Biomed Tech 2011; 56 (Suppl. 1) © 2011 by Walter de Gruyter • Berlin • Boston. DOI 10.1515/BMT.2011.481
Influence of endocardial catheter contact on properties of the atrial signal and comparison with simulated electrograms Stefan Ponto, Christopher Schilling, Martin W. Krueger, Frank M. Weber, Gunnar Seemann, Olaf Doessel Karlsruhe Institute of Technology (KIT), Institute of Biomedical Engineering, Karlsruhe, Germany
[email protected]
Abstract In spite of the considerable medical and technical progress during the last years, catheter ablation of atrial fibrillation is still challenging. For a successful execution of the ablation and the avoidance of intricacies the catheter must be in contact with the endocardium, which is still difficult to assure with existent techniques. It would be desirable to detect the endocardial catheter contact directly from the signal shape and its properties. In this work, significant signal property changes were detected and investigated, which allow an automatic contact detection. Furthermore, atrial electrograms were simulated and compared with a database of measured and annotated signals. During these simulations, the distance between endocardium and the catheter tip could be chosen discretionary. The simulated signals revealed themselves to be very accurate. Simulations can now be used to analyse intracardiac signals more closely. The exact position of the catheter will hereby always be assured, which is not always granted in clinical practice.
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Introduction
Despite the great medical progress in recent years, cardiac arrhythmias are still a major health problem and cardiovascular diseases display the cause of death number one in western society. The most common arrhythmia is atrial fibrillation (AF), which affects more than 10% of the population older than 70 and more than 1% of the population in general with an upward trend [1]. An accepted and effective method to treat AF is catheter ablation. During this procedure physicians try to electrically insulate the most important sources of AF-triggering, which are often suspected to be in the pulmonary veins. Additionally, special signal types, which are indicating further AF maintaining tissue, so called Complex Fractionated Atrial Electrograms (CFAEs), are searched for and are ablated [2]. During this procedure, contact of the catheter with the endocardium is essential. If the catheter looses endocardial contact, the ablation will be either imperfect or fails entirely. Besides, ablation procedures without having contact are holding a serious hazard of inducing intricacies like thromboses. Furthermore, while analysing CFAEs with the catheter not in endocardial contact, the resulting changed signal shape may lead to misinterpretations of the physician regarding the ablation decision [3]. Although the importance of the endocardial contact is clear, the methods of ensuring this contact are unsatisfactory. Mostly the physicians are trying to establish the contact using the subjective tactile resistance of the movability of the catheter. Since this procedure is fragile for errors, it would be desirable to determine the endocardial contact directly from the measured signal.
There is evidence from physicians that there are significant changes in the signal attributes, when the catheter is losing contact, but this characteristics were not analyzed up to now in previous work [4]. The aim of this work is to explicitly investigate the changes of the signal attributes in order to enable a possible automatic contact detection. Additionally, atrial electrograms will be simulated to inspect on the one hand the correctness of the mentioned attributes and on the other hand to check the possible use of simulated atrial electrograms in this specific research field.
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Methods
2.1
Data acquisition
In cooperation with St¨adtisches Klinikum Karlsruhe, intracardiac bipolar electrograms from different regions of the atria were examined. For a detailed investigation of the specific signal properties a substantial database, containing data of four patients, was composed. It contains signals measured while the catheter was in contact with the endocardium and signals measured while no contact was assured. Two of the patients suffered from paroxysmal atrial fibrillation, one patient suffered from acute atrial flutter, and one patient suffered from Wolff-Parkinson-White-Syndrome. Eventually, the database contains 256 signal segments, 149 in contact and 107 without contact, thus assuring a good comparison between all different signals. In order to allow an automatic analysis, a self-acting detection and segmentation method of active segments of the atrial electrograms was necessary. For this, an algorithm regarding the frequency and energy of the signal, the Non-
Linear Energy Operator (NLEO), was used [5]. Additionally, to disburden the signal from noise and baseline wander, frequencies less than 30 Hz and higher than 250 Hz were filtered out firsthand by the recording system.
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For an analysis of frequency changes the signal’s representation in the frequency domain was analysed. For this the Fourier Transform was used, which is defined as: 1 X( f ) = √ 2π
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Since the signal segments used to be relatively short, they were mirrored and repeated. Additionally, for a better function of the Fast Fourier algorithm the data was zero padded to 2n .
2.2.2 Energy In signal processing, the energy of a signal is a further common investigated property. In the present case, the frequency plays a role as well, since during AF CFAEs provide higher frequencies. For a combined examination of energy and frequency the Non-Linear Energy Operator delivers a solid tool and is in its discrete form defined as: En = xn2 − xn−1 · xn+1 .
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2.2.3 Shape Since physicians observed a blunting of signal peaks, the steepness will also be regarded. The steepness can be easily evaluated by calculating the slope of the derivative at the point of zero-crossing. In other words: It is the value of the second derivative at the point of the signal’s maximum. Besides, in order to make the steepness independent from the amplitude the signal is going to be scaled.
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Simulation of atrial electrograms
For a detailed simulation of the signals, we used the Courtemanche-Ramirez-Nattel (CRN) model [6], which is an exact mathematical model of the action potential based on ionic currents obtained from human atrial cells. For the simulation of the excitation propagation in complex tissue, such as the atria, the bidomain model was used. The bidomain model regards the intra- and extracellular space as two domains and describes the resulting intra- and extracellular potentials with two coupled partial differential equations. For definite results we modelled a three-dimensional tissue patch with measurements of 30 x 5 x 8 mm and a resolution of 0.1 mm. In z-direction the patch contained of human atrial tissue with a size of 2 mm. The balance was filled
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Results
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Differences between measured contact and non-contact signals
The frequency spectrum delivers a good method to distinguish signals whereas the catheter had endocardial contact (contact signal) from signals at which the contact was not existent (non-contact signal). Two signal examples, which allegorize good representations of their specific signal group are presented in figure 2. It is visible that the spectrum of the contact signal in comparison to the non contact signal is clearly broadened. This is visible for the vast majority of the database. The reflection of the signal energy also delivers a good method to distinguish both signal classes. When the energy is calculated with the NLEO, the observation of the energy for every signal of the database shows a considerable difference between the certain boxplots (see figure 3). The distribution of the calculated signal steepness is dis-
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with blood. In order to generate an excitation propagation, the tissue was stimulated on the very left part (see figure 1). For the signal recording we modelled a catheter with established dimensions. It consisted of two electrodes with a gap of 6 mm. The electrodes themselves had the shape of a ring. For the different measurements, the position of the catheter could now be varied arbitrarily in endocardial distance and measuring angle (tilt). Since the measured signals were already filtered by the recording system, this procedure had to be done with simulated signals as well in order to allow a good comparison between the two signal groups. Although the effect of filtering is often negligible in surface electrocardiograms, it has been revealed that filtering of intracardiac electrograms plays a crucial role for signal shape and properties and should never be ignored [7].
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Figure 1 Schematic description of the simulation environment. The excitation propagation is visualized with arrows.
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terscheiden. terscheiden. DeutlichDeutlich wird jedoch, wird jedoch, dass diedass Aufnahmeposition die Aufnahmeposition des Katheters des Katheters zum Endokard zum Endokard einen einen
Figure 5 Comparison between measured and simulated siggroßen Einfluss großen Einfluss auf die auf Signalmorphologie die Signalmorphologie darstellt. darstellt. Es zeigte Essich zeigte zudem sich weiterhin, zudem weiterhin, dass diedass gedie genauere Modellierung nauere Modellierung des Katheters des Katheters praktisch praktisch keinen Einfluss keinen Einfluss auf die Signalform auf die Signalform oder dasoder Spektrum das Spektrum nals. The signals on the left hand side are non-contact sigaus¨ ubt. aus¨ Dieubt. ausDie Punktelektroden aus Punktelektroden bestehenden bestehenden Katheter Katheter liefern fast liefern identische fast identische Ergebnisse Ergebnisse vergli- verglinals and on the rightgemittelten hand side they are contact signals. The chen mit chen ausmit mehreren aus mehreren gemittelten Spannungssensoren Spannungssensoren bestehenden bestehenden Elektroden. Elektroden. Alle simulierten Alle simulierten Signale Signale sind vollst¨ sind andig vollst¨ im andig Anhang im Anhang B.1 dargestellt. B.1 dargestellt. measured and simulated signals are highly similar.
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For a good validation and proof of the quality of the simulation, the simulated signals have been compared with the measured ones. Additionally to the general shape, the above mentioned properties should be similar as well. While regarding figure 5, where measured and simulated signals are visualized next to each other, these selected examples can valued to be nearly identical. If accessorily figure 6 (left) is regarded, the general signal shape, while increasing the distance to the endocardium, is definitely related to common measured atrial electrograms as well. Furthermore, the frequency spectrum shows the same characteristics, which was already visualized in figure 2: With an increasing distance of the catheter from the endocardium, the frequency range becomes clearly narrow. While comparing a virtually adjacent catheter with the simulation at a distance of 1.5 mm, the value of the highest appearing frequency is nearly halved. During the simulations, it was revealed that the angle of the catheter relatively to the endocardium plays a crucial role for the shape of the outcoming signal. Although at the very same position, different signal shapes could be observed, when the measurement angle was changed (see figure 7). The simulated measuring angles are described in table 1. Due to these different measuring positions 38 signals could
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Figure 66.3.Simulated atrial electrograms and their associAbb. 6.3. Abb. Einfluss Einfluss des Endokardabstands des Endokardabstands auf die Signalmorphologie. auf die Signalmorphologie. (a) Signale (a) mit Signale verschiedenen mit verschiedenen Kathe- Katheterabst¨ afrequency terabst¨ nden. (b) anden. Entsprechende (b) Entsprechende Leistungsdichtespektren. Leistungsdichtespektren. DeutlichDeutlich zu erkennen zu catheter erkennen ist eine schnelle ist einedistance schnelle Abnahme Abnahme ated spectrum with increasing der Amplitude der Amplitude mit wachsendem mit wachsendem Wandabstand. Wandabstand. Die Signalspitzen Die Signalspitzen werden zudem werdenerkennbar zudem erkennbar stumpfer, stumpfer, was was zus¨ atzlich zus¨ durch atzlich ein durch Fehlen einhochfrequenter Fehlen hochfrequenter Signalanteile in den Leistungsdichtespektren in den Leistungsdichtespektren atigtbest¨ wird. atigt wird. from the endocardium. The Signalanteile displayed distancesbest¨are (from top to down): 0.1 mm (virtually adjacent), 0.5 mm, 1.0 mm and 1.5 mm.
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Figure 4 Boxplot of the steepness. The non-contact signals have a significant lower mean value, which make them more blunted in comparison to the contact-signals.
be analysed. In this connection, the observation of further signal properties showed a good correlation with the database. While regarding only the simulated signals the previously mentioned characteristics are showing definite differences between non-contact and contact signals (see figure 8). A quantitative comparison with boxplots resulting from the measured database (compare figures 3 and 4) and the simulations provides clear similarities. Finally, it should be once again highlighted that the present signals were simulated and that the simulation environment was entirely free of natural parasitic influences. Caused by this reason the results are clear without ambiguity, which explains the non existent outliers of the boxplots and the small quantitative value differences.
Table 1 Simulated measuring angles. α represents the angle of the x-z-plane and β represents the angle of the x-y-plane.
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Discussion and conclusion
In this work, changes of signal properties of a catheter signal with and without endocardial contact were presented. For a definite proof of these findings, a substantial database was created. These changes used to be definitely significant. Principally the frequency spectrum shows a major change. When the catheter was considerably in contact, the spectrum was broadened in contrast to the case, when the catheter lost endocardial contact. Furthermore, properties like signal energy and steepness of signal peaks showed sizeable alterations as well. As a second part of this work, atrial electrograms were simulated. The simulations were accomplished with different gaps and measuring angles relative to the endocardium. As a result the signal shape was comparable with the measured ones. Additionally, the above mentioned signal properties showed a similar result for contact and non-contact signals and thus were proven to be of good and usable quality. Using these reliable findings, regarding the signal property alterations, it is now possible to develop a system (e.g. based on a decision tree), which is able to detect the endocar-
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Acknowledgements
This work was composed in collaboration with St¨adtisches Klinikum Karlsruhe. We would like to address our special thanks to Prof. Dr. Claus Schmitt, Dr. Matthias Merkel, and Dr. Armin Luik for the excellent cooperation, the measurement of the signals and the intensive discussion of the results.
6 Figure 7 Influence on the signal shape, when the angle of the catheter, relatively to the endocardium, is changed. Positions clockwise from top left: Position 1, 2, 4, 3.
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dial catheter contact automatically. Utilizing this system, catheter ablation could become even more fail-safe and intricacies would be reduced to a minimum. Additionally, it was shown that simulations of these signals are reliable. In future, detailed simulations could make intracardiac signal analysis easier. It is now possible to take the angle of the catheter into account and to define the gap of the catheter from the endocardium as accurate as it is nearly impossible to accomplish in clinical practice.
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Figure 8 Boxplot of the NLEO (left) and boxplot of the signal steepness (right).
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References
[1] Fuster, V.; Ryden, L.; Asinger, R. et al.: ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation. Circulation, (2006) [2] Haissaguerre, M.; Jais, P.; Shah, D. et al.: Spontaneous initiation of atrial fibrillation by ectopic beats originating in the pulmonary veins. The New England Journal of Medicine, (1998) [3] Nademanee, K.; McKenzie, J.; Kosar, E. et al.: A new approach for catheter ablation of atrial fibrillation: mapping of the electrophysiologic substrate. Journal of the American College of Cardiology, (2004) [4] Rango, J.; Adams, L.; Stellbrink, C. et al.: Entwicklung eines Auswertesystems f¨ur die minimalinvasive Therapie von Vorhofflimmern. Biomedizinische Technik, (2001) [5] Schilling, C.; Nguyen, M. P.; Luik, A. et al.: Non-linear energy operator for the analysis of intracardial electrograms. In IFMBE Proceedings World Congress on Medical Physics and Biomedical Engineering, 2009 [6] Courtemanche, M.; Ramirez, R.; Nattel, S.: Ionic mechanisms underlying human atrial action potential properties: Insights from a mathematical model. Am. J. Physiol., (1998) [7] Kusumoto, F.: Understanding Intracardiac EGMs and ECGs. John Wiley, 2010
