Resolution limits of electrocardiography: Evidences of a model study

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1 Resolution limits of electrocardiography: Evidences of a model study KRISZTINA SZAKOLCZAI, KRISTÓF HARASZTI, GYÖRGY KOZMANN Research Institute for Technical Physics and Materials Science Konkoly-Thege Miklós u , 2 Budapest, and University of Veszprém, Egyetem u., 82 Veszprém HUNGARY Abstract: - According to previous modeling studies - propagation of depolarizing wavefronts - consists of subintervals, each characterized by an epoch of smooth progression of activation. At the onset and end of these intervals, abrupt changes occur in the 3D pattern of activation waves (e.g. at the time of collision of an activation wave with other waves, or unexcitable myocardium), which manifest themselves in the surface ECG as jumps (high frequency notches and slurs). The amplitude and timing of jumps provides diagnostic information on bioelectrical tissue properties of the heart. According to the numerical modeling results the resolution of electrocardiography is in the range of 5-6 mm in the case of wave-initiation point dislocation, while intramural spherical unexcitable tissue segments with a radius of 5-6 mm are detectable. Key-Words: electrocardiography, activation, bioelectrical tissue properties, unexcitable tissue, resolution Introduction According to our previous modeling results, propagation of depolarizing wavefronts in the myocardium is largely deterministic, resulting essentially in piece-wisely smooth, body surface ECG signals. However, even in normal hearts there are times when ECG exhibits sudden unexpected changes (notches and slurs). These time instants are referred to as jump times while the underlying biophysical events are referred to as discontinuous propagation. Discontinuous propagation occurs at times of epicardial or endocardial breakthrough, collision of activation waves (the most common characteristic events, CEs), or other phenomena occurring at the interface of regions with altered activation (or activation propagation) properties [-4]. Recovery the body surface signs of discontinuous propagation can be achieved by a simple linear predictive algorithm (LPA) and a decision-making procedure [2]. The systematic comparison of the exactly known ventricular activation propagation timing and the sudden increase in the prediction error function proved that jumps are reliable indicators of the underlying discontinuous propagation. The timing of discontinuous events provides information on bioelectrical tissue properties (excitability and propagation velocity) of the myocardium and the intraventricular conduction system. However, this type of information is currently unexploited mainly because the information carrier features are low in amplitude, not readily accessible. In this study, the resolution limits of electrocardiographic methods were addressed from the point of view intrinsic activation timing measurements and the detection of unexcitable regions. The model based estimates of resolution were considered in the light of the signal-tonoise ratio achievable by advanced signal processing. 2 Materials and Methods The numerical model used consisted of a conceptual (simplified geometry) propagation heart model [5], and a realistic inhomogeneous torso model. Potential field data were simulated with a forward program package [6]. In the simplified "conceptual heart model, ventricle geometry was defined analytically by sections of compound quasi-ellipsoids. Activation was initiated from predetermined starting elements (initiation points), and propagated in agreement with the Huygen s principle. From the point of view of electrical sources, the activation wave front was considered as a uniform dipole layer (UDL model) [7]. The simulation was confined to depolarization. Basically the spread of activation in the whole mass of myocardium was considered to be isotropic, but a layer with a higher conduction velocity was defined on the endocardial surface of the left and right ventricular walls to simulate the effect of the intraventricular conduction system (mesh of Purkinje fibers), where propagation velocity was three times higher than in the rest of the myocardium. Physically, each of the propagation model corresponded to 2.5 ms in the real heart (an approximation derived from the cubic voxel dimensions of the model and from the value of

2 propagation velocity). The time course of ventricular activation was visually represented by (color coded) cross-sectional activation maps clearly displaying myocardial regions already activated and parts still to be activated. At each moment the cross-sectional activation maps as well as epicardial activation map were available to provide the reference timing of "electrophysiological events", wave collision, breakthrough or other discontinuous propagation. Body surface potential distribution associated with the simulated activation process was computed by a forward program package using the boundary element method and assuming a piecewise inhomogeneous realistic volume conductor (body) model. Due to inherent properties of the uniform double layer theory, the effect of the real wavefronts were taken into consideration by the geometry of the relevant rims, measurable on S H. [7,8]. φ ( P, t) = l( P, S) H ( t τ ( r )) ds H (2.) S H where: φ(p i,t) :potential at the ith body surface point at the moment of t, l(p,s H ) :lead-field between the chest surface point P and the S H heart surface, closing the excitable myocardium. (Typically endocardium and epicardium, but in the case of intramural unexcitable tissues, the surface involves closed surfaces surrounding the unexcitable regions as well.) H(t) :Heaviside function τ (r) :activation sequence along S H For the sake of the direct comparison of the model generated and the measured signals, the Simson-type bipolar leads were derived as well from the simulated ECG signals. The prediction error was computed by the equation (2.2). e i (t) = φ i (t) - 2 φ i (t- t) + φ i (t-2 t). (2.2) where: φ i (t) t e i (t) : potential at the ith body surface ECG at the moment t, :, : error at the ith body surface ECG, at the moment t. 3 Results We have demonstrated that all the sudden increases of prediction errors were associated with the collision of activation waves with permanently or functionally unexcitable tissues (such as breakthrough, collision of activation waves or collision of activation waves with unexcitable sub-regions of the myocardium [9-2]). 3. Perturbation of discontinuous event timing The sensitivity of LPA to reveal subtle changes in discontinuous event timing was tested by the relative displacement of two septal wave initiation points on the endocardial surface (the relative displacement of two initiation points left and right, up and down along the main curvature lines by 6 mm). Obviously such displacements should be reflected in shifted timing of the relevant events, in this case the time of wave collision. The changes occurred according to the expectation; i.e. a greater distance between the initiation points shifted the time of collision upward and vice versa (Fig.). The result is remarkable, as body surface signals due to septal collisions are small (few µvs). observed Scatterplot of reference and observed septal collision times y= *x+eps reference case 2 cases 3 cases cases Fig. Scatter plot of the detected CE time vs. the reference time observed on the basis of cross-sectional activation maps. The effect of the dislocation of two septal initiation points on the time instant of septal collision is shown. 3.2 Detectability of spherical intramural unexcitable tissues Intramural unexcitable tissues (scars, fibrotic tissues) were represented by spherical regions, systematically replaced in different anatomical positions. An example of the arrangement is depicted on the schematic drawing of Fig.2 During the simulation a normal sequence of activation was assumed. In each individual experiment the relevant sequence of body surface maps were

3 computed as well as the Simson type X,Y,Z leads were computed and analyzed. time-instant of the sudden increase of the difference time-functions. The polarity of the differences is depending on the direction of the activation wave normal vector at the point of collision with the unexcitable region. A: Fig.2 Schematic representation of the unexcitable regions within the myocardium. Unexcitable regions shown in the lower crossection are located in the height represented by the heavy horizontal line in the upper, view B:,8,6,4 Anterior X Posterior X Lateral X Anterior X Posterior X Lateral X In Fig.3 the deviation of the prediction error signal from the normal case is drawn based on the relevant Simson leads for the total duration of depolarization (QRS interval). The use of the difference signal in this representation allows the estimation of the net contribution of the unexcitable tissue to the surface signal. According to the graphs shown, the surface effect of an unexcitable tissue in the myocardium is influenced by the location and also by the extension of region. In Fig.3A the starting point of the upstroke of the difference signals (in absolute value) is according to our expectation, i.e. the defect manifested itself first in the posterior region, while the lateral effect showed up relatively late. In Fig.3B, the relevant e(t) error functions are presented. The significant difference in timing is clearly shown in these examples as well, but obviously, the most significant error amplitudes coincide with the maximal second derivatives. Amplitude differences in Fig.3B might be due to the difference in the relative curvatures of the activation wave and the unexcitable region hited, but the major cause can be attributed to the differences in the relevant lead vectors [3,4]. These model computations suggest that meaningful diagnostic features are hidden in the low amplitude (µv level) details. Fig.4 shows the effect of spherical unexcitable regions inserted along a vertical cross-section in the posterior heart surface. Anatomically the localizations moved from the apex of the heart up to the base. In these examples again, significant differences are shown in the,2 -,2 -,4 -,6 -, Fig.3 A: Deviations from normal φ i (t) time-course in Simson's lead X, due to the unexcitable regions located according to in the layout shown in Fig. 2. B: The e(t) functions of the above X lead signals. (One equals to 2.5 msec, amplitudes are in µvs.) apex middle base Fig.4 Differences in the Simson s X lead due to the replacement of unexcitable spherical obstacles, along a vertical cross-section on the posterior wall. (One time step equals to 2.5 msec, amplitudes are in µvs.)

4 3.3 Resolution limits in real measurements The resolution limits in real human measurements due to the noise level was estimated by the signals of 7 healthy subjects taken by the lead system suggested by Simson for late potential studies. Signal-to-noise ratio was improved by a high-precision synchronized averaging. Time-alignment was done by the use of the correlation method. The number of cycles involved in averaging was gradually increased in steps of cycles. According to Fig.5, residual noise level was < µv, if more than cycles were involved in averaging. Fig.5 Illustration the effect of synchronized averaging on the improvement of signal-to-noise ratio of the error function, e(t). Before the Qonset (dotted vertical line) the steady reduction of the residual noise is clearly observable. 4 Conclusion Fine details of BSPMs have been analyzed based on a numerical chest and heart model. Due to the inherent accuracy limits of the numerical models, the results obtained should be considered cautiously. However, the simultaneous analysis of the spatio-temporal source formation by cross-sectional activation maps and the relevant BSPMs as well as the error maps introduced earlier, suggest, that µv-level fine details of BSPMs contain meaningful biophysical information, not accessible by other methods. From a diagnostic point of view, the detection of localized defects (discontinuities) in tissue electrical properties inside the myocardium arising from ischemic heart disease or fibrosis might have a significant impact on the care and treatment of patients. Based on the results illustrated above, a dislocation of epicardial wave initiation points by 5-6 mm or the development of a spherical unexcitable tissue in the myocardium with a radius of 5-6 mm yield in detectable body surface signals. According to our interpretation, the use of BSPMs with a noise level in the order of late potential measurements allows the development of parameters characterizing directly the tissue properties in the ventricular conduction system as well as in the myocardium. Consequently, the electrical function of the heart can be addressed with a higher precision than before, with signal processing similar to late potential recovery (timealignment and averaging). Acknowledgement This study was supported by the National Research Found grant T3385, the NKFP grant 2/52/2 of the Ministry of Education, Budapest, and by the bilateral cooperation of the Hungarian and Slovakian Academies. References: [] Langer, P.H., Geselowitz, D.B., Mansure, F.T. Highfrequency components in the electrocardiogram of normal subjects and of patients with coronary heart disease. Am. Heart J., 62:746 (96). [2] Kozmann, Gy., Cserjés, Zs., and Préda, I. Manifestation of characteristic events of ventricular activation in body surface potential field. In Electrocardiology 83 (I. Ruttkay-Nedecky, P. Macfarlane, Eds.), pp. 2o4-2o7, Excerpta Medica, Amsterdam, 984. [3] Greensite, F. Well-posed formulation of the inverse problem of electrocardiography. Ann. Biomed. Eng. 22:72 (994). [4] Zenda, N., Tsutsumi, T., Sato, M., Tekeyama, Y., Harumi, K., Wei, D. Computer simulation of notches on initial part of QRS complex in patients with anterior myocardial infarction. In Electrocardiology 2 (L. De Ambroggi, Ed.), pp. 7-2, Casa Editrice Scientifica Internazionale, Roma, 2. [5] Szathmáry, V., and Osvald R. An interactive computer model of propagated activation with analytically defined geometry of ventricles. Comput. Biomed. Res. 27, 27(994). [6] Tinova, M., Huiskamp, G.J., Turzova, M., Tysler, M. The uniform double layer model and myocardial infarction: forward solution. Brat. Lek. Listy 97, 558(996). [7] Cuppen, JJM, van Oosterom, A. Model studies with the inversely calculated isochrones of ventricular activation. IEEE Trans Biomed Eng, BME-3: (984). [8] Macfarlane, P.W., Veitch Lavrie, T.D. (eds). Comprehensive electrocardiology, Section 4, Vol., , Pergamon Press, New York, 989.

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