Characterization of the Electrophysiological Characteristics of Chronic Atrial Fibrillation for Efficient Simulations.

Atrial biophysical simulations have the potential to enhance outcomes by enabling the simulation of pharmacological and ablative strategies. However, the high computational times associated with such simulations render them unsuitable for diagnostic purposes. To address this challenge, discrete models such as cellular automata (CA) have been developed, which consider a finite number of states, thus significantly reducing computational times. Yet, there is a pressing need to determine whether CA can replicate pathological simulations with accuracy. The analysis of simulations under different degrees of electrical remodeling shows an expected increase of Action Potential Duration (APD) with the previous Diastolic Interval (DI) interval, indicating short-term memory of atrial cardiomyocytes: shorter APD0 provoked shorter APD+1, and previous DI has a similar effect on APD+1. Independent prediction using both APD0 and DI was found to provide a far better estimation of APD+1 values, compared to relying on DI alone (p<<0.01). Finally, the CA models were able to replicate reentrant patterns and cycle lengths of different states of atrial remodeling with a high degree of accuracy when compared to biophysical simulations. Overall, the use of atrial CA with short-term memory allows accurate reproduction of arrhythmic behavior in pathological tissue within a clinically relevant timeframe.Clinical Relevance- Discrete electrophysiological models simulate pathological self-sustained arrhythmias in diagnostic times.

Assessment of Risk for Ventricular Tachycardia based on Extensive Electrophysiology Simulations.

Patients that have suffered a myocardial infarction are at high risk of developing ventricular tachycardia. Patient stratification is often determined by characterization of the underlying myocardial substrate by cardiac imaging methods. In this study, we show that computer modeling of cardiac electrophysiology based on personalized fast 3D simulations can help to assess patient risk to arrhythmia. We perform a large simulation study on 21 patient digital twins and reproduce successfully the clinical outcomes. In addition, we provide the sites which are prone to sustain ventricular tachycardias, i.e, onset sites around the scar region, and validate if they colocalize with exit sites from slow conduction channels.Clinical relevance- Fast electrophysiological simulations can provide advanced patient stratification indices and predict arrhythmic susceptibility to suffer from ventricular tachycardia in patients that have suffered a myocardial infarction.

Phase singularity point tracking for the identification of typical and atypical flutter patients: A clinical-computational study.

Atrial Flutter (AFL) termination by ablating the path responsible for the arrhythmia maintenance is an extended practice. However, the difficulty associated with the identification of the circuit in the case of atypical AFL motivates the development of diagnostic techniques. We propose body surface phase map analysis as a noninvasive tool to identify AFL circuits. Sixty seven lead body surface recordings were acquired in 9 patients during AFL (i.e. 3 typical, 6 atypical). Computed body surface phase maps from simulations of 5 reentrant behaviors in a realistic atrial structure were also used. Surface representation of the macro-reentrant activity was analyzed by tracking the singularity points (SPs) in surface phase maps obtained from band-pass filtered body surface potential maps. Spatial distribution of SPs showed significant differences between typical and atypical AFL. Whereas for typical AFL patients 70.78 ±â€¯16.17% of the maps presented two SPs simultaneously in the areas defined around the midaxialliary lines, this condition was only satisfied in 5.15 ±â€¯10.99% (p < 0.05) maps corresponding to atypical AFL patients. Simulations confirmed these results. Surface phase maps highlights the reentrant mechanism maintaining the arrhythmia and appear as a promising tool for the noninvasive characterization of the circuit maintaining AFL. The potential of the technique as a diagnosis tool needs to be evaluated in larger populations and, if it is confirmed, may help in planning ablation procedures.

Minimal configuration of body surface potential mapping for discrimination of left versus right dominant frequencies during atrial fibrillation.

BACKGROUND: Ablation of drivers maintaining atrial fibrillation (AF) has been demonstrated as an effective therapy. Drivers in the form of rapidly activated atrial regions can be noninvasively localized to either left or right atria (LA, RA) with body surface potential mapping (BSPM) systems. This study quantifies the accuracy of dominant frequency (DF) measurements from reduced-leads BSPM systems and assesses the minimal configuration required for ablation guidance. METHODS: Nine uniformly distributed lead sets of eight to 66 electrodes were evaluated. BSPM signals were registered simultaneously with intracardiac electrocardiograms (EGMs) in 16 AF patients. DF activity was analyzed on the surface potentials for the nine leads configurations, and the noninvasive measures were compared with the EGM recordings. RESULTS: Surface DF measurements presented similar values than panoramic invasive EGM recordings, showing the highest DF regions in corresponding locations. The noninvasive DFs measures had a high correlation with the invasive discrete recordings; they presented a deviation of <0.5 Hz for the highest DF and a correlation coefficient of >0.8 for leads configurations with 12 or more electrodes. CONCLUSIONS: Reduced-leads BSPM systems enable noninvasive discrimination between LA versus RA DFs with similar results as higher-resolution 66-leads system. Our findings demonstrate the possible incorporation of simplified BSPM systems into clinical planning procedures for AF ablation.

Adaptive step ODE algorithms for the 3D simulation of electric heart activity with graphics processing units.

In this paper we studied the implementation and performance of adaptive step methods for large systems of ordinary differential equations systems in graphics processing units, focusing on the simulation of three-dimensional electric cardiac activity. The Rush-Larsen method was applied in all the implemented solvers to improve efficiency. We compared the adaptive methods with the fixed step methods, and we found that the fixed step methods can be faster while the adaptive step methods are better in terms of accuracy and robustness.