Vincent Jacquemet

Network interactions within the canine intrinsic cardiac nervous system: implications for reflex control of regional cardiac function

•u2002 Control of regional cardiac function, as mediated by the intrinsic cardiac (IC) nervous system, is dependent upon its cardiac afferent neuronal inputs, changes in its central neuronal drive and interactions mediated within via local circuit neurons. •u2002 The majority of its local circuit neurons receive indirect central (sympathetic and parasympathetic) inputs, lesser proportions transducing the cardiac milieu. •u2002 Fifty per cent of IC neurons exhibit cardiac cycle‐related periodicity that is primarily related to direct cardiac mechano‐sensory afferent inputs and, secondarily, to indirect central autonomic efferent inputs. •u2002 In response to mediastinal nerve stimulation, most IC neurons became excessively activated in the induction of atrial arrhythmias such that their stochastic interactivity precedes and persists throughout neuronally induced atrial fibrillation. •u2002 Modulation of such stochastic IC local circuit neuronal recruitment may represent a novel target for the treatment of select cardiac disease, including atrial arrhythmias.

An Eikonal Approach for the Initiation of Reentrant Cardiac Propagation in Reaction–Diffusion Models

Microscale electrical propagation in the heart can be modeled by a reaction-diffusion system, describing cell and tissue electrophysiology. Macroscale features of wavefront propagation can be reproduced by an eikonal model, a reduced formulation involving only wavefront shape. In this paper, these two approaches are combined to incorporate global information about reentrant pathways into a reaction-diffusion model. The eikonal-diffusion formulation is generalized to handle reentrant activation patterns and wavefront collisions. Boundary conditions are used to specify pathways of reentry. Finite-element-based numerical methods are presented to solve this nonlinear equation on a coarse triangular mesh. The macroscale eikonal model serves to construct an initial condition for the microscale reaction-diffusion model. Electrical propagation simulated from this initial condition is then compared to the isochrones predicted by the eikonal model. Results in 2-D and thin 3-D test-case geometries demonstrate the ability of this technique to initiate anatomical and functional reentries along prescribed pathways, thus facilitating the development of dedicated models aimed at better understanding clinical case reports.

Evaluation of a subject-specific transfer-function-based nonlinear QT interval rate-correction method.

The QT interval in the electrocardiogram (ECG) is a measure of total duration of depolarization and repolarization. Correction for heart rate is necessary to provide a single intrinsic physiological value that can be compared between subjects and within the same subject under different conditions. Standard formulas for the corrected QT (QTc) do not fully reproduce the complexity of the dependence in the preceding interbeat intervals (RR) and inter-subject variability. In this paper, a subject-specific, nonlinear, transfer function-based correction method is formulated to compute the QTc from Holter ECG recordings. The model includes five parameters: three describing the static QT-RR relationship and two representing memory/hysteresis effects that intervene in the calculation of effective RR values. The parameter identification procedure is designed to minimize QTc fluctuations and enforce zero correlation between QTc and effective RR. Weighted regression is used to better handle unbalanced or skewed RR distributions. The proposed optimization approach provides a general mathematical framework for further extensions of the model. Validation, robustness evaluation and comparison with existing QT correction formulas is performed on ECG signals recorded during sinus rhythm, atrial pacing, tilt-table tests, stress tests and atrial flutter (29 subjects in total). The resulting average modeling error on the QTc is 4.9 ± 1.1 ms with a sampling interval of 2 ms, which outperforms correction formulas currently used. The results demonstrate the benefits of subject-specific rate correction and hysteresis reduction.

An eikonal-diffusion solver and its application to the interpolation and the simulation of reentrant cardiac activations

Electrical propagation of the cardiac impulse in the myocardium can be described by the eikonal-diffusion equation. This equation governs the field of activation times in a domain where conduction properties are specified. This approach has been applied to knowledge-based interpolation of sparse measurements of activation times and to the creation of initial conditions for detailed ionic models of cardiac propagation. This paper presents the mathematical basis, matrix formulation, and compact Matlab implementation of an iterative finite-element solver (triangular meshes) for the eikonal-diffusion equation extended to reentrant activations, which automatically identifies the period of reentry and computes the resulting isochrones. An iterative algorithm is designed to perform Laplacian interpolation of reentrant activation maps to be used as initial estimate for the eikonal-diffusion solver. The performance of the algorithm is analyzed in test-case geometries (ventricular slice and simplified atrial surface model).

Optimizing Local Capture of Atrial Fibrillation by Rapid Pacing: Study of the Influence of Tissue Dynamics

While successful termination by pacing of organized atrial tachycardias has been observed in patients, rapid pacing of AF can induce a local capture of the atrial tissue but in general no termination. The purpose of this study was to perform a systematic evaluation of the ability to capture AF by rapid pacing in a biophysical model of the atria with different dynamics in terms of conduction velocity (CV) and action potential duration (APD). Rapid pacing was applied during 30xa0s at five locations on the atria, for pacing cycle lengths in the range 60–110% of the mean AF cycle length (AFCLmean). Local AF capture could be achieved using rapid pacing at pacing sites located distal to major anatomical obstacles. Optimal pacing cycle lengths were found in the range 74–80% AFCLmean (capture window width: 14.6xa0±xa03% AFCLmean). An increase/decrease in CV or APD led to a significant shrinking/stretching of the capture window. Capture did not depend on AFCL, but did depend on the atrial substrate as characterized by an estimate of its wavelength, a better capture being achieved at shorter wavelengths. This model-based study suggests that a proper selection of the pacing site and cycle length can influence local capture results and that atrial tissue properties (CV and APD) are determinants of the response to rapid pacing.

Estimating the time scale and anatomical location of atrial fibrillation spontaneous termination in a biophysical model

Due to their transient nature, spontaneous terminations of atrial fibrillation (AF) are difficult to investigate. Apparently, confounding experimental findings about the time scale of this phenomenon have been reported, with values ranging from 1xa0s to 1xa0min. We propose a biophysical modeling approach to study the mechanisms of spontaneous termination in two models of AF with different levels of dynamical complexity. 8xa0s preceding spontaneous terminations were studied and the evolution of cycle length and wavefront propagation were documented to assess the time scale and anatomical location of the phenomenon. Results suggest that termination mechanisms are dependent on the underlying complexity of AF. During simulated AF of low complexity, the total process of spontaneous termination lasted 3,200xa0ms and was triggered in the left atrium 800xa0ms earlier than in the right atrium. The last fibrillatory activity was observed more often in the right atrium. These asymmetric termination mechanisms in both time and space were not observed during spontaneous terminations of complex AF simulations, which showed less predictable termination patterns lasting only 1,600xa0ms. This study contributes to the interpretation of previous clinical observations, and illustrates how computer modeling provides a complementary approach to study the mechanisms of cardiac arrhythmias.

Lessons from computer simulations of ablation of atrial fibrillation

This paper reviews the simulations of catheter ablation in computer models of the atria, from the first attempts to the most recent anatomical models. It describes how postulated substrates of atrial fibrillation can be incorporated into mathematical models, how modelling studies can be designed to test ablation strategies, what their current trade‐offs and limitations are, and what clinically relevant lessons can be learnt from these simulations. Drawing a parallel between clinical and modelling studies, six ablation targets are considered: pulmonary vein isolation, linear ablation, ectopic foci, complex fractionated atrial electrogram, rotors and ganglionated plexi. The examples presented for each ablation target illustrate a major advantage of computer models, the ability to identify why a therapy is successful or not in a given atrial fibrillation substrate. The integration of pathophysiological data to create detailed models of arrhythmogenic substrates is expected to solidify the understanding of ablation mechanisms and to provide theoretical arguments supporting substrate‐specific ablation strategies.

Vagal stimulation targets select populations of intrinsic cardiac neurons to control neurally induced atrial fibrillation

Mediastinal nerve stimulation (MNS) reproducibly evokes atrial fibrillation (AF) by excessive and heterogeneous activation of intrinsic cardiac (IC) neurons. This study evaluated whether preemptive vagus nerve stimulation (VNS) impacts MNS-induced evoked changes in IC neural network activity to thereby alter susceptibility to AF. IC neuronal activity in the right atrial ganglionated plexus was directly recorded in anesthetized canines (n = 8) using a linear microelectrode array concomitant with right atrial electrical activity in response to: 1) epicardial touch or great vessel occlusion vs. 2) stellate or vagal stimulation. From these stressors, post hoc analysis (based on the Skellam distribution) defined IC neurons so recorded as afferent, efferent, or convergent (afferent and efferent inputs) local circuit neurons (LCN). The capacity of right-sided MNS to modify IC activity in the induction of AF was determined before and after preemptive right (RCV)- vs. left (LCV)-sided VNS (15 Hz, 500 μs; 1.2× bradycardia threshold). Neuronal (n = 89) activity at baseline (0.11 ± 0.29 Hz) increased during MNS-induced AF (0.51 ± 1.30 Hz; P < 0.001). Convergent LCNs were preferentially activated by MNS. Preemptive RCV reduced MNS-induced changes in LCN activity (by 70%) while mitigating MNS-induced AF (by 75%). Preemptive LCV reduced LCN activity by 60% while mitigating AF potential by 40%. IC neuronal synchrony increased during neurally induced AF, a local neural network response mitigated by preemptive VNS. These antiarrhythmic effects persisted post-VNS for, on average, 26 min. In conclusion, VNS preferentially targets convergent LCNs and their interactive coherence to mitigate the potential for neurally induced AF. The antiarrhythmic properties imposed by VNS exhibit memory.

Modeling left and right atrial contributions to the ECG

This paper presents the mathematical formulation, the numerical validation and several illustrations of a forward-modeling approach based on dipole-current sources to compute the contribution of a part of the heart to the electrocardiogram (ECG). Clinically relevant applications include identifying in the ECG the contributions from the right and the left atrium. In a Courtemanche-based monodomain computer model of the atria and torso, 1000 dipoles distributed throughout the atrial mid-myocardium are found to be sufficient to reproduce body surface potential maps with a relative error <1% during both sinus rhythm and atrial fibrillation. When the boundary element method is applied to solve the forward problem, this approach enables fast offline computation of the ECG contribution of any anatomical part of the atria by applying the principle of superposition to the dipole sources. In the presence of a right-left activation delay (sinus rhythm), pulmonary vein isolation (sinus rhythm) or left-right differences in refractory period (atrial fibrillation), the decomposition of the ECG is shown to help interpret ECG morphology in relation to the atrial substrate. These tools provide a theoretical basis for a deeper understanding of the genesis of the P wave or fibrillatory waves in normal and pathological cases.

QT interval measurement and correction in patients with atrial flutter: a pilot study

BACKGROUND AND PURPOSEnMeasurement of QT intervals during atrial flutter (AFL) is relevant to monitor the safety of drug delivery. Our aim is to compare QT and QTc intervals in AFL patients before and after catheter ablation in order to validate QT measurement during AFL.nnnMETHODSn25 patients suffering from AFL underwent catheter ablation; 9 were in sinus rhythm and 16 were in AFL at the time of the procedure. Holter ECGs were continuously recorded before, during and after the procedure. In AFL signals, flutter waves were subtracted using a previously-validated deconvolution-based method. Fridericias QTc was computed before and after ablation after hysteresis reduction.nnnRESULTSnComparing QTc values obtained before and after ablation showed that (1) the intervention did not significantly affect QTc, and (2) the QTc during AFL was concordant with the QTc value in sinus rhythm.nnnCONCLUSIONnQTc can be reliably measured in patients with AFL using flutter wave subtraction and hysteresis reduction.