applied, the loading reduces. When the table is horizontal the loading is at a baseline level. When the head
down position is applied, the loading increases. It appears that these maneuvers influence the loading sufficiently
to obtain distinguishable PV loops. The Emax value is the slope of the ESPVR. To draw the ESPVR a linear fit is
used. It can be noticed from figures 9 and 10 that this fitting algorithm works appropriate.
Statistics
To be able to quantify the results of the measurements an inter and intra observer analysis was done on the EDV
and ESV. These volumes were used because they are directly determined by the observers in the post processing
of the echo data. An ANOVA test is applied because the influence of the observers, positions and repetitions can
be accounted for directly in terms of significance. Three observers and three repetitive observations were used
because that limits the amount of time necessary for the analysis, and gives sufficient amount of data to use for an
ANOVA test.
The sensitivity of the Emax for the shift of the pressure curve is investigated through an ANOVA test. The
influence of the observers on Emax is determined as well as the sensitivity of the Emax for a shift of the pressure
curve. The shift of the pressure curve is investigated through the appliance of a fixed pressure shift of +/- 52ms.
This corresponds to 20 samples. This value is used because within this range the appearance of the PV loop is still
within a physiological range.
Results
Volume
The theoretically expected shape of the volume curve with isovolumic contraction and relaxation phases can not
be recognized clearly in the acquired volume curve in figures 3 and 5. The isovolumic contraction and relaxation
phases are either not measured because the frame rate at which the images are acquired is too low, or these phases
are leveled out by the smoothening that is caused by the interpolation of the volume curve. The applied
interpolation algorithm is unknown and a thorough investigation of this is beyond the scope of this project. The
echo measurements are triggered on the ECG signal, therefore it is assumed that a complete cardiac cycle is
measured and no phases are missed.
Pressure
The results of the pressure measurement are shown in figure 6. The applied 14 points convolution filter reduces
the noise of the pressure signals sufficiently. The choice for a 14 points convolution filter is a compromise
between optimal elimination of noise and maintaining the shape of the pressure signal. Since this filter does not
affect the pressure signals negatively it is a defensible choice.
Combining the pressure and the volume data sets
In figure 7 and 8 the final results of the combining of the pressure and the volume datasets are depicted. The
drawn PV loops all show a discontinuity in the isovolumic contraction phase. This is caused by the volume curve.
The value of the first frame of the volume curve and the last frame of the volume curve are different. This
irregularity always is visible in the isovolumic contraction phase because the volume curve starts with a manually
determined EDV and ends with an automatically determined EDV. The quantification software determines the
endocardial border of the second EDV without consideration of the manually determined endocardial border of
the first EDV. During the appliance of the pressure shift the position of the volume step is maintained in the
isovolumic contraction phase to ensure a physiological shape of the PV loop.
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Emax
The results of the Emax calculation of animal 1 and 2 are discussed independently. Representative PV loops of
one observer are used to discuss the results of the Emax calculation.
The results of the Emax calculation of animal 1 are depicted in figure 9. Here three PV loops are drawn that
correspond to the different preload situations of the left ventricle (head up, horizontal, head down). The change in
preload primarily causes a change in EDV. The Frank Starling mechanism causes a larger myofiber stress
development and consequently a higher pressure. This can be noticed from the change of the end systolic
pressures of the PV loops in figure 9. The Frank Starling mechanism functions properly in case of animal 1. A
representative ESPVR and Emax value can be determined in this situation.
The results of the Emax calculation of animal 2 are depicted in figure 10. The effects of the preload change of the
ventricle can be recognized from the change of the EDV. In this case the Frank Starling mechanism works
sufficiently to increase the pressure when the position is changed from head up to horizontal. When the position is
changed to head down, the preload is increased more and an increase of the pressure is expected. In this case the
pressure does not increase sufficiently. This is depicted in figure 10 by the red PV loop. It is chosen to leave this
non responding situation out of the Emax calculation because it has a major and instable influence on the Emax
value. This is not desirable in the statistical analysis of the Emax value.
Volume statistics
The results of the inter and intra observer analysis is represented in table 1 and 2. Here the mean and standard
deviation of the EDV and ESV are presented. Because only three measurements are used to determine the mean
and standard deviation of the samples, this is not a very reliable estimation for the characteristics of the
population. Because three measurements are used, the standard deviation is an indication of the range of the
values that are used to calculate the mean. The ANOVA test which is applied, defines the significance of the
difference between mean values of groups. For this reason the mean and standard deviation are represented in the
tables.
The statistical analysis of animal 1 and animal 2 is done identically. The results will be discussed at once. The
reliability interval is chosen 95%. It than can be stated that p values >0.05 indicate that there is a 95% chance that
mean values of the examined groups are significantly the same. When the p value <0.05 there is a 95 % chance
that the mean values of the examined differ significantly.
In the p (pos) column of table 1 and 2 the results of an ‘interposition’ ANOVA test are represented. During this
test each position is considered a group. The p value therefore indicates the difference between the mean values of
each position. It shows that in most cases there is a 95% chance that there is significant difference between the
mean values of head up, horizontal and head down. For the case where p (pos) >0.05 it can be noticed that the
mean values of each position are comparable.
In the p (rep) column of table 1 and 2, the results of an ‘intra observer’ ANOVA test are represented. During this
test each repetition is considered a group. The p value therefore indicates the difference between the mean values
of the consecutive repetitions. The nth measurement at head up, horizontal and head down, form a group. Since the
differences between the means of the measurements at different positions are significant, in the most cases, (p
(pos) <0.05), the difference of the means of the repetitions gives insight in the consistence of an observer to
examine the data. It shows that in all cases the p (rep) >0.05. There for it can be stated that there is a 95% chance
that there is no significant difference between the mean values of the consecutive examinations of one observer. It
needs to be taken into account that the examinations of one observer are done within subsequent hours. It is
empirically noticed that spreading the analysis of the data over subsequent days increases the intra observer
variability.
In the p (obs) row of table 1 and 2, the results of an ‘inter observer’ ANOVA test are represented. During this test
the measurements at each position is considered a group. The p value indicates the difference between the mean
values of each observer at a position. In the cases where p <0.05 it can be stated that there is 95% chance that the
mean value of each observer differs significantly from the other observers. In the cases where p>0.05 there is a
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95% chance that the mean value of each observer does not differ significantly from the other observers. Both
situations can be recognized in table 1 and 2. This means that the difference between the assessments of different
observers depend on the case that is being examined. It must be taken into account that the observers that have
contributed to this research have different experience levels. This enhances the inter observer variability. Another
factor that can enhance the inter observer variability is the noise that is available on the echo data. This has a
major influence on the tracing of the endocardial wall.
The figures that are found in literature about intra and inter observer analysis on EDV and ESV values that are
determined by means of 3D echo (Baker et al.) can not be compared unambiguously to this study. The available
figures are all from measurements on patients that suffer from a congenital heart disease, and another method than
ANOVA is used to do the statistical analysis.
Emax statistics
The results of the ANOVA test that is applied to assess the observer influence on the calculated Emax values are
noted in table 3 and 4. The mean and the standard deviation of normal (no shift), minimal, and maximal Emax
values are presented. The mean values are calculated from three measurements. Therefore these values do not
represent the characteristics of the population. This is done nevertheless because the ANOVA test makes use of
the mean value of a group.
For the statistical analysis the same technique and reliability interval as for the volume statistics are applied. The
analysis of animal 1 and animal 2 are done identical. The results will be discussed at once.
The p (shift) column of table 3 and 4 the results of an ‘inter shift’ ANOVA test are presented. p (shift) indicates
the differences between the mean Emax values in the columns: ‘no shift’, ‘min’ and ‘max’. The calculated Emax
values in each column are considered a group. It can be seen that p (shift) values >0.05 and <0.05 both appear for
both animals. p (shift) >0.05 indicates the situations where there is a 95% chance that the mean ‘no shift’, ‘min’
and ‘max’ Emax values are not significantly different. p (shift) <0.05 indicates the situations where there is a 95%
chance that the mean ‘no shift’, ‘min’ and ‘max’ Emax values significantly differ. It shows that in these situations
the Emax values are spreaded more widely. A possible explanation for this is that there is no clear border between
the groups, and that there for no significant difference between the groups can be detected.
In the p (obs) row of table 3 and 4, the results of an ‘inter observer’ ANOVA test are presented. During this test
the mean ‘no shift’, ‘min’, and ‘max’ Emax values are considered a group. The p (obs) value indicates the
difference between the mean values of each observer in each column. In the cases where p <0.05 it can be stated
that there is 95% chance that the mean value of each observer differs significantly from the other observers. In the
cases where p>0.05 there is a 95% chance that the mean value of each observer does not differ significantly from
the other observers. Despite one case, all p (obs) values are >0.05. This means that there is a 95% chance that
there is no significant difference between the mean values of the observers. It is plausible that this is caused by the
absence of a clear border between the groups.
These observation need to be considered more thoroughly. From the analysis that is performed it occurs that the
Emax value does not differ significantly between the observers and does not differ significantly when a shift of
the pressure curve is applied. This was not expected.
Normal human Emax values are 4.35 ± 1.81 [mmHg/ml] (Starling et al). A slight change of Emax is the result of
a considerable physiological change of the contractility of the myocard. The mean Emax values that are calculated
are in the physiological range (‘no shift’ column in table 3 and 4). When the standard deviation is taken into
account, the Emax values represent completely different myocardial contractility conditions. The Emax range is
[1.03 – 8.85]. Measurements are performed during one contractile state. This error must be due to intra observer
variability of the calculated EDV and ESV. It is proven that there is no significant difference between the mean
values of the consecutive examinations of one observer, still the standard deviation of this quantity is too large to
be able to derive an unambiguous Emax.
It can be concluded that the ANOVA test is not able to appoint the non physiological variance of the Emax as
significant because there is no clear distinction between the examined groups. The intra observer variability of the
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calculated volumes appears to be too high to calculate a physiological reliable Emax value. No conclusions can be
drawn from the inter observer variability investigation. This can not be investigated reliably due to the high intra
observer variability.
Considerations
No comparable research topics have been found in the online publication databases. The construction of a PV loop
from 3D echo measurements and invasively measured pressure is proven to be possible. Due to the pathological
animal model that is subjected during this study, no comparison measurements could be done. To be able to draw
quantitative conclusions, a comparison study must be performed. This can for example be done through the use of
two volume measurement methods. This can either be done through MRI or CT images. When a conductance
catheter is used as a comparison, it needs to be taken into account that the measurements are performed properly.
To be able to obtain a PV loop completely non invasively, the left ventricular pressure must be estimated non
invasively as well. For Emax estimation only the systolic part of the PV loop is necessary. A good estimation of
the systolic left ventricular pressure suffices to calculate Emax. There are clinically available measurement
devices that can do this estimation from the pressure that is measured in the finger. Application of these devices
can be a next step towards the acquiring of Emax through non invasive measurements.
CONCLUSION
Emax is an important parameter in the diagnosis of cardiac dysfunction. Non invasive calculation of Emax can
become an important diagnostic tool. If it would be possible to construct accurate PV loops using volumes that
are determined by 3D echocardiography, Emax could be calculated from these PV loops. Then a non invasive
method to calculate Emax is available.
In this project it was discovered that the inter observer variability of the calculated EDV and ESV is significant.
The intra observer variability of the calculated EDV and ESV is not significant. Since the range of the determined
EDV and ESV values results in a large range of Emax values that is not physiological, it needs to be concluded
that the volume measurements are not sufficiently accurate. Possible solutions for this are in the discussion part.
The influence of the coupling of the pressure data to the volume data is investigated by means of a shift that is
applied to the pressure curve. Due to the wide range of Emax values that were found, significance of the
difference that is caused by the shift of the pressure curve can not be diagnosed. More thorough investigation
towards these factors needs to be done.
RECOMMENDATIONS
The differences between the mean values of the consecutive examinations of one observer are proven to be too
large to use for Emax estimation. To decrease this variability, recommendations are done:
Further research needs to be performed on healthy porcine or healthy human subjects. Then it is more likely that
the knowledge database that is used to determine the endocardial border works properly.
The experience levels of the observers should be higher and more corresponding. Then inter and intra observer
variability can both be improved.
The error that is introduced during the manual coupling of the pressure and the volume data can be eliminated
when the coupling of the pressure and volume data is triggered on the ECG.
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REFERENCES
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Weber, Peter Ewert, Eckard Fleck, Eike Nagel, Ingram Schulz-Neick, Peter Lang; Magnetic Resonance Imaging
Analysis of Right Ventricular Pressure-Volume Loops. In Vivo Validation and Clinical Application in Patients
With Pulmonary Hypertension, Circulation , 2004.
Mark R. Starling, Milton D. Gross, Richard A. Walsh, Louis J. Dell’Italia, Daniel G. Montgomery, Sheila
A. Squicciarini, Ralph Blumhardt; Assesement of the Radionuclide Angiographic Left Ventricular Maximum
Time-Varying Elastance Calculation in Man, Journal of Nuclear Medicine 1988.
George Baker, MD, English Flack, MS, Anthony Hlavacek, MD, Karen Chessa, RDCS, Dawn Flemming,
RDCS, Mark Scheurer, MD, Girish Shirali, MBBS; Variability and Resource Utilisation of Bedside Threedimensional Echographic Quantitative Measurements of Left Ventricular Volume in Congenital Heart Disease,
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Richard
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Klabunde,
(http://www.cvphysiology.com/index.html)
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Guyton, A.C., Hall, J.E.; Textbook of Medical Physiology
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Physiology
Concepts
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