Pharmacologic TWIK-Related Acid-Sensitive K+ Channel (TASK-1) Potassium Channel Inhibitor A293 Facilitates Acute Cardioversion of Paroxysmal Atrial Fibrillation in a Porcine Large Animal Model.

Background The tandem of P domains in a weak inward rectifying K+ channel (TWIK)-related acid-sensitive K+ channel (TASK-1; hK2P3.1) two-pore-domain potassium channel was recently shown to regulate the atrial action potential duration. In the human heart, TASK-1 channels are specifically expressed in the atria. Furthermore, upregulation of atrial TASK-1 currents was described in patients suffering from atrial fibrillation (AF). We therefore hypothesized that TASK-1 channels represent an ideal target for antiarrhythmic therapy of AF. In the present study, we tested the antiarrhythmic effects of the high-affinity TASK-1 inhibitor A293 on cardioversion in a porcine model of paroxysmal AF. Methods and Results Heterologously expressed human and porcine TASK-1 channels are blocked by A293 to a similar extent. Patch clamp measurements from isolated human and porcine atrial cardiomyocytes showed comparable TASK-1 currents. Computational modeling was used to investigate the conditions under which A293 would be antiarrhythmic. German landrace pigs underwent electrophysiological studies under general anesthesia. Paroxysmal AF was induced by right atrial burst stimulation. After induction of AF episodes, intravenous administration of A293 restored sinus rhythm within cardioversion times of 177±63 seconds. Intravenous administration of A293 resulted in significant prolongation of the atrial effective refractory period, measured at cycle lengths of 300, 400 and 500 ms, whereas the surface ECG parameters and the ventricular effective refractory period lengths remained unchanged. Conclusions Pharmacological inhibition of atrial TASK-1 currents exerts antiarrhythmic effects in vivo as well as in silico, resulting in acute cardioversion of paroxysmal AF. Taken together, these experiments indicate the therapeutic potential of A293 for AF treatment.

Mapping and Removing the Ventricular Far Field Component in Unipolar Atrial Electrograms.

OBJECTIVE: Unipolar intracardiac electrograms (uEGMs) measured inside the atria during electro-anatomic mapping contain diagnostic information about cardiac excitation and tissue properties. The ventricular far field (VFF) caused by ventricular depolarization compromises these signals. Current signal processing techniques require several seconds of local uEGMs to remove the VFF component and thus prolong the clinical mapping procedure. We developed an approach to remove the VFF component using data obtained during initial anatomy acquisition. METHODS: We developed two models which can approximate the spatio-temporal distribution of the VFF component based on acquired EGM data: Polynomial fit, and dipole fit. Both were benchmarked based on simulated cardiac excitation in two models of the human heart and applied to clinical data. RESULTS: VFF data acquired in one atrium were used to estimate model parameters. Under realistic noise conditions, a dipole model approximated the VFF with a median deviation of 0.029 mV, yielding a median VFF attenuation of 142. In a different setup, only VFF data acquired at distances of more than 5 mm to the atrial endocardium were used to estimate the model parameters. The VFF component was then extrapolated for a layer of 5 mm thickness lining the endocardial tissue. A median deviation of 0.082 mV (median VFF attenuation of 49x) was achieved under realistic noise conditions. CONCLUSION: It is feasible to model the VFF component in a personalized way and effectively remove it from uEGMs. SIGNIFICANCE: Application of our novel, simple and computationally inexpensive methods allows immediate diagnostic assessment of uEGM data without prolonging data acquisition.

Recurrence Quantification Analysis for Investigating Atrial Fibrillation Dynamics in a Heterogeneous Simulation Setup.

The outcomes of ablation targeting either reentry activations or fractionated activity during persistent atrial fibrillation (AF) therapy remain suboptimal due to, among others, the intricate underlying AF dynamics. In the present work, we sought to investigate such AF dynamics in a heterogeneous simulation setup using recurrence quantification analysis (RQA). AF was simulated in a spherical model of the left atrium, from which 412 unipolar atrial electrograms (AEGs) were extracted (2 s duration; 5 mm spacing). The phase was calculated using the Hilbert transform, followed by the identification of points of singularity (PS). Three regions were defined according to the occurrence of PSs: 1) no rotors; 2) transient rotors and; 3) long-standing rotors. Bipolar AEGs (1114) were calculated from pairs of unipolar nodes and bandpass filtered (30-300 Hz). The CARTO criterion (Biosense Webster) was used for AEGs classification (normal vs. fractionated). RQA attributes were calculated from the filtered bipolar AEGs: determinism (DET); recurrence rate (RR); laminarity (LAM). Sample entropy (SampEn) and dominant frequency (DF) were also calculated from the AEGs. Regions with longstanding rotors have shown significantly lower RQA attributes and SampEn when compared to the other regions, suggesting a higher irregular behaviour (P≤0.01 for all cases). Normal and fractionated AEGs were found in all regions (respectively; Region 1: 387 vs. 15; Region 2: 221 vs. 13; Region 3: 415 vs. 63). Region 1 vs. Region 3 have shown significant differences in normal AEGs (P≤0.0001 for all RQA attributes and SampEn), and significant differences in fractionated AEGs for LAM, RR and SampEn (P=0.0071, P=0.0221 and P=0.0086, respectively). Our results suggest the co-existence of normal and fractionated AEGs within long-standing rotors. RQA has unveiled distinct dynamic patterns-irrespective of AEGs classification-related to regularity structures and their nonstationary behaviour in a rigorous deterministic context.