Electrocardiographic assessment of repolarization heterogeneity

Bart Hooft van Huysduynen Electrocardiographic Assessment of Repolarization Heterogeneity Bart Hooft van Huysduynen El...

Author: Bart Hooft van Huysduynen

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Bart Hooft van Huysduynen

Electrocardiographic Assessment of Repolarization Heterogeneity Bart Hooft van Huysduynen

Electrocardiographic Assessment of Repolarization Heterogeneity


Bart Hooft van Huysduynen


PROEFSCHRIFT ter verkrijging van de graad van Doctor aan de Universiteit Leiden op gezag van de Rector Magnificus Dr. D. D. Breimer, hoogleraar in de faculteit der Wiskunde en Natuurwetenschappen en die der Geneeskunde, volgens besluit van het College voor Promoties te verdedigen op donderdag 8 juni 2006 te klokke 16.15 uur

door

Bart Hooft van Huysduynen geboren te Amsterdam in 1974

Promotiecommissie Promotores:

Prof. dr. M.J. Schalij Prof. dr. E.E. van der Wall

Co-promoter: Dr. ir. C.A. Swenne Referent:

Prof. dr. N.M. van Hemel (Hart Long Centrum Utrecht, Nieuwegein)

Overige commissieleden:

Prof. dr. A. van der Laarse Prof. dr. A. van Oosterom (Centre Hospitalier Universitaire Vaudois, Lausanne) Dr. H.W. Vliegen Prof. dr. A.A.M. Wilde (Academisch Medisch Centrum, Amsterdam)

The research described in this thesis was performed at the Department of Cardiology of the Leiden University Medical Center, Leiden, the Netherlands The study described in this thesis was supported by a grant of the Netherlands Heart Foundation ( NHF-2001B177). Financial support by the Netherlands Heart Foundation for the publication of this thesis is gratefully acknowledged.

Aan mijn ouders

© 2006 B. Hooft van Huysduynen, Leiden, the Netherlands All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission from the copyright owner.

ISBN: 978-90-9020616-5 Cover image: Scanning electron microscope picture of Purkinje fibers at the endocardium of the heart (magnification 300x). The electrocardiogram (lead V5) of dr. P.S. Monraats. Printed by: Febodruk B.V. te Enschede Financial contribution to the publication of this thesis was kindly provided by Jacques H. de Jong Stichting, J.E. Jurriaanse Stichting, St Jude Medical, Siemens, Guidant, Novartis, Bayer, Schering-Plough, AstraZeneca, Boehringer Ingelheim, BristolMyers Squibb, Servier, Pfizer, Sankyo and Medtronic.

Contents Chapter 1. Introduction: Electrocardiographic assessment of repolarization heterogeneity. Chapter 2. Validation of ECG indices of ventricular repolarization heterogeneity; A computer simulation study. J Cardiovasc Electrophysiol 2005; 16: 1097-103 Chapter 3. Hypertensive stress increases dispersion of repolarization. Pacing Clin Electrophysiol. 2004; 27: 1603-9 Chapter 4. Increased dispersion of ventricular repolarization during recovery from exercise. submitted Chapter 5. Reduction of QRS duration after pulmonary valve replacement in adult Fallot patients is related to reduction of right ventricular volume after pulmonary valve replacement in Fallot’s tetralogy. Eur Heart J 2005; 26: 928-32 Chapter 6. Pulmonary valve replacement in tetralogy of Fallot improves the repolarization. submitted Chapter 7. Dispersion of the repolarization in cardiac resynchronization therapy. Heart Rhythm 2005; 2: 1286-93 Chapter 8. Summary and conclusions

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Nederlandse samenvatting

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Dankwoord

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Curriculum Vitae

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Chapter 1 Introduction Electrocardiographic assessment of repolarization heterogeneity

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Chapter 1

Outline of chapter 1 History of the electrocardiogram and the T wave The T wave and action potentials Heterogeneity of the repolarization and arrhythmias Physiological heterogeneity of repolarization -Transmural repolarization heterogeneity -Apico-basal repolarization heterogeneity Electrocardiographic indices of repolarization heterogeneity - QT interval - Tapex-end interval - QT dispersion - T-wave amplitude - T-wave area - QRS-T angle - T-wave complexity - Ventricular gradient Aim and outline of the thesis

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Introduction: Electrocardiographic assessment of repolarization heterogeneity

History of the electrocardiogram and the T wave The development of electrocardiography has largely taken place in Leiden. Willem Einthoven was one of the founding fathers of electrocardiography, for which he received the Nobel prize in 19241. Einthoven was head of the Leiden University Physiology Laboratory nearby the Academic Hospital2. Initially he improved Lippmann’s electrometer, which Waller had used to record the first human ECG in 18873. In 1895 Einthoven developed a mathematical formula to construct the actual ECG from the signal of the slow responsive electrometer. To discern his calculated ECG from its predecessor, he renamed the ABCD deflections into PQRST (Figure 1a) 4 . These names were universally adopted and are still in use today. He described the T wave more or less as “ein stumpf und aufwärts gerichte Spitze “. In the following years Einthoven developed the world famous string galvanometer5, which allowed recording of high quality, stable electrocardiograms. In 1902 the first so recorded ECGs were published and the actual shape of the T wave was revealed (Figure 1b)6.

Figure 1a. Einthoven calculated the electrocardiogram from the signal of the slowly responsive electrometer and called the derived deflections PQRST, names that are still in use today. Einthoven. Pflügers Arch ges Physiol 1895.

Figure 2a. In 1902 electrocardiograms recorded with the string galvanometer were first published. Einthoven. In: Herinneringsbundel Prof. Rosenstein 1902.

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Chapter 1

The T wave and action potentials The T wave depends on differences in timing of the repolarization of myocardial cells. Schematically, when two action potentials are subtracted, a T-wave emerges7 (Figure 2). The repolarization time of a given myocardial cell consists of the summation of the activation time and action potential duration (APD).

Figure 2. Schematically, when two action potentials are subtracted, a T-wave emerges. 0 = fast depolarizing upstroke, 1 = initial rapid recovery phase, 2 = plateauphase, 3 = repolarization, 4 = resting potential. Adapted from Franz et al. Prog Cardiovasc Dis 1991.

The primary function of the cardiac electrical system is the coordination of myocardial contraction. After the upstroke of the action potential, myocardial contraction starts, thereafter the plateau phase of the action potential is responsible for the continuation of myocardial contraction. In combination with the specific organization of the myocardial fibers, the contraction of myocardial cells results in a wringing motion8 of the heart that efficiently propels the blood9. Furthermore, action potential durations have the tendency to correct for differences in activation time. In general, the earliest activated regions have the longest action potential duration and the latest activated regions have the shortest action potential duration. These repolarizing properties result in a more homogeneous repolarization10;11 and relaxation12.

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Heterogeneity of the repolarization and arrhythmias Besides a direct relation with mechanical function, the shape of the action potential (AP) also has protective electrophysiological properties. The relatively long plateau phase of the cardiac action potential prohibits tetanus in the myocardium, which occurs relatively frequently in skeletal muscle 13. Furthermore, the tendency of APDs to compensate for different activation times diminishes repolarization heterogeneity10;11, which reduces the risk of arrhythmias. Heterogeneous repolarization facilitates the formation of functional barriers surrounded by excitable tissue14;15. Re-entrant arrhythmias may be initiated by an adversely timed stimulus that reaches such a barrier and circles around it16. As a consequence, abrupt, local differences in refractoriness facilitate re-entrant arrhythmias. Repolarization differences between nearby areas are therefore potentially more arrhythmogenic than repolarization differences between areas more distant from each other (Figure 3). Figure 3. Dispersion in repolarization or refractoriness depicted by varying grey scale in two simulated fields of 256 (16×16) electrode sites. Lower panels show histograms of these local inhomogeneity values, corresponding to the two fields. Arrowheads above histograms indicate the values of percentiles P5 ( ► ), P50 ( ▼ )(median) and P95 ( ◄ ). Although the median dispersion of refractory period is the same in both conditions, the left figure shows global dispersion, with smoothly changing differences in refractoriness. Only in the right figure local dispersion exists with possible higher susceptibility to functional barreres and re-entry arrhythmias. Local inhomogeneity values are calculated on the extreme right as the maximum (24 ms, circled) of absolute differences (4, 10, 18 and 24 ms) within a neighbourhood of four electrode sites. Adapted from Burton and Cobbe. Cardiovasc Res 2001. 13

Chapter 1

As can be inferred from the above, repolarization heterogeneity is thus linked to arrhythmogenesis due to the relationship with refractoriness. When the AP of a myocardial cell is still in its plateau phase (phase 2) the cell is absolute refractory, to the contrary, when the cell is fully repolarized (phase 4) the cell is fully excitable. Any phase in between, on the down slope of the APD (phase 3), will result in a partially excitable cell, also named the relatively refractory period, during which a strong stimulus is still able to depolarize the cell17. An exception to these principles is, for example, post-repolarization refractoriness, which can be present in ischemic myocardium18. An ischemic cell may be refractory despite having reached phase 4. Action potentials can be recorded using microelectrodes or monophasic action potential catheters19. The action potential duration is defined as the APD90, which is the time interval from upstroke of the action potential to the moment when action potential amplitude has decreased by 90 % of its maximum amplitude. In vivo, repolarization studies in animals are mostly performed using needle electrodes allowing the measurement of activation recovery intervals (ARIs). The ARI is measured from the negative deflection of the activation complex to the positive deflection of the repolarization wave on the unipolar electrogram. ARIs are a surrogate measure of APD, but with a good correlation20;21 between recorded monophasic action potentials and ARIs 20. As stated before, repolarization heterogeneity may form the substrate for an arrhythmia, but a trigger is also necessary to initiate an arrhythmia. Early after depolarizations may occur in the setting of a disturbed repolarization and may serve as this trigger. The premature stimulus itself also modifies the repolarization heterogeneity22;23. Even in patients without overt structural heart disease, closely coupled, multiple extrastimuli are able to induce ventricular fibrillation. Arrhythmias can also be maintained by continuously firing foci24-26.

Physiological heterogeneity of the repolarization Repolarization heterogeneity is mostly classified in transmural and apico-basal heterogeneity. Repolarization heterogeneity between the left and right ventricle also exists, but data are scarce.

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Transmural repolarization heterogeneity The nature of the transmural repolarization differences is not entirely clear; some studies dispute the existence and direction of the transmural repolarization gradient27;28. The presence or absence and direction of the transmural gradient is essential for the understanding of the formation of the normal T wave and will be discussed in detail the following paragraphs. As early as in 1931 Wilson proposed the existence of a ventricular gradient, caused by non-homogeneous action potential durations throughout the heart29. Despite opposite polarities of de- and repolarization currents, human QRS complexes and T waves attain the same polarity in most ECG leads. This concordance between QRS complexes and T waves can be explained by an inverse transmural repolarization order (from epi-to-endocardium) compared to the excitation order (from endo-toepicardium)29;30. Animal studies In canines the polarity of T waves can be varied by changing transmural APD differences by local warming or cooling30. Warming is known to shorten APD and cooling is known to lengthen APD31. Epicardial warming as well as endocardial cooling cause upright, concordant T waves. Endocardial warming and epicardial cooling cause inverse, discordant T waves30. Van Dam and Durrer measured refractory periods in dogs and found the shortest refractory periods in the midwall. Intermediate APDs were recorded from the endocardium and the longest APDs from the epicardium. They reported negative T waves in unipolar leads from the epicardial surface32. On the other hand, Burgess et al. measured longer endocardial than epicardial refractory periods33. Abildskov studied refractoriness and repolarization times (defined as activation time plus refractory period) in 15 anesthetized dogs34. In 5 dogs, transmural excitation and repolarization studies were performed immediately after thoracotomy. Despite an earlier excitation, the endocardium repolarized later than the epicardium, as reflected by longer refractory periods and later repolarization times (figure 4).

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Chapter 1

Figure 4. Despite an earlier excitation, the endocardium repolarized later than the epicardium, as reflected by longer refractory periods and later repolarization times. Recovery times are used as a surrogate for repolarization time (excitation time + refractory period = repolarization time) Adapted from Abildskov. Circulation 1975.

Spach and Barr used intramural and epicardial electrodes to measure potential distributions during excitation and repolarization35. Beforehand they recorded ECGs to ensure positive (concordant) T waves, and excluded several dogs with negative T waves. Depolarization spread in accordance with the findings of Durrer and coworkers36 from endo- to epicardium, starting at the left midseptum and ending at the base. In general, positive potentials were recorded from the epicardium compared to more negative potentials recorded from the endocardium, implying an earlier epicardial repolarization. El-Sherif et al. performed 3-D mapping of arrhythmias emerging under long QT conditions in an in-vivo canine model37. They found that subendocardial focal activity can maintain arrhythmias but may result in reentrant arrhythmias when the repolarization heterogeneity was large enough. Steep transmural differences in ARI across the wall contributed to this repolarization heterogeneity. Recently, Janse et al. published a study performed in dogs28 that was in line with the findings of Janse’s thesis published in 197138. The epicardial repolarization time was not earlier compared to the endocardial repolarization time. However, the published canine ECG showed discordant QRS complexes and T waves28 as opposed to the T and QRS concordance found in humans. Different species, and more specifically different mammals of different size may show

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either concordance or discordance on their ECG39. In dogs concordance may be either present or absent35. In chimpanzees, a species genetically close to humans, concordance is present in most leads40. The ECGs of the giraffe as well as the humpback whale41 show discordant T waves. Several studies disputing the presence of an epi- to endocardial transmural repolarization gradient, depicted surface ECGs with discordant ECGs. Results obtained from these species can therefore not be extrapolated to the human repolarization. Before selecting animals for an invasive repolarization study, electrocardiograms should be recorded to assure concordant T waves. Human studies Franz et al. recorded left ventricular endocardial monophasic action potentials in 7 patients undergoing catheterization (for suspected coronary disease in 5 patients and aortic disease in 2 patients)10. Additionally, they measured epicardial monophasic action potentials during surgery for coronary artery bypass grafting in 3 other patients. To compare endo- and epicardial recovery times in these different patients, and during different interventions, they normalized the repolarization times (RT = activation time + APD) of endo-and epicardium on the individual QT intervals on the surface ECGs. Expressed as percentage of the QT interval, epicardial RTs (71-84 %) were shorter than endocardial RTs (80-98%). Taggart et al. measured left ventricular ARIs in 21 patients during CABG42. Measurements were performed during right ventricular stimulation at different cycle lengths and during spontaneous atrial beats. No statistical differences were found between any of the recording sites. However, when closely observing the transmural ARI graphs, a trend towards a 5 ms shorter subepicardial ARI than subendocardial ARI can be detected. Electrograms provided as example show that the epicardial ARI is 14 ms shorter than the subendocardial ARI. These differences are small but consistent. Possibly, the interindividual variation in ARI is larger than the intraindividual variation in transmural ARI, rendering them undetectable by the used statistical methods. Understandably, Taggart et al. used short needles, the edge of the deepest electrode reaching only 7.15 mm. The authors state that the first 0.5 to 1.0 mm is epicardial fat, this would mean that the center of the deepest electrode reaches only to a depth of 6.5 mm from the epicardial myocardial surface. Therefore the endocardium is virtually left out of these experiments. In conclusion, in animal studies the direction of a transmural gradient determines the 17

Chapter 1

polarity of the T wave. An epi- to endocardial gradient is responsible for concordant T waves. The results of these animal studies combined with the interpretation of the above mentioned human studies suggest that a small transmural epi- (early repolarization) to endocardium (later repolarization) repolarization gradient is likely to be present under physiological conditions in humans. M-cells M-cells may play a pivotal role in transmural repolarization heterogeneity43. Part of the debate on transmural dispersion is the discussion whether M-cells have a significant physiological effect on the repolarization. Yan and Antzelevitch demonstrated the presence of M-cells in a preparation of the left ventricular free wall43. This preparation was made by dissecting a wedge shaped part of the left ventricular wall with its supplying large epicardial artery (which was perfused subsequently). Monophasic action potentials were recorded from epi- and endocardial cells and from the mid-myocardial cells, which were named: M-cells. The M-cells in this preparation had the longest APD and the epicardial cells the shortest APD. The difference in action potential duration and amplitude between these cell layers mainly determined the morphology of the T wave in a pseudo-ECG recorded across the wedge preparation. The shorter epicardial APD and earlier repolarization time resulted in a positive T wave directed towards the epicardium. Drouin et al. confirmed the presence of M-cells in wedge preparations of 4 apparently healthy human hearts44. M-cells were found 1 mm up to 4-5 mm from the epicardial surface, constituting of approximately 30 % of the myocardial mass. M-cells demonstrated an increased rate-dependence of their already longer APD duration during electrical stimulation with 1 to 0.1 Hz. The lower the stimulation frequency, the longer the APD, thereby increasing transmural repolarization heterogeneity. Anyukhovsky et al. performed a comparative study of wedge preparations and in vivo canine hearts45. They measured APDs in transmural wedge preparations and ARIs in in vivo hearts. In the wedge preparations they found M-cells; midmyocardial cells with relatively long APDs that were more sensitive to abrupt changes in cycle length than endo- and epicardial cells. Noteworthy is that the epicardial APD were longer than endocardial APD. However, they did not find any transmural difference in (averaged) ARIs in vivo, supposedly caused by electrotonic interaction between myocar-

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dial cells. However, in their example an endocardial (shorter repolarization time) to epicardial (longer repolarization time) gradient was present and accompanied by an ECG with a discordant T wave. Conrath and Opthof used (strand-) simulation models to study the effects of electrical coupling on transmural repolarization differences46. Their conclusion is plausible: in physiological conditions, M-cells do not introduce large transmural repolarization differences; due to intact electrotonic coupling the repolarization differences become smaller. In conclusion, from the wedge preparation studies we know M-cells exist. However, the electrophysiological significance of M-cells in the normal heart is probably small. Large, abrupt repolarization differences due to different repolarization properties of different cells are smoothened by electrotonic interaction with surrounding cells. However, arrhythmias mostly emerge under unphysiological conditions. For example, in heart failure patients connexins are down regulated, which produces uncoupling between transmural muscle layers leading to marked repolarization heterogeneity between epicardial and deeper myocardial layers. Therefore, decreased connexin expression patterns can potentially contribute to an arrhythmic substrate in failing myocardium47. Another argument against the functional significance of Mcells is that APD lengthening appears only at unphysiological slow rates. However, Torsade de pointes arrhythmias are known to be initiated after a short-long(-short) sequences48. Thus, arrhythmias mostly emerge under pathological conditions, with less electrical coupling, greater cycle length changes and adversely timed extrastimuli. These conditions may increase the electrophysiological expression of M-cells resulting in an increase of transmural repolarization heterogeneity to a critical level and an increased susceptibility to arrhythmias.

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Chapter 1

Apico-basal repolarization heterogeneity Besides a (small) transmural gradient, an apico-basal gradient is probably also present under normal conditions. However, data on apico-basal repolarization heterogeneity is contradicting. The apico-basal gradient is also crucial for the inscription of the normal T wave. The normal T wave forms the basis for further studies on irregular T waves and electrocardiographic indices of repolarization heterogeneity throughout this thesis. An essential aspect of the discussion on the apico-basal gradient is the issue whether action potentials overcompensate or undercompensate for differences in activation times. This would imply difference or similarity between activation and repolarization patterns. In the following studies on the apico-basal gradient, repolarization and activation times were measured parallel to the ventricular walls, on either the epicardium or the endocardium, or both. Subsequently, we will present an analysis based on the characteristics of QRS and T vector loops recorded in healthy subjects. Burgess et al. reported shorter refractory periods at the base than at the apex in dogs33. Restivo et al. however found shorter apical than basal APDs in guinea pigs measured with voltage sensitive dye. Long QT syndrome type 3 was mimicked with anthopleurin-A. Anthopleurin-A exacerbated the normal epicardial uniform apex-base APD gradient, resulting in heterogeneous repolarization gradients, functional blockades, re-entry and ventricular tachycardias49. Gepstein et al. measured endocardial ARI in 13 swine during atrial activation and ventricular pacing50. He found that even after a short period of pacing, ARIs adapted to and compensated for depolarization times. In most pigs ARIs did not overcompensate for the depolarization time, causing repolarization patterns to follow the depolarization patterns. Refractoriness was measured in 3 swine and appeared to be inversely related to the depolarization time, thus overcompensating the depolarization times. The quickness of this ARI adaptation to depolarization times suggests that electrotonic coupling played an important role in the shortening of ARI. Franz et al. showed that differences in activation time were compensated by action potential duration differences so that repolarization was nearly homogeneous measured on the endocardium in some patients as well as measured on the epicardium 20


in other patients10. Only a trend towards a longer repolarization time of the first activated regions (diaphragmatic and apico-septal) compared to the later activated regions was present. When all activation times (AT) and action potential durations of individual patients were plotted, an inverse relation was found with an average slope greater than negative unity (-1.34), which shows that action potential duration overcompensate for activation time, thereby contributing to concordant T waves. Yuan et al. measured endocardial monophasic APD in eight patients referred for arrhythmia treatment to the electrophysiological laboratory and in 10 swine51. They showed that in most patients and swine, repolarization followed depolarization, despite shorter MAP at later activated sites. In patients the slope between AT and APD was -0.45, showing an incomplete compensation of differences in activation times. Yue et al. measured in 13 patients, mostly referred for idiopathic monomorphic ventricular tachycardia, ARI with a non-contact mapping system11. They showed that on the endocardial surface ARI compensated for AT, but not over-compensated, as the overall regression slope between activation times and ARIs was -0.76. During sinus rhythm, RTs were better compensated (slope - 0.81) than during premature stimulation (slope -0.61). Summarizing, data on human repolarization is limited and contradicting. The discussed older study shows an overcompensation of depolarization time by the action potential durations. The repolarization pattern measured on either the endo- or epicardium (parallel to the ventricular walls) is suggested to be the reverse of the depolarization pattern. However, the more recent studies discussed here found that repolarization followed the depolarization order at the endocardium. The patients in the above studies were not completely healthy, therefore analysis of the QRS and T vector loops of healthy subjects may provide some additional information regarding the normal sequence of repolarization. Typically, the same global orientation and direction of inscription of the QRS and T loops was found in healthy humans52-54. These properties are in agreement with a similar de- and repolarization order measured parallel to the ventricular walls, from midseptum to apex ending at the lateral base, and a reversed transmural repolarization sequence from epi- to endocardium53. Furthermore, the normal T vector loop points to the apex and is smaller and more elongated than the QRS vector loop. These properties implicate a smaller heteroge21

Chapter 1

neity of repolarization times than of activation times, with a larger apico-basal than transmural repolarization gradient (Figure 5). Figure 5. Proposed normal human repolarization order in accordance with vectorloop morphology

and direction.The heart is shown in a horizontal plane. Transventricular repolarization follows activation sequence from sepum to apex to base. Transmural repolarization gradient is small, but inversely directed from epi- to endocardium.

ECG indices of repolarization heterogeneity Repolarization heterogeneity predisposes to arrhythmias14;15;37. Therefore, a non-invasive index of this repolarization heterogeneity potentially would have great clinical value. More than hundred years after its discovery, the ECG is still an easily available, cheap and valuable diagnostic test. At present, the standard 12-lead configuration is most used in the routine clinical setting. Therefore, we used the 12-lead configuration throughout this thesis. QT interval The traditional electrocardiographic repolarization index is the QT interval, defined as the interval from the start of the earliest QRS complex to the latest end of the T-wave in any lead. The QT interval represents the interval from the earliest depolarization to the end of the repolarization anywhere in the heart. The risk of arrhythmias in long QT patients increases with the duration of the QT(c) interval55. A large proportion of drugs with arrhythmogenic side-effects decrease the 22


rapid delayed rectifier, a repolarizing potassium current, thereby lengthening the QT interval56. Therefore, the American Federal Drug Administration requires QT interval testing for every new drug before market release is authorized. Despite its widespread use, the QT interval has some important limitations as estimator of repolarization heterogeneity. By definition, the QT interval is dependent on the longest action potential durations. However, the duration of the longest action potentials is not related to repolarization heterogeneity per se. For example, amiodarone lengthens the action potential durations homogeneously throughout the ventricular wall and has an anti-arrhythmic effect rather than a pro-arrhythmic effect57. The QT interval varies with heart rate. To estimate the QT interval during varying heart rates, correction factors are needed. The most commonly used formula is Bazett’s58, probably due to its simplicity. QTc = QT / √RR However, the Bazett formula has a tendency to overcorrect the QT interval at fast heart rates and to undercorrect the QT interval at slow heart rates, see Figure 659. Measurement of the end of the T-wave is often difficult due to slowly decreasing slopes at the end of the T-wave, low amplitude T waves and overlap with the P-wave at fast heart rates60. Furthermore, the practical and theoretical disputes to discern the end of the T wave from the U wave have not been settled61;62. A practical solution is often chosen to set the end of T at the crossing of the baseline with the steepest tangent to the descending part of the T wave63 or at the T-U nadir60. In summary, the QT interval represents the end of the repolarization anywhere in the heart and may be useful in conditions which are characterized by a lengthened repolarization. However, the QT interval does not directly assess repolarization heterogeneity.

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Chapter 1

Figure 6. The Bazett formula has a tendency to overcorrect the QT interval at fast heart rates and to undercorrect the QT interval at slow heart rates. Lecocq et al. Am J Cardiol. 1989.

Tapex-end interval More recently, Yan and Antzelvitch proposed the Tapex-end interval, the interval from the apex of the T-wave to the end of the T-wave, to assess transmural repolarization heterogeneity43. Their proposal is based on sophisticated experiments in a wedge preparation of the left ventricular free wall of canine hearts64. As stated before, their findings appoint the midmyocardial M-cells as the cells with the longest APD. The APD of these cells were reflected in the end of the T wave in the pseudo-ECG they recorded across the preparation (Figure 7). The epicardial cells appeared to have the shortest APDs and the end of the repolarization in these cells coincided with the moment of the apex of the T-wave. They concluded that the Tapex-end interval is therefore a measure of the difference between the epicardial and mid-myocardial repolarization times, i.e., transmural repolarization heterogeneity. Their experiments provide pathophysiological insight in various forms of long QT syndrome. A large number of drugs with arrhythmic side effects are known to inhibit the delayed rectifier current. In wedge experiments these properties were shown to

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preferentially lengthen the APD of cells with already the longest APD, the APD of the M cells. This increases the differences in repolarization time between M-cells and surrounding cells, thereby increasing repolarization heterogeneity and facilitating arrhythmias, which could be induced even in a small preparation as the wedge preparation65. Congenital long QT syndrome, types 1, 2 and 3 were mimicked in the wedge with respectively, IKs, IKr and INa inhibition66;67. These experiments showed that transmural repolarization heterogeneity was the culprit for torsade de pointeslike arrhythmias, and that transmural dispersion was adequately reflected in the Tapex-end interval in the pseudoFigure 7. The apex and the end of the T-wave re- ECG of the wedge preparation. corded in the pseudo-ECG were linked to the repo- Although their experiments were ellarization of different cell layers in the ventricular wall. The end of repolarization of the cells with the egant and insightful, the finding that longest APDs, the midmyocardial M-cells, coincided Tapex-end was a measure of transmuwith the end of the T wave. The end of repolariza- ral dispersion of the repolarization in tion of the cells with the shortest APDs, the epicarthe pseudo-ECG, recorded across the dial cells, coincided with apex of the T wave. Yan and Antzelevitch. Circulation 1998. wedge preparation, led to the assumption that these findings could be ex68-70 trapolated to the surface ECG . This, however, is unlikely. First of all, one would need a transmural ECG. This is definitely not the case in ECG leads recorded with electrodes at some distance from the heart, i.e., the limb leads and leads V5 and V6. Laws of physics prescribe that at every moment all leads register the electrical field generated by the heart and that the amplitude of a recorded potential is inversely dependent on the squared distance from the source. Even if in leads V2, V3 and V4, which are recorded from electrodes overlying the heart, would reflect some local information, this would be a composite of information obtained from the right ven25

Chapter 1

tricle and information from the anterior wall of the left ventricle. Therefore also these precordial leads do not reflect pure transmural dispersion of the repolarization. The apex of the T-wave is probably inscribed when, spreaded across the heart, most cells simultaneously repolarize. The end of the T wave is inscribed when the cells with the longest APD, wherever in the heart, are repolarized. So the Tapex-end interval has an indirect link with repolarization heterogeneity generated in the whole heart71. These theoretical deductions were recently evaluated by detailed mapping studies using more than 50 epi- and endocardial monophasic action potential recordings in pigs. In these experiments, the apex of the T wave coincided with the earliest repolarization of cells anywhere in the heart while the end of the T wave was recorded when the last cells repolarized, which were endocardial cells in nine out of ten pigs72. During electrical stimulation the origin of the Tapex-end interval is completely different. The Tapex-end interval is related to the progression of the repolarization wave front spreading from the pacing electrode through the heart73. The slow myocardial cell-to-cell activation has a significant influence on the de- and repolarizing time of the cells, so that not only the depolarization but also the repolarization spreads from the site of stimulation through the heart. The opposite direction of the repolarizing current compared to the depolarizing current causes an opposite orientation of the T-wave compared to the QRS complex observed during pacing. During abnormal, slow activation the Tapex-end interval is related to the interval from the moment the repolarization wave front approximately attains is maximal surface area (Tapex) to the moment when the last parts of heart repolarize (Tend). The areas of the heart that repolarize last are the areas that are geometrically and electrophysiologically farthest away from the pacing electrode. In chapter 5, the behavior of the Tapex-end interval during pacing is further clarified. QT dispersion In 1990, QT dispersion, calculated as the longest minus the shortest QT interval in any of the 12 standard ECG leads, was introduced as a marker of local repolarization heterogeneity74. Promising initial studies, in which QT dispersion was associated with arrhythmic risk74;75, triggered a large number of studies on this new ECG index. More than 850 publications can be currently retrieved (April 2006). However, more recently, QT dispersion as a measure of local heterogeneity came under serious 26


criticism76;77. QT-interval differences in ECG leads depend on different projections of the (global) heart vector on the 12 lead vectors. The end of the QT interval in an ECG lead is partly determined by the angle of the terminal T vector with the lead vector76. A terminal T vector that is directed perpendicular to a lead vector, is not registered in that lead and shortens the QT interval. Therefore, the end of the T-wave in a certain lead can not be interpreted as the end of repolarization in the myocardial region closest to that lead. Thus, QT dispersion does not represent local repolarization differences. An additional problem of QT dispersion is the low reproducibility78;79, for example due to the subjectivity involved in exclusion of low-amplitude T waves and the difficult measurement of the end of T waves in noisy ECGs. These insights strengthened the opposition against QT dispersion80-82. Nevertheless, QT dispersion may have a weak relation with repolarization disturbances and was associated with arrhythmias in some studies83;84. A large QT dispersion is for example found in patients with low amplitude T waves. Low amplitude T waves can be caused by triangulation of the APD85, which is thought to be related to a decreased repolarization reserve in, for example, patients with the long QT syndrome, i.e., the patient group in which the initial promising results were found74. Articles providing data on the risk-estimating capabilities of QT dispersion are still frequently published. Although QT dispersion is an indirect measure of repolarization heterogeneity, QT dispersion remains in use, probably due to habituation and its accessibility. T-wave amplitude T-wave amplitude, the maximal amplitude of the T-wave or the apex of the T-wave, reflects the maximal potential difference in the heart during the repolarization. The larger the differences in duration and amplitude of action potentials from different parts of the myocardium, the higher the T-wave amplitude becomes86. Syndromes or conditions associated with heterogeneity of the repolarization causing large-amplitude T waves are long QT syndrome type 1 and hyperkalemia. The high amplitude T waves of long QT-1 syndrome were realistically mimicked in wedge preparations of the canine left ventricular wall66. An IKs blocker in combination with isoprenaline caused a relatively long APD in the M-cells, causing a high amplitude T wave in the pseudo-ECG recorded across the ventricular wall. These findings concur with the observed propensity for arrhythmias in long QT 1 patients associated with exercise87;88. Hyperkalemia is well known to cause high amplitude T waves and ar27

Chapter 1

rhythmias, likely to be due to increased repolarization heterogeneity89. Furthermore, in the acute phase of myocardial infarction the AP of the infarcted cells changes; the upstroke velocity falls, maximum amplitude dips and APD shortens90. This causes potential differences between injured and normal cells and a systolic “injury” current directed from normal to ischemic cells. These injury currents cause ST elevation and increased T-wave amplitude. Although T-wave amplitude is an indicator of repolarization heterogeneity in the above conditions, T-wave amplitude is insensitive or even misleading to certain other changes in AP morphology. Triangulation of APs in response to pro-arrhythmogenic drugs is associated with increased repolarization heterogeneity and decreases T-wave amplitude91. Also, long QT syndrome type 2 is typically associated with low amplitude T waves92. Furthermore, a high inter-individual variation in T-wave amplitude exists due to variations in body fat and internal ventricular diameter. Additionally, cancellation has a strong influence on the T-wave amplitude. Based upon animal and modeling studies Abildskov and Klein assessed the amount of cancellation during ventricular depolarization to be approximately two thirds of locally generated potential differences93. Based upon measurements of refactoriness by Durrer32, Burgess and Abildskov assessed the amount of cancellation during repolarization even more than 90 %, due to opposed directions of repolarization vectors within the wall94. The lower T-wave amplitude observed during biventricular pacing compared to single sided pacing is probably caused by a larger cancellation of two repolarization wave fronts instead of one wave front73;94. In conclusion, the use of T-wave amplitude as a measure of repolarization heterogeneity has serious limitations, but T-wave amplitude may be an accurate reflection of repolarization heterogeneity in specific conditions. T-wave area T-wave area reflects magnitude and duration of repolarization differences throughout the heart. Several studies showed a relation between repolarization heterogeneity, assessed from a limited number of action potential recordings, and T-wave area. T-wave area correlated with increased repolarization heterogeneity in rabbit hearts measured by epicardial monophasic action potentials95 In dogs, T-wave96 and QRST97 surface area was related to repolarization heterogeneity and a lowered threshold for ventricular fibrillation.98 Drugs that lengthen APD of specific cell layers, for ex28


ample, IKr blockers that foremost lengthen midmyocardial APD, cause an increased T-wave area in left ventricular wedge experiments99. Mathematical simulation studies confirmed these experimental findings. Human heart-in-thorax models showed that increased repolarization heterogeneity resulted in increased T-wave area100;101, as presented in chapter 4 of this thesis101. T-wave area can be determined in individual leads or in the vector magnitude constructed by means of the inverse Dower matrix102;103. T-wave area can be objectively and automatically measured. Furthermore, this index is relatively insensitive to noise. Small, peaked oscillations will average out, having little influence on total T-wave area. Its disadvantage is, like T-wave amplitude, a high inter-individual variation which makes individual risk assessment difficult if only one ECG is available. Serial ECG analysis started before a potentially pro-arrhythmic event would therefore be more suited to evaluate repolarization heterogeneity by measurement of T-wave area. QRS-T angle An increased QRS-T angle is predictive for (sudden) death. Kardys et al. showed that a wide QRS-T angle predicted cardiac death in a general population of more than 6000 men and women older than 55 years 104. After adjustment for cardiovascular risk factors, hazard ratios of abnormal QRS-T angles for sudden death were 4.6 (CI 2.5-8.5). Zabel et al. tested five ECG variables of T-wave morphology in patients after myocardial infarction 105. Only the spatial angle between depolarization and repolarization was shown to contribute to the risk stratification of these patients, independent of classical risk factors. Other studies underscored the prognostic value of the spatial QRS-T angle and the orientation of the T axis 106-108 The spatial angle between the QRS and T vectors is normally 78 ± 26º 109. A small QRS-T angle is caused by a similar direction of de- and repolarization. Several pathologies may cause a wide QRS-T angle. An altered activation pattern may cause a similar de- and repolarization sequence as described in the paragraph on the Tapexend interval. Due to the similar de- and repolarization order, but opposite direction of the currents, the QRS and T vectors then attain an opposite direction, and a large QRS-T angle. Furthermore, ischemia may alter the repolarization process and the direction of the T vector. Any other condition that disturbs the normal distribu29

Chapter 1

tion of the action potential durations throughout the heart may increase the QRS-T angle. The multitude of pathologies that may cause an increased QRS-T angle explains the excellent predictive value of this ECG index. Therefore, an increased QRS-T angle is a final common pathway and not very specific for increased repolarization heterogeneity. Nevertheless, this ECG index can be measured accurately (and automatically) and may therefore be useful as a general indicator of the electrophysiological status of the cardiac patient. T-wave complexity Methods used to describe the complexity of the T wave are essentially morphological descriptors of the T-waves in the ECG. We used singular value decomposition to calculate T-wave complexity in this thesis. Singular value decomposition was introduced in cardiology as an algebraic algorithm to distillate non-redundant signals from multiple leads (up to 200) obtained with body surface mapping. We used singular value decomposition to reconstruct the T waves of the eight independent ECG leads (I, II, V1-6) into 8 independent components that are by definition orthogonal to each other (Figure 8). If the T waves can be described by only the first few components, the T waves have a relatively simple shape and are similar to each other in the different leads. The more components are needed to accurately describe the T waves and thus contain a significant amount of information, the more complex the T waves. The energy contained in the eight components is quantified by the corresponding singular values. To calculate T-wave complexity, we divided the higher, more complex singular values 2 to 8 by the first, most simple singular value. Another variation we and others used was the ratio of the second to the first singular value110. Although one influential group used the absolute value of the singular values 4-8111, according to our observations, these highest singular values have a low signal-to-noise ratio. Nevertheless, this method appears to have prognostic capabilities112;113. Furthermore, T-wave complexity has been shown to yield independent prognostic information in patients with cardiovascular disease113. In patients with arrhythmogenic right ventricular dysplasia, higher T-wave complexity is associated with arrhythmias 114. Additionally, T-wave complexity is increased in patients with primary repolarization disturbances and can be used to discriminate these patients from healthy individuals 110 . Van Oosterom mathematically proved that a higher repolarization heterogeneity leads to increased T-wave complexity.115 30


Figure 8. Singular value decomposition was used to reconstruct the T waves of the eight independent ECG leads (I, II, V1-6) into 8 independent components that are by definition orthogonal to each other.

Our opening statement that T-wave complexity is essentially an index of the morphology of the T wave can now be further refined. T-wave complexity is related to the simplicity of the T-wave form; a smooth T-wave that is similar in different leads can be described by fewer singular values than an irregularly shaped T-wave. Although every clinician knows that irregular T-wave morphology deflects an abnormal repolarization, the advantage of singular value decomposition is the objective quantification of T-morphology aberrancy. Ventricular gradient The concept of the ventricular gradient was originally formulated by Wilson in 193129. The ventricular gradient is calculated by summation of the integral of the spatial depolarization and repolarization vectorloops. This results in the gradients of

31

Chapter 1

AP differences only, while excluding the influence of the depolarization order. When activating the heart from an ectopic focus (as a ventricular extra stimulus), the ventricular gradient was supposed to remain unaltered as the ventricular gradient reflected heterogeneity of action potential (duration and amplitude) and not the activation order. Despite the attractive theoretical background, APD appeared to be influenced by the depolarization order. Adaptation of the APD to activation order that persists after restoration of the original activation order is apparent even after a short time of ectopic activation, a phenomenon which is called T-wave memory116. Furthermore, the direction of the activation wavefront compared to the fiber direction has an effect on APD117. Moreover, the mechanism of arrhythmogenesis is dependent on repolarization differences, which is the resultant of activation and APD; or more specifically refractoriness, which has been shown to facilitate re-entry arrhythmias. Nevertheless, the ventricular gradient still reflects the APD heterogeneity, whether this APD pattern is modified by the activation pattern or not. The ventricular gradient remains an interesting concept in research-oriented ECG analysis. The ventricular gradient can be particularly useful to discern between primary and secondary repolarization changes. Aim and outline of the thesis Repolarization changes due to several interventions were evaluated by measurement of several ECG indices of repolarization heterogeneity in several groups of healthy subjects and patients. Detailed study of different ECG indices in different patient groups may provide insight in their behavior and may guide the appropriate use of these electrocardiographic indices of repolarization heterogeneity. In chapter 2 healthy males are subjected to normotensive stress (modified tilt testing) and hypertensive stress (handgrip). Different tilt angles of the legs are applied to achieve the same heart rate during both stressors to be able to compare the effects of these stressors on electrocardiographic indices of repolarization heterogeneity without the errors introduced by heart rate correction. An increase in sudden cardiac death has been observed during or immediately after exercise. In chapter 3 we measure electrocardiographic indices of repolarization heterogeneity during and after maximal exercise testing. The fitness level of the subjects varied from professional marathon ice skaters to untrained subjects. The response to vigorous exercise is compared in athletes with the largest hearts to the untrained subjects. 32


Electrocardiographic indices may differ in their reaction on increasing repolarization heterogeneity. In chapter 4 a mathematical ECG simulation model is used to observe whether various ECG indices adequately reflect increasing local repolarization heterogeneity. In chapter 5 the electrocardiographic effects of pulmonary valve replacement in Fallot patients with dilated right ventricles are studied. In these patients QRS duration is known to be predictive of ventricular arrhythmias. We use an interactive ECG analysis program to accurately measure the QRS duration before and a half year after surgery. Changes in right ventricular end-diastolic volumes were previously studied with cardiac magnetic resonance imaging and are incorporated in the present study. In chapter 6 we extend the analysis of the Fallot patients with electrocardiographic indices proposed to measure repolarization heterogeneity. We measure the changes in these indices due to pulmonary valve replacement and study the possible relation with arrhythmias. Previous studies on cardiac resynchronization therapy have suggested a detrimental effect of epicardial pacing on the transmural repolarization heterogeneity, causing arrhythmias in vulnerable patients, who can be identified by electrocardiographic evaluation. In chapter 7 we study the effects of different pacing modes of cardiac resynchronization devices on electrocardiographic indices of repolarization heterogeneity. Subsequently we use a simulation model to interpret the electrocardiographic findings from our heart failure patients.

33

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91. 92.

93. 94. 95. 96. 97. 98. 99. 100.

potential predict serious proarrhythmia, but action potential duration prolongation is antiarrhythmic. Circulation. 2001;103:2004-2013. van Oosterom A. Genesis of the T wave as based on an equivalent surface source model. J Electrocardiol. 2001;34 Suppl:217-227. Moss AJ, Robinson JL, Gessman L, Gillespie R, Zareba W, Schwartz PJ, Vincent GM, Benhorin J, Heilbron EL, Towbin JA, Priori SG, Napolitano C, Zhang L, Medina A, Andrews ML, Timothy K. Comparison of clinical and genetic variables of cardiac events associated with loud noise versus swimming among subjects with the long QT syndrome. Am J Cardiol. 1999;84:876-879. Wilde AA, Roden DM. Predicting the long-QT genotype from clinical data: from sense to science. Circulation. 2000;102:2796-2798. Wan X, Bryant SM, Hart G. The effects of [K+]o on regional differences in electrical characteristics of ventricular myocytes in guinea-pig. Exp Physiol. 2000;85:769774. Kleber AG, Janse MJ, van Capelle FJ, Durrer D. Mechanism and time course of S-T and T-Q segment changes during acute regional myocardial ischemia in the pig heart determined by extracellular and intracellular recordings. Circ Res. 1978;42:603-613. Shah RR, Hondeghem LM. Refining detection of drug-induced proarrhythmia: QT interval and TRIaD. Heart Rhythm. 2005;2:758-772. Zhang L, Timothy KW, Vincent GM, Lehmann MH, Fox J, Giuli LC, Shen J, Splawski I, Priori SG, Compton SJ, Yanowitz F, Benhorin J, Moss AJ, Schwartz PJ, Robinson JL, Wang Q, Zareba W, Keating MT, Towbin JA, Napolitano C, Medina A. Spectrum of ST-T-wave patterns and repolarization parameters in congenital long-QT syndrome: ECG findings identify genotypes. Circulation. 2000;102:28492855. Abildskov JA, Klein RM. Cancellation of electrocardiographic effects during ventricular excitation. Sogo Rinsho. 1962;11:247-251. Burgess MJ, Millar K, Abildskov JA. Cancellation of electrocardiographic effects during ventricular recovery. J Electrocardiol. 1969;2:101-107. Zabel M, Portnoy S, Franz MR. Electrocardiographic indexes of dispersion of ventricular repolarization: an isolated heart validation study. J Am Coll Cardiol. 1995;25:746-752. van Opstal JM, Verduyn SC, Winckels SK, Leerssen HM, Leunissen JD, Wellens HJ, Vos MA. The JT-area indicates dispersion of repolarization in dogs with atrioventricular block. J Interv Card Electrophysiol. 2002;6:113-120. Abildskov JA, Green LS, Evans AK, Lux RL. The QRST deflection area of electrograms during global alterations of ventricular repolarization. J Electrocardiol. 1982;15:103-107. Kubota I, Lux RL, Burgess MJ, Abildskov JA. Relation of cardiac surface QRST distributions to ventricular fibrillation threshold in dogs. Circulation. 1988;78:171177. Shimizu W, Antzelevitch C. Sodium channel block with mexiletine is effective in reducing dispersion of repolarization and preventing torsade des pointes in LQT2 and LQT3 models of the long-QT syndrome. Circulation. 1997;96:2038-2047. di Bernardo D, Murray A. Explaining the T-wave shape in the ECG. Nature.

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Chapter 1 2000;403:40. 101. Hooft van Huysduynen, B., Swenne, C. A., Draisma, H. H. M., Antoni, M. L., Van de Vooren, H., Van der Wall, E. E., and Schalij, M. J. Validation of ECG Indices of Ventricular Repolarization Heterogeneity: A Computer Simulation Study. J Cardiovasc Electrophysiol. 2005;16:1097-103. 102. Dower GE, Machado HB, Osborne JA. On deriving the electrocardiogram from vectoradiographic leads. Clin Cardiol. 1980;3:87-95. 103. Edenbrandt L, Pahlm O. Vectorcardiogram synthesized from a 12-lead ECG: superiority of the inverse Dower matrix. J Electrocardiol. 1988;21:361-367. 104. Kardys I, Kors JA, van dM, I, Hofman A, van der Kuip DA, Witteman JC. Spatial QRS-T angle predicts cardiac death in a general population. Eur Heart J. 2003;24:1357-1364. 105. Zabel M, Acar B, Klingenheben T, Franz MR, Hohnloser SH, Malik M. Analysis of 12-lead T-wave morphology for risk stratification after myocardial infarction. Circulation. 2000;102:1252-1257. 106. de Torbal A, Kors JA, van Herpen G, Meij S, Nelwan S, Simoons ML, Boersma E. The electrical T-axis and the spatial QRS-T angle are independent predictors of long-term mortality in patients admitted with acute ischemic chest pain. Cardiology. 2004;101:199-207. 107. Kors JA, de Bruyne MC, Hoes AW, van Herpen G, Hofman A, van Bemmel JH, Grobbee DE. T axis as an indicator of risk of cardiac events in elderly people. Lancet. 1998;352:601-605. 108. Rautaharju PM, Nelson JC, Kronmal RA, Zhang ZM, Robbins J, Gottdiener JS, Furberg CD, Manolio T, Fried L. Usefulness of T-axis deviation as an independent risk indicator for incident cardiac events in older men and women free from coronary heart disease (the Cardiovascular Health Study). Am J Cardiol. 2001;88:118-123. 109. Draper HW, Peffer CJ, Stallmann FW, Littmann D, Pipberger HV. The corrected orthogonal electrocardiogram and vectorcardiogram in 510 normal men (Frank lead system) Circulation. 1964;30:853-864. 110. Priori SG, Mortara DW, Napolitano C, Diehl L, Paganini V, Cantu F, Cantu G, Schwartz PJ. Evaluation of the spatial aspects of T-wave complexity in the long-QT syndrome. Circulation. 1997;96:3006-3012. 111. Acar B, Yi G, Hnatkova K, Malik M. Spatial, temporal and wavefront direction characteristics of 12-lead T-wave morphology. Med Biol Eng Comput. 1999;37:574584. 112. Okin PM, Malik M, Hnatkova K, Lee ET, Galloway JM, Best LG, Howard BV, Devereux RB. Repolarization abnormality for prediction of all-cause and cardiovascular mortality in American Indians: the Strong Heart Study. J Cardiovasc Electrophysiol. 2005;16:945-951. 113. Zabel M, Malik M, Hnatkova K, Papademetriou V, Pittaras A, Fletcher RD, Franz MR. Analysis of T-wave morphology from the 12-lead electrocardiogram for prediction of long-term prognosis in male US veterans. Circulation. 2002;105:10661070. 114. De Ambroggi L, Aime E, Ceriotti C, Rovida M, Negroni S. Mapping of ventricular repolarization potentials in patients with arrhythmogenic right ventricular dysplasia: principal component analysis of the ST-T waves. Circulation.

40

Introduction: Electrocardiographic assessment of repolarization heterogeneity 1997;96:4314-4318. 115. van Oosterom A. Singular value decomposition of the T wave: its link with a biophysical model of repolarization. Int J Bioelectromagnetism. 2002;4:59-60. 116. Rosenbaum MB, Blanco HH, Elizari MV, Lazzari JO, Davidenko JM. Electrotonic modulation of the T wave and cardiac memory. Am J Cardiol. 1982;50:213-222. 117. Osaka T, Kodama I, Tsuboi N, Toyama J, Yamada K. Effects of activation sequence and anisotropic cellular geometry on the repolarization phase of action potential of dog ventricular muscles. Circulation. 1987;76:226-236.

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Chapter 2 Validation of ECG indices of ventricular repolarization heterogeneity A computer simulation study

Bart Hooft van Huysduynen Cees A. Swenne Harmen H.M. Draisma M. Louisa Antoni Hedde van de Vooren, Ernst E. van der Wall Martin J. Schalij

J Cardiovasc Electrophysiol 2005; 16: 1097-103

43

Chapter 2

ABSTRACT Introduction. Repolarization heterogeneity is functionally linked to dispersion in refractoriness and to arrhythmogeneity. In the current study we validate several proposed ECG indices for repolarization heterogeneity: T-wave amplitude, -area, -complexity and -symmetry ratio, QT dispersion, and the Tapex-end interval (the latter being an index of transmural dispersion of the repolarization). Methods and results. We used ECGSIM, a mathematical simulation model of ECG genesis in a human thorax, and varied global repolarization heterogeneity by increasing the standard deviation (SD) of the repolarization instants from 20 (default) to 70 ms in steps of 10 ms. T-wave amplitude, -area, -symmetry and Tapex-end depended linearly on SD. T-wave amplitude increased from 275 ± 173 to 881 ± 456 µV, T-wave area from 34·103 ± 21·103 to 141·103 ± 58·103 µV·ms, T-wave symmetry decreased from 1.55 ± 0.11 to 1.06 ± 0.23 and Tapex-end increased from 84 ± 17 to 171 ± 52 ms. T-wave complexity increased initially but saturated at SD = 50 ms. QT dispersion increased modestly until SD = 40 ms and more rapidly for higher values of SD. Transmural dispersion of the repolarization increased linearly with SD. Tapex-end increased linearly with transmural dispersion of the repolarization, but overestimated it. Conclusion. T-wave complexity did not discriminate between differences in larger repolarization heterogeneity values. QT dispersion had low sensitivity in the transitional zone between normal and abnormal repolarization heterogeneity. In conclusion, T-wave amplitude, -area, -symmetry, and, with some limitations, Tapex-end and T-wave complexity reliably reflect changes in repolarization heterogeneity.

44

INTRODUCTION Cardiac repolarization is more spread in time than cardiac depolarization because of regional differences in action potential duration (APD). Functionally, repolarization heterogeneity (RH) is closely related to dispersion in refractoriness, which in turn increases the vulnerability to reentrant arrhythmias.1;2 RH has been described between the apex and basal areas of the heart,3 between the left and right ventricles4 and between the epicardium, mid-myocardium and endocardium.5 The latter type of RH has been named transmural dispersion of the repolarization (TDR). Primary electrical disease as well as several drugs are known to exaggerate action potential differences in the heart, thus increasing RH and arrhythmia risk. A noninvasive, electrocardiographic index of RH would therefore be of great clinical value.6 Several ECG indices to assess RH have been proposed, like the amplitude of the T-wave7 (Tamplitude), T-wave surface area8 (Tarea), symmetry ratio of the T wave9 (Tsymmetry), complexity of the T wave calculated by singular value decomposition10 (Tcomplexity) and QT dispersion.11 The Tapex-end interval in the left precordial leads (Tapex-end) has been put forward as a measure that directly assesses the duration of TDR.12 Although clinical studies have shown that most of these ECG parameters have prognostic power,13-15 it remains unknown if they really assess RH. Whole heart studies in which endo- and epicardial repolarization as well as surface ECGs are recorded are scarce. Most whole-heart biological models of ECG genesis only measure either epicardial or endocardial dispersion,16,17 thus completely ignoring TDR. Tapex-end, currently the only index that assesses TDR duration, has been validated on the basis of a quasi-ECG obtained from transmural recordings of a wedge preparation of the left ventricular wall,12 but not in a whole heart and torso model. In the current study, we sought to validate the above mentioned electrocardiographic indices of RH by using a mathematical simulation model of ECG genesis of a human heart in a thorax.18 Within this model, we increased the heterogeneity of the action potential durations throughout the heart and measured the consequences of these manipulations for TDR and RH, and for the ECG indices of ventricular repolarization heterogeneity.

45

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METHODS ECGSIM ECGSIM, an interactive computer program conceived and realized by Van Oosterom and Oostendorp,18 is a mathematical model for studying QRST waveform genesis. The model is available in the public domain at www.ecgsim.org. It is a combination of a source model of the heart and a volume conductor model of the torso. The heart is a double layer model in which all electrical activity is represented by equivalent sources on the surface encompassing the ventricular myocardium. This surface, of which the shape has been derived from magnetic resonance imaging data, consists of 257 nodes. Each node has its own electrophysiological properties in the form of a transmembrane action potential, in which the timing of the depolarization, the timing of the maximal negative slope and the magnitude of the transmembrane potential can be changed. The default action potential (AP) onset sequence represents normal conduction of the impulse, and APD differences throughout the heart represent the natural apex-to-base and endo-to-epicardial APD heterogeneity. The heart is placed in a realistic thorax model based on magnetic resonance imaging data and includes conductance inhomogeneities like the lungs. With default parameter settings, ECGSIM generates potentials on the thoracic surface that closely resemble those of a healthy subject. ECGSIM allows for simulations of pathological conditions such as abnormal activation sequences or, by adjusting the magnitude of the transmembrane potential, for simulations of acute ischemia. For the current study, the default, normal settings for activation sequence and source strengths were kept throughout the simulations. Manipulation of repolarization heterogeneity We adopted the standard deviation of the repolarization times of all 257 nodes (SDrep) as a measure of RH (repolarization times in the model are defined as the moments of maximum downslope of the transmembrane action potential). Different levels of SDrep were obtained by increasing the standard deviation of the action potential durations (SDAPD). By setting the model parameter SDAPD at different levels, all 257 APDs are modified without changing the mean APD. Because each node’s repolarization time is calculated by adding its APD to its activation time, an increase of SDAPD increases SDrep as well. In the current version of ECGSIM the model parameter SDAPD can assume a number of discrete values.18 SDAPD values were set 46

Validation of ECG indices of ventricular repolarization heterogeneity

in such a way that SDrep increased in steps of approximately 10 ms. Thus, SDrep was increased from the default value of 20.8 ms to 30.7, 40.6, 51.1, 60.6, and finally to a maximum of 70.7 ms. Sinus rhythm at a rate of 60 beats per minute was maintained during all simulations. As a control experiment, we evaluated the effects of homogeneous APD lengthening on the ECG repolarization indices in the measurable leads. The APDs of all nodes were lengthened to the same extent by increasing the mean APD from 245.1 ms at baseline to 319.0 ms and 395.0 ms, respectively. Calculation of transmural dispersion of the repolarization In the 257 node model, 42 / 61 nodes constitute the endo / epicardium of the free left ventricular wall, 54 / 70 nodes the endo / epicardium of the right ventricular wall and 14 / 16 nodes the left / right septum. Most endocardial nodes were paired with one opposing epicardial node, and TDR was calculated as differences in repolarization time between the endo- and epicardial node. However, as there are more epicardial than endocardial nodes, some endocardial nodes had two opposing epicardial nodes. In these cases, the difference was calculated between the repolarization time of the endocardial node and the mean repolarization time of the two opposing epicardial nodes. Similarly, each left ventricular septal node was paired with one or two right ventricular septal nodes. Subsequently, all paired repolarization time differences were averaged to calculate TDR. ECG analysis The simulated ECGs were analyzed by LEADS (Leiden ECG Analysis and Decomposition Software), our MATLAB (The MathWorks, Natick, USA) program for research oriented ECG analysis. LEADS identifies the apex and end of the T wave in each ECG lead. The end of the T wave was defined as the point where the tangent to the steepest portion of the terminal part of the T wave crosses the isoelectric line. Thereafter, the low amplitude T waves in lead V1 were excluded because these led to erroneous detection of the apex and end of the T wave. LEADS calculated Tapex-end, Tamplitude and Tarea in every measurable lead and in the vector magnitude signal computed from the vectorcardiogram constructed

47

Chapter 2

by using the inverse Dower matrix.19,20 Tsymmetry was calculated in all measurable leads as the ratio of the early T-wave area, from the J point to the apex of the T wave, to the late T wave area, from the T wave apex to the end of the T wave.9 Finally, the values of Tapex-end, Tamplitude, Tarea, Tsymmetry in all measurable leads were averaged. Calculation of repolarization complexity was performed by means of singular value decomposition (SVD) of the T-wave.10;21 SVD was computed over an interval starting 50 ms after the J point until 50 ms after the end of the T-wave. We computed the SVD-based Tcomplexity as the square root of the summed second to eighth singular values divided by the first singular value. QT dispersion was calculated as the longest minus the shortest measurable QT interval in any of the 12 standard ECG leads.

48


RESULTS Two example ECGs generated with the default, low level of RH (SDrep = 20.8 ms) and with a high level of RH (SDrep = 70.7 ms) are depicted in Figure 1, panels A and B, respectively. Figure 1a. Twelve-lead ECG as generated by ECGSIM with default, low repolarization heterogeneity (standard deviation of the repolarization times = 20.8 ms). As ECGSIM models the ventricular electrical depolarization/repolarization, no P waves are present. The signals were baseline corrected in ESGSIM and one complex is given for each lead.

Figure 1b. Twelve-lead ECG generated by ECGSIM with high repolarization heterogeneity (standard deviation of the repolarization times = 70.7 ms).

49

Chapter 2

SDrep increased linearly with the SDAPD, in an almost 1:1 relationship: SDrep = 0.97 · SDAPD - 7.0 (r2 = 0.99). The average absolute TDR in the left ventricle, septum, right ventricle and whole heart all related linearly to SDrep (Figure 2). The slope of TDR of the right ventricle (0.72) was smaller than the slope of the left ventricle (1.04) and the septum (0.95), while the whole heart slope assumed an intermediate value (0.90). All these relationships had a correlation coefficient of 0.99.

Figure 2. Relation between the standard deviation of the repolarization times (SDrep) and the averaged absolute transmural dispersion of the repolarization (TDR) in the right ventricle, left ventricle, septum and whole heart.

Linear regression plots of Tapex-end in the left precordial leads as a function of TDR in the free wall of the left ventricle are depicted in Figure 3. The relationship of the Tapex-end in leads V4-6 with RH were all linear with correlations ≥ 0.99. Tapexend in leads V2 and V3 showed a discontinuity when T waves became biphasic at increasing RH levels; in lead V2 at an SDrep of 30 ms and in lead V3 at an SDrep of 50 ms. Tapex-end overestimated TDR in all left precordial leads.

50


Figure 3. Relation between the transmural dispersion of the repolarization (TDR) in the left ventricular free wall and the Tapex-end in the left precordial leads. Discontinuities in the V2 and V3 data are caused by a transition from a monophasic to a biphasic T wave. (dashed line = line of identity)

Tapex-end, Tamplitude, Tarea and Tsymmetry The relationships of Tapex-end, Tamplitude, Tarea and Tsymmetry with RH were close to perfectly linear (Tables 1a and b). Table 1a lists values that were averaged over the ECG leads in which the respective RH index could be measured (lead V1 had to be excluded because of a low amplitude T wave). The RH indices were also measured in the vector magnitude signal (Table 1b). All linear regressions had correlations of at least 0.98. Regressions with the vector magnitude derived indices had generally steeper slopes than those with the average of the ECG leads. All RH indices but Tsymmetry had a positive relation with RH.

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Chapter 2

Averaged over ECG leads

slope

intercept

r2

Value at baseline RH SDrep = 20.8

Value at maximal RH SDrep = 70.7

Tapex-end (ms)

1.7

48

0.99

84 ± 17

171 ± 52

Tamplitude (µV)

12.1

48

0.99

275 ± 173

881 ± 456

2.1·103

-11·103

0.99

34·103 ± 21·103

141·103 ± 58·103

-0.01

1.72

0.98

1.55 ± 0.11

1.06 ± 0.23

Tarea (µV·ms) Tsymmetry

Table 1a. Slope, intercept and correlation (r2) of the linear regressions of Tapex-end, Tamplitude, Tarea and Tsymmetry on repolarization heterogeneity (RH) and the value of these RH indices at minimal and maximal RH.

In vector magnitude signal

slope

intercept

r2

Value at baseline RH SDrep = 20.8

Value at maximal RH SDrep = 70.7

Tapex-end (ms)

2.7

60

0.99

116

252

Tamplitude (µV)

16.7

86

0.99

403

1253

Tarea (µV·ms)

3.4·103

-19·103

0.99

52·103

221·103

Tsymmetry

-0.012

1.60

0.99

1.39

0.78

Table 1b. Slope, intercept and r2 of the linear relations of Tapex-end, Tamplitude, Tarea and Tsymmetry with RH and the value of these indices at minimal and maximal values of RH.

52


Tcomplexity Tcomplexity increased initially and saturated at about SDrep ≥ 40 ms, see Figure 4. Tcomplexity increased from 0.13 at default to 0.18 at an SDrep of 40 ms and remained 0.19 while SDrep increased from 50 to 70 ms.

Figure 4. Relation between the standard deviation of the repolarization times (SDrep) and the T-wave complexity as expressed by the ratio of the 2nd-8th components to the first component in the vectorcardiogram. For visual support we fitted a line through the six data points by a 5th order polynomial. The figure shows that the sensitivity to changes in repolarization heterogeneity decreases at higher heterogeneity values.

QT dispersion QT dispersion increased modestly at low and intermediate levels of RH and more rapidly at higher levels of RH, see Figure 5. QT dispersion increased from 58 ms at default to 68 and 85 ms at SDrep = 30 and SDrep = 40 ms, respectively. Thereafter, QT dispersion increased more rapidly to 102, 137 and 171 ms. The slope of the regression line for SDrep ≤ 40 ms was 1.4 and the slope of the regression line for SDrep ≥ 50 ms was 3.5. 53

Chapter 2

Figure 5. Relation between the standard deviation of the repolarization times (SDrep) and QT dispersion. QT dispersion is sensitive to changes in the repolarization heterogeneity in the very pathological zone (slope 3.5), but has a lower sensitivity in the transitional zone between normal and abnormal (slope 1.4). Therefore this parameter is not well suited to discriminate between normal and abnormal repolarization heterogeneity.

Homogeneous APD lengthening Homogeneous APD lengthening resulted in no apparent morphological T-wave changes, only the ST segment lengthened. Changes in Tapex-end, Tamplitude, Tarea and QT dispersion due to homogeneous APD lengthening were less than 3 % of the changes due to SDrep increase. Only Tsymmetry and T complexity decreased considerably, 19 % and 47 % of the changes due SDrep increase, respectively. These changes were in opposite direction to the changes induced by increasing SDrep.

54

DISCUSSION In this modeling study, we evaluated the effects of repolarization heterogeneity on electrocardiographic indices proposed to assess repolarization heterogeneity. The observed changes in the ECG indices were not caused by APD lengthening per se, as homogeneous APD lengthening caused only minor changes in most ECG indices, and counteracted rather than contributed to the changes in the other ECG indices due to RH increase. Tapex-Tend interval Tapex-end is the only measure that potentially estimates the time window during which repolarization is heterogeneous. Tapex-end is believed to represent TDR, the interval from the end of the epicardial APDs to the end of the (sub)endocardial APDs.12 In left ventricular wedge preparations, the apex of the T-wave concurs with the end of the epicardial AP because the end of the epicardial AP is very steep.12,22,23 This steep descent of the epicardial AP caused the largest differences in amplitude with the (sub)endocardial AP. However, when other AP morphologies are present, a different phase of the AP could coincide with the apex of the T wave. For example, a steep descent at the start of phase 3 with a more slowly diminishing tail at the end of the AP could cause the apex of the T wave to coincide with the start of phase 3 of the epicardial AP. In that case, Tapex-end would overestimate TDR. In our study, overall Tapex-end had a good linear relation with RH (Tables 1a and b). However, Tapex-end in the left precordial leads overestimated TDR by several tens of milliseconds, this bias having the same order of magnitude as TDR itself (Figure 3). The abrupt increase in Tapex-end in leads V2 and V3 when biphasic T-waves evolve due to increased RH illustrates an additional problem: the difficult localization of the end of the T wave. The 1:1 relation between the duration of Tapex-end and TDR as found in the wedge preparation did not hold in a three dimensional structure as ECGSIM. The differences between the transmural quasi-ECG in the wedge preparation and the surface ECG may be explained by different AP morphologies and also by the fact that the wedge is but part of a heart. Therefore, the floating endocardial electrode in the wedge

55

Chapter 2

preparation is not the analogue of the Wilson central terminal in electrocardiography. Moreover, in the regular electrocardiogram other structures in the heart than the left ventricular free wall additionally contribute to the cardiac vector. Amongst others, this causes a considerable amount of cancellation, a phenomenon not occurring in the wedge preparation. T-wave complexity by singular value decomposition Singular value decomposition is a method to quantify the complexity of the repolarization. A smooth simple T wave is usually associated with a normal repolarization process, while a notched, irregular morphology is seen with disturbed repolarization processes.24 SVD-calculated complexity is higher in Long-QT patients and can be used to distinguish these patients from healthy subjects.10 In patients with arrhythmogenic right ventricular dysplasia, higher repolarization complexity, measured in body surface maps as a decreased contribution of the first, most simple SVD component, was associated with arrhythmias.25 In U.S. veterans with cardiovascular disease, repolarization complexity calculated with SVD conferred independent prognostic information.15 Van Oosterom mathematically proved that a higher RH leads to increased Tcomplexity.26 Our results in ECGSIM suggest that T-wave complexity reacts to small increases in RH, but fails to increase further with higher levels of RH. SVD may therefore be useful to detect increases of RH, but is unlikely to discriminate between smaller and larger RH values. QT dispersion QT dispersion, defined as the longest minus the shortest QT interval in any of the 12 ECG leads, was initially believed to represent local repolarization differences.11 According to current insight this concept is incorrect; QT-interval differences in ECG leads depends on projections of the (global) heart vector on the different lead vectors and can therefore not represent local repolarization differences.27 Another problem of manual measurement of QT dispersion is the low reproducibility, for example due to the subjectivity involved in exclusion of low-amplitude T waves and the difficult measurement of the end of T waves in noisy ECGs. Nevertheless, QT dispersion may have a weak relation with repolarization disturbances28 and was associated with arrhythmias in some studies.29;30 We measured QT dispersion values up to 171 ms. Although most previous studies 56


reported smaller values, similar values have been reported in patients shortly before an episode of Torsade de Pointes31 and in Long QT patients who remained symptomatic despite beta-blocker therapy.32 We measured the QT dispersion value of 171 ms at the maximum simulated RH (SDrep = 70 ms), a situation that is likely to be highly arrhythmogenic in reality. In our simulations, QT dispersion increased relatively little with initial RH increases, but it increased more at higher levels of SDrep. QT dispersion is sensitive for changes of RH in the very pathological zone, but has little sensitivity in the transitional zone between normal and abnormal. Therefore, this parameter is not well suited to discriminate between normal and abnormal. The above mentioned theoretical and practical objections in combination with the insensitivity for small increases in RH render QT dispersion unsuitable as an index of RH. T-wave amplitude Tamplitude reflects the net maximal voltage gradients in the whole heart after cancellation. The repolarization gradients in ECGSIM are caused by the voltage difference of opposing endo- and epicardial APs. By increasing RH the already long endocardial APDs were further lengthened and the already short epicardial APDs were further shortened, mainly achieved by a change in the duration of the plateau phase. This caused the endo- and epicardial APs to shift further out of phase such that endocardial APs still had a high amplitude and are less opposed by the already diminished epicardial AP amplitude. Our simulated T waves mimic the high amplitude T waves found in long-QT syndrome type 1.33 In wedge preparations mimicking the long-QT 1 syndrome, application of an IKs current blocker in combination with isoprotenerol caused a relatively longer APD of the mid-myocardium (subendocardium) compared to the epicardial APD. This caused an increased voltage gradient directed toward the epicardium and therefore, high amplitude T-waves on the transmural quasi ECG.23 The mathematical background of the dependence of Tamplitude on RH in the equivalent surface source model was worked out by Van Oosterom.34 For inter-individual comparison, the main disadvantage of the Tamplitude is its individual variability, due to differences in thorax and heart size. For example, athletes will have a higher Tamplitude35 mostly on the basis of a higher cardiac mass and not necessarily caused by an increased RH. This problem may be dissolved by recording a reference ECG, for example before the start of potentially 57

Chapter 2

arrhythmogenic medication. T-wave surface area Several studies showed a relation between RH, assessed from a limited number of action potential recordings, and Tarea. Tarea correlated with increased RH in rabbit hearts in which epicardial monophasic action potentials were recorded simultaneously with a surface ECG.8 In dogs, T-wave36 and QRST37 surface area was related to RH and a lowered threshold for ventricular fibrillation.38 Drugs that lengthen the APDs of specific cell layers, for example IKr blockers that foremost cause a lengthened midmyocardial APD, cause an increased Tarea in left ventricular wedge experiments.22 In our simulations, Tarea showed large increases at increasing RH. Tarea has the practical advantage of a low sensitivity to noise. Tarea may be the most comprehensive measure of RH, as it not only represents the maximum of the summed voltage gradients, like the T-amplitude, but also encompasses the time window during which the repolarization differences exist. T-wave symmetry ratio The T symmetry ratio was brought under attention by di Bernardo and Murray.9 They found that the T wave became more symmetrical with increased apico-basal and transmural dispersion. A normal symmetry ratio is 1.5 and with an increased RH this symmetry ratio approaches 1.0. Ischemia is known to induce high peaked symmetrical T waves, increased RH39 and vulnerability to arrhythmias.40 An advantage of this morphological parameter is that, in contrast to the high individual variability of Tamplitude, Tsymmetry seems to be more stable with different positions of the heart in the thorax.9 In our study, we also found that increased RH is reflected in a decreased Tsymmetry. Limitations As with all electrocardiographic studies, this simulation study addresses the forward problem and not the inverse problem, i.e., the changes in RH cause changes in the repolarization indices in the simulated surface ECG, but such ECG changes could theoretically also be caused by phenomena other than increased RH. Conclusions The well-established concept of RH is likely to play a major role in arrhythmo58


genesis. In a realistic three dimensional computer model we simulated a number of situations with increased RH. It appeared that transmural dispersion of the repolarization increased linearly with global RH. QT dispersion has a low sensitivity in the transitional zone between normal and abnormal RH and has a weak theoretical basis as an index of RH. Tapex-end in the left precordial leads overestimated TDR. Tcomplexity did not discriminate between higher values of RH. In conclusion, Tsymmetry, Tamplitude, Tarea, and, with some limitations, Tapex-end and Tcomplexity reliably reflect changes in repolarization heterogeneity.

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Hypertensive stress increases dispersion of repolarization Bart Hooft van Huysduynen Cees A. Swenne Henk J. Ritsema van Eck Jan A. Kors Anna L. Schoneveld Hedde van de Vooren Piet Schiereck Martin J. Schalij Ernst E. van der Wall

Pacing Clin Electrophysiol 2004; 27: 1603-9

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ABSTRACT Purpose. Several electrocardiographic indices for repolarization heterogeneity have been proposed previously. We studied the behavior of these indices under two different stressors at the same heart rate: i.e., normotensive gravitational stress, and hypertensive isometric stress. Methods. In 56 healthy males ECG and blood pressure were recorded during rest (sitting with horizontal legs), hypertensive stress (performing handgrip) and normotensive stress (sitting with lowered legs). During both stressors, heart rates differed less than 10 % in 41 subjects, who constituted the final study group. Results. Heart rate increased from 63 ± 9 bpm at rest to 71 ± 11 bpm during normotensive and to 71 ± 10 bpm during hypertensive stress (P

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