Left ventricular PV loop estimation using 3D echo

Transcription

1 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 F.J. van Slochteren, P.F. Grundeman, A.J. Teske, P.H.M. Bovendeerd

2 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 2

3 CONTENTS Topic page INTRODUCTION 4 METHOD 5 Animal model 5 Volume measurement 5 Pressure measurement 7 Combining the pressure and volume data sets 7 Emax calculation 7 Statistics 8 RESULTS 9 Volume results 9 Pressure results 9 Combining the pressure and the volume data sets results 9 Emax calculation results 10 Statistical results 11 Volume 11 Emax 12 DISCUSSION 13 Method 13 Animal model 13 Volume 13 Pressure 13 Combining the pressure and the volume data sets 13 Emax 14 Statistics 14 Results 14 Volume 14 Pressure 14 Combining the pressure and the volume data sets results 14 Emax 15 Volume statistics 15 Emax statistics 16 Considerations 17 CONCLUSION 17 RECOMMENDATIONS 17 REFERENCES 18 3

4 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. 4

5 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. Figure 1: Theoretical PV loop 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. 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. 5

6 The 3D dataset that is acquired is analyzed in the quantification software Qlab 3D Advanced (version ). 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. 6

7 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 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. Figure 4: Theoretical relation between pressure and volume 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. 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 7

8 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 (3 3 = 27) Emax values can be calculated. 8

9 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. 9

10 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

11 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 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) p (rep) head up horizontal head down p (pos) p (rep) A 60 (7) 81 (1.5) 94.5 (1.5) < (9) 43 (3) 47 (1.5) B 50 (2) 77.5 (1) 92.5 (3.5) < (1.5) 36 (0.5) 39 (1) < C 45.5 (3.5) 72.5 (8.5) 85.5 (4) < (3.5) 36 (1.5) 38 (3) p (obs) Table 1: Mean EDV and ESV at different positions measured by different observers (animal 1) 11

12 Observer EDV mean (sd) [ml] ESV mean (sd) [ml] head up horizontal head down p (pos) p (rep) head up horizontal head down p (pos) p (rep) A 76 (6) 121 (1.5) (1) < (2.5) 71.5 (1.5) 81 (3) < B 65.5 (0) 101 (0) (0.5) < (2) 63.5 (0.5) 69 (3) < C 75.5 (3.5) 108 (3) 117 (6.5) < (2.5) 59 (2.5) 60 (8.5) p (obs) < < 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. 100 EDV ESV 140 EDV ESV Volume [ml] 60 Volume [ml] Head up Horizontal Position Head down Head up Horizontal Position Head down 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 p (shift) no shift min max P (shift) A 5.5 (3) 2.5 (0.5) 30 (33) (0.5) 1.5 (0) 3 (1) B 3 (0.5) 2 (0.5) 5 (0.5) < (0.5) 1.5 (0.5) 3.5 (1.5) C 4.5 (1.5) 2 (1) 10.5 (7) (1) 2.4 (0.5) 12 (10) p (obs) Table 3: Mean Emax value by different observers (no shift). Mean minimal (min) and maximal (max) Emax value when shift is applied. Animal 1. Table 4: Mean Emax value by different observers (no shift). Mean minimal (min) and maximal (max) Emax value when shift is applied. Animal 2. 12

13 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. 13

14 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. 14

15 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 n th 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 15

16 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 [ ]. 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 16

17 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. 17

18 REFERENCES Titus Kuehne, Sevim Yilmaz, Paul Steendijk, Philip Moore, Maarten Groenink, Maythem Saaed, Olivier 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, 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 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, Congenital Hart Disease November/December Richard E. Klabunde, Cardiovascular Physiology Concepts website ( Guyton, A.C., Hall, J.E.; Textbook of Medical Physiology 18