Abstract:

Background: Computer models for simulating cardiac electrophysiology are valuable tools for research and clinical applications. Traditional reaction-diffusion (RD) models used for these purposes are computationally expensive. While eikonal models offer a faster alternative, they are not well-suited to study cardiac arrhythmias driven by reentrant activity. The present work extends the diffusion-reaction eikonal alternant model (DREAM), incorporating conduction velocity (CV) restitution for simulating complex cardiac arrhythmias. Methods: The DREAM modifies the fast iterative method to model cyclical behavior, dynamic boundary conditions, and frequency-dependent anisotropic CV. Additionally, the model alternates with an approximated RD model, using a detailed ionic model for the reaction term and a triple-Gaussian to approximate the diffusion term. The DREAM and monodomain models were compared, simulating reentries in 2D manifolds with different resolutions. Results: The DREAM produced similar results across all resolutions, while experiments with the monodomain model failed at lower resolutions. CV restitution curves obtained using the DREAM closely approximated those produced by the monodomain simulations. Reentry in 2D slabs yielded similar results in vulnerable window and mean reentry duration for low CV in both models. In the left atrium, most inducing points identified by the DREAM were also present in the high-resolution monodomain model. DREAM's reentry simulations on meshes with an average edge length of 1600$\mu$m were 40x faster than monodomain simulations at 200$\mu$m. Conclusion: This work establishes the mathematical foundation for using the accelerated DREAM simulation method for cardiac electrophysiology. Cardiac research applications are enabled by a publicly available implementation in the openCARP simulator.

Abstract:

The electrocardiogram (ECG) is a standard cost-efficient and non-invasive tool for the early detection of various cardiac diseases. Quantifying different timing and amplitude features of and in between the single ECG waveforms can reveal important information about the underlying (dys-)function of the heart. Determining these features requires the detection of fiducial points that mark the on- and offset as well as the peak of each ECG waveform (P wave, QRS complex, T wave). Manually setting these points is time-consuming and requires a physician’s expert knowledge. Therefore, the highly modular ECGdeli toolbox for MATLAB was developed, which is capable of filtering clinically recorded 12-lead ECG signals and detecting the fiducial points, also called delineation. It is one of the few open toolboxes offering ECG delineation for P waves, T Waves and QRS complexes. The algorithms provided were evaluated with the QT database, an ECG database comprising 105 signals with fiducial points annotated by clinicians. The median difference between the fiducial points set by the boundary detection algorithm and the clinical annotations serving as a ground truth is less than 4 samples (16 ms) for the P wave and the QRS complex markers.

Abstract:

The most common arrhythmia worldwide is atrial fibrillation (AF), recognized as a substantialpublic health burden due to its rising incidence. Patients affected by AF face elevated risksfor stroke, myocardial infarction, and mortality. Moreover, current treatment approachesoften prove ineffective, resulting in a high recurrence rate. Hence, there is an urgent need forfurther investigation into the mechanisms underlying AF to advance treatment strategies.The objective of this study was to assess the impact of the morphology of the conductionvelocity (CV) restitution curve on reentry events. We evaluated this influence using metricssuch as the vulnerability window, the average reentry duration, and the dominant frequency.By conducting this vulnerability assessment, the aim was to establish correlations betweenthe morphology of the CV restitution curve and these key features.We investigated the impact of using the pacing cycle length (PCL) and the diastolic interval(DI) on the restitution curve through simulations in the monodomain model. Additionally, theinfluence of the maximum longitudinal CV on the CV restitution curve was analyzed. ClinicalCV restitution curves of 13 patients with persistent AF, measured at various atrial locations,were employed in simulations on a 2D tissue slab utilizing the diffusion reaction eikonalalternant model (DREAM) to simulate electrical wave propagation with a personalizedionic model (Courtemanche) for the action potential (AP). The vulnerability assessmentwas done using an S1-S2 protocol. The experiments encompassed diverse morphologies ofrestitution curves and varying maximal longitudinal CV values. Moreover, experiments withheterogeneous meshes using two different restitution curve morphologies were conducted.No notable influence of the maximal longitudinal CV on the morphology of the CV restitutioncurve was identified. Moreover, the ionic model was successfully personalized using afunction that interpolated conductance values between healthy and AF tissue. Additionally, acorrelation between the steepness of the CV restitution curve and the vulnerability window,average reentry duration, and dominant frequency was established.Nevertheless, this work has limitations regarding the data acquisition and the model usedfor the electrophysiological simulations although it was shown that a shallow CV restitutioncurve is more vulnerable to AF and maintains it longer. Summarizing, the CV restitutioncurve proved to be a crucial factor for reentry events, promising to improve vulnerabilityassessment and treatment outcomes of AF.