Effects of early afterdepolarizations on excitation patterns in an accurate model of the human ventricles

Early Afterdepolarizations, EADs, are defined as the reversal of the action potential before completion of the repolarization phase, which can result in ectopic beats. However, the series of mechanisms of EADs leading to these ectopic beats and related cardiac arrhythmias are not well understood. Therefore, we aimed to investigate the influence of this single cell behavior on the whole heart level. For this study we used a modified version of the Ten Tusscher-Panfilov model of human ventricular cells (TP06) which we implemented in a 3D ventricle model including realistic fiber orientations. To increase the likelihood of EAD formation at the single cell level, we reduced the repolarization reserve (RR) by reducing the rapid delayed rectifier Potassium current and raising the L-type Calcium current. Varying these parameters defined a 2D parametric space where different excitation patterns could be classified. Depending on the initial conditions, by either exciting the ventricles with a spiral formation or burst pacing protocol, we found multiple different spatio-temporal excitation patterns. The spiral formation protocol resulted in the categorization of a stable spiral (S), a meandering spiral (MS), a spiral break-up regime (SB), spiral fibrillation type B (B), spiral fibrillation type A (A) and an oscillatory excitation type (O). The last three patterns are a 3D generalization of previously found patterns in 2D. First, the spiral fibrillation type B showed waves determined by a chaotic bi-excitable regime, i.e. mediated by both Sodium and Calcium waves at the same time and in same tissue settings. In the parameter region governed by the B pattern, single cells were able to repolarize completely and different (spiral) waves chaotically burst into each other without finishing a 360 degree rotation. Second, spiral fibrillation type A patterns consisted of multiple small rotating spirals. Single cells failed to repolarize to the resting membrane potential hence prohibiting the Sodium channel gates to recover. Accordingly, we found that Calcium waves mediated these patterns. Third, a further reduction of the RR resulted in a more exotic parameter regime whereby the individual cells behaved independently as oscillators. The patterns arose due to a phase-shift of different oscillators as disconnection of the cells resulted in continuation of the patterns. For all patterns, we computed realistic 9 lead ECGs by including a torso model. The B and A type pattern exposed the behavior of Ventricular Tachycardia (VT). We conclude that EADs at the single cell level can result in different types of cardiac fibrillation at the tissue and 3D ventricle level

Spatial patterns of excitation at tissue and whole organ level due to early afterdepolarizations

Early after depolarizations (EAD) occur in many pathological conditions, such as congenital or acquired channelopathies, drug induced arrhythmias, and several other situations that are associated with increased arrhythmogenicity. In this paper we present an overview of the relevant computational studies on spatial EAD dynamics in 1D, 2D, and in 3D anatomical models and discuss the relation of EADs to cardiac arrhythmias. We also discuss unsolved problems and highlight new lines of research in this area

Directed networks as a novel way to describe and analyze cardiac excitation : directed graph mapping

Networks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes. During (normal) sinus rhythm or during cardiac arrhythmias, successive excitation connects neighboring electrodes, resulting in their own unique directed network. This in theory makes it a perfect fit for directed network analysis. In this study, we applied directed networks to the heart in order to describe and characterize cardiac arrhythmias. Proof-of-principle was established using in-silico and clinical data. We demonstrated that tools used in network theory analysis allow determination of the mechanism and location of certain cardiac arrhythmias. We show that the robustness of this approach can potentially exceed the existing state-of-the art methodology used in clinics. Furthermore, implementation of these techniques in daily practice can improve the accuracy and speed of cardiac arrhythmia analysis. It may also provide novel insights in arrhythmias that are still incompletely understood

Prospective evaluation of entrainment mapping as an adjunct to new-generation high-density activation mapping systems of left atrial tachycardias

BACKGROUND Identification of atrial tachycardia (AT) mechanism remains challenging. OBJECTIVE We sought to investigate the added value of entrainment maneuvers (EM) when using new high-density activation mapping (HDAM) technologies for the identification of complex left ATs. METHODS Thirty-six consecutive complex ATs occurring after ablation of persistent atrial fibrillation were prospectively analyzed. The AT mechanism was diagnosed in 2 steps by 2 experts: (1) based on H DAM only (Coherent module, CARTO, Biosense Webster Inc., Irvine, CA) and (2) with additional analysis from EM. RESULTS EM resulted in atrial fibrillation in 1 patient, who was excluded from the analysis. Ten of 11 single loop macroreentries identified by HDAM were confirmed by EM. Only 4 of 14 double loop macroreentries identified by HDAM wereconfirmed by EM (in 10 patients, EM unmasked passive activation of one of the visual cir- cuits). One sole microreentry circuit identified by HDAM was confirmed by EM. A combination of macro- and microreentry circuits was visualized in 3 ATs using H DAM. However, EM revealed passive activation of the visual macroreentrant loop in 2 of these 3 cases. By using HDAM in 6 of 35 ATs (17%), no univocal mechanism could be identified, whereas EM finally enabled the diagnosis of 5 microreentry circuits and 1 macroreentrant AT. All the diagnoses made from EM in addition to HDAM were confirmed by ablation. CONCLUSION Entrainment maneuvers are still useful during mapping of complex left ATs, mostly to differentiate active from passive macroreentrant loops and to demonstrate microreentry circuits

Directed graph mapping shows rotors maintain non-terminating and focal sources maintain self-terminating Torsade de Pointes in canine model

Torsade de Pointes is a polymorphic ventricular tachycardia which is as yet incompletely understood. While the onset of a TdP episode is generally accepted to be caused by triggered activity, the mechanisms for the perpetuation is still under debate. In this study, we analysed data from 54 TdP episodes divided over 5 dogs (4 female, 1 male) with chronic atrioventricular block. Previous research on this dataset showed both reentry and triggered activity to perpetuate the arrhythmia. 13 of those TdP episodes showed reentry as part of the driving mechanism of perpetuating the episode. The remaining 41 episodes were purely ectopic. Reentry was the main mechanism in long-lasting episodes (>14 beats), while focal sources were responsible for maintaining shorter episodes. Building on these results, we re-analysed the data using directed graph mapping This program uses principles from network theory and a combination of positional data and local activation times to identify reentry loops and focal sources within the data. The results of this study are twofold. First, concerning reentry loops, we found that on average non-terminating (NT) episodes (≥10 s) show significantly more simultaneous reentry loops than self-terminating (ST) TdP (<10 s). Non-terminating episodes have on average 2.72 ± 1.48 simultaneous loops, compared to an average of 1.33 ± 0.66 for self-terminating episodes. In addition, each NT episode showed a presence of (bi-)ventricular loops between 10.10% and 69.62% of their total reentry duration. Compared to the ST episodes, only 1 in 4 episodes (25%) showed (bi-)ventricular reentry, lasting only 7.12% of its total reentry duration. This suggests that while focal beats trigger TdP, macro-reentry and multiple simultaneous localized reentries are the major drivers of long-lasting episodes. Second, using heatmaps, we found focal sources to occur in preferred locations, instead of being distributed randomly. This may have implications on treatment if such focal origins can be disabled reliably

Directed graph mapping shows rotors maintain non-terminating and focal sources maintain self-terminating Torsade de Pointes in canine model

Torsade de Pointes is a polymorphic ventricular tachycardia which is as yet incompletely understood. While the onset of a TdP episode is generally accepted to be caused by triggered activity, the mechanisms for the perpetuation is still under debate. In this study, we analysed data from 54 TdP episodes divided over 5 dogs (4 female, 1 male) with chronic atrioventricular block. Previous research on this dataset showed both reentry and triggered activity to perpetuate the arrhythmia. 13 of those TdP episodes showed reentry as part of the driving mechanism of perpetuating the episode. The remaining 41 episodes were purely ectopic. Reentry was the main mechanism in long-lasting episodes (&gt;14 beats), while focal sources were responsible for maintaining shorter episodes. Building on these results, we re-analysed the data using directed graph mapping This program uses principles from network theory and a combination of positional data and local activation times to identify reentry loops and focal sources within the data. The results of this study are twofold. First, concerning reentry loops, we found that on average non-terminating (NT) episodes (≥10 s) show significantly more simultaneous reentry loops than self-terminating (ST) TdP (&lt;10 s). Non-terminating episodes have on average 2.72 ± 1.48 simultaneous loops, compared to an average of 1.33 ± 0.66 for self-terminating episodes. In addition, each NT episode showed a presence of (bi-)ventricular loops between 10.10% and 69.62% of their total reentry duration. Compared to the ST episodes, only 1 in 4 episodes (25%) showed (bi-)ventricular reentry, lasting only 7.12% of its total reentry duration. This suggests that while focal beats trigger TdP, macro-reentry and multiple simultaneous localized reentries are the major drivers of long-lasting episodes. Second, using heatmaps, we found focal sources to occur in preferred locations, instead of being distributed randomly. This may have implications on treatment if such focal origins can be disabled reliably

DGM : Directed-Graph Mapping as a novel tool to analyze cardiac arrhythmias

Cardiac arrhythmias and related diseases are the leading cause of death in the Western world. The management thereof currently accounts for about 9\% of the total health-care expenditure across the EU. Research on the mechanisms of arrhythmia and optimizations of diagnostic tools remain important. The normal rhythm of the heart results in about 60 to 100 beats per minute, which accumulate roughly to about 3 billion beats in a lifetime. It is likely for this rhythm to get disturbed once in a while. Naturally, the heart rate increases with exercise or slows down during sleep. Drugs, alcohol, nicotine and the general health condition of a person may also affect the heart's condition. However, persistent abnormality of the heart rhythm can indicate cardiac arrhythmia and the associated complications will depend on the type of arrhythmia. In general, complications and symptoms of cardiac arrhythmias may include a racing or slow heartbeat, chest pain, shortness of breath or even anxiety and fatigue. In more severe cases cardiac arrhythmia can induce stroke, heart failure and sudden cardiac death. Treatment of arrhythmia may include medication, specific therapies such as vagal maneuvers and cardioversion, surgery like ablation and maze procedures or the placement of implantable devices lika a pacemaker or defibrillator. For this work, mainly ablation therapy is of interest. During ablation the electrophysiologist (EP) inserts a catheter (a measuring device with electrodes) into the heart and records the electrical activity. These electrical signals are presented on a color-coded map. Based on an educated interpretation of these color maps and corresponding signals the EP will gather knowledge about the mechanism maintaining the arrhythmia. Once the mechanism is understood and located, the EP will ablate or scar the heart tissue in order to stop electrical propagation in that specific region. This will stop the arrhythmia restoring the normal heart rhythm or convert the excitation pattern to a (usually) slower arrhythmia. It can be very challenging to determine the mechanism of an arrhythmia and wrong ablation lines can make the heart prone to new arrhythmias and limits the myocardial contractility. Analysis of these electrical maps can be difficult and prone interpretation. Therefore, there is a need for automated and operator independent interpretations and strategies. My dissertation is devoted to the development, applicability and accuracy of Directed-Graph Mapping or DGM on analysis of cardiac arrhythmia mechanisms. DGM is a mathematical approach based on concepts of network theory describing the properties of cardiac excitation waves. DGM takes as input the spatial coordinates of the electrodes and the Local Activation Time (LAT) of the signals. With this data, a directed graph is created. Based on validated algorithms of graph theory and new algorithms I designed, DGM automatically analyzes these graphs and presents the rotational circuit or focal sources of the arrhythmia under study

Directed graph mapping is able to distinguish between the true and false rotors in a complex in-silico excitation pattern

Background In realistic in-silico studies (Figure1, top row) it was shown that phase mapping PM (Figure 1, A) can detect the correct rotor as well as phantom rotors as an artefact of interpolation or due to the far field (Figure 1, B). After interpretation of the LAT, the far field detections could not be distinguished from the true rotor driving the excitation pattern. This can contribute to failure in Atrial Fibrillation (AF) ablation procedures. Objective We tested if the recently developed tool Directed Graph mapping (DGM) is less prone to far-field effects and interpolation artefacts than PM on the same in-silico data. DGM represents the excitation pattern as a directed network, from which the rotational activity is detected as cycles in that network. Methods Starting from the electrograms (EGMs) of the 64 electrode basket catheter, we interpolated to 957 equidistant electrodes and calculated local activation times (LATs) of the interpolated EGMs (Figure 1, C). We varied the minimal allowed conduction velocity and calculated the corresponding networks for the complete simulation time. Detections were considered as correct if they were located in the same region of the true core of the phasemaps. The false detections were classified in multiple different regions (Figure 1, D). Results We find that by proper choice of CVs in the graphs it is possible to achieve a 80% detection of true rotors with 26% detection of false rotors. Reducing restrictions on the CVs increased the detection rate of the false rotors. False rotors due to artifacts were not detected by DGM (Figure 1, last row). Conclusion DGM is able to distinguish between true and far field rotors. False detections due to interpolation artifacts as seen in the PM protocol were not observed. The velocity limits in the graph construction play a keyrole in eliminating the far field effects