Abstract:

Background: During atrial fibrillation, heterogeneities and anisotropies result in a chaotic propagation of the depolarization wavefront. The electrophysiological parameter called conduction velocity (CV) influences the propagation pattern over the atrium. We present a method that determines the regional CV for deformed catheter shapes, which result due to the catheter movement and changing wall contact.Methods: The algorithm selects stable catheter positions, finds the local activation times (LAT), considers the wall contact and calculates all CV estimates within the area covered by the catheter. The method is evaluated with simulated data and then applied to four clinical data sets. Both sinus rhythm activity as well as depolarization wavefronts initiated by stimulation are analyzed. The regional CV is compared with the fractionation duration (FD) and peak-to-peak (P2P) voltages. A speed of 0.5 m/s was defined to create the simulated LAT.Results: After analyzing the simulated LAT with clinical catheter spatial coordinates, the median CV of 0.5 m/s with an interquartile range of 0.22 and exact CV direction vectors were obtained. For clinical cases, the CV magnitude range of 0.08 m/s to 1.0 m/s was obtained. The P2P amplitude of 0.7 mV to 3.7 mV and the mean FD from 40.79ms to 48.66ms was obtained. The correlation of 0.86 was observed between CV and P2P amplitude, and 0.62 between CV and FD.Conclusion: In this paper, a method is presented and validated which calculates the CV for the deformed catheter and changing wall contact. In an exemplary clinical data set correlation between regional CV with FD and the P2P voltage was observed.

Abstract:

Background: Intracardiac electrograms are an indispensable part during diagnosis of supraventriculararrhythmias, but atrial activity (AA) can be obscured by ventricular far-fields (VFF). Concepts based onstatistical independence like principal component analysis (PCA) cannot be applied for VFF removalduring atrial tachycardia with stable conduction.Methods: A database of realistic electrograms containing AAand VFF was generated. Both PCA and thenew technique periodic component analysis (πCA) were implemented, benchmarked, and applied toclinical data.Results: The concept of πCA was successfully verified to retain compromised AA morphology,showing high correlation (cc = 0.98 ± 0.01) for stable atrial cycle length (ACL). Performance ofPCA failed during temporal coupling (cc = 0.03 ± 0.08) but improved for increasing conductionvariability (cc = 0.77 ± 0.14). Stability of ACL was identified as a critical parameter for πCAapplication. Analysis of clinical data confirmed these findings.Conclusion: πCA is introduced as a powerful new technique for artifact removal in periodic signals.Its concept and performance were benchmarked against PCA using simulated data and demonstratedon measured electrograms.

Abstract:

Atrial arrhythmia is the most common cardiac arrhythmia. Parameters such as conduction velocity (CV), CV restitution etc. are under analysis in order to understand the cardiac arrhythmias. A number of methods have been proposed for CV calculation in simulation as well as clinical environments. Regional CV gives the information about the magnitude and direction of the propagating depolarization wavefronts on the atrium with homogeneous and heterogeneous tissue. The CV in different regions can provide important quantitative electrophysiological information about the underlying tissue. In this work the regional CV has been calculated using simulated local activation times (LAT) on clinical atrial geometries. Regions with homogeneous and heterogeneous propagation were manually selected for LAT simulation and later the regional CV has been calculated. The calculated CV for both the homogeneous and heterogeneous cases for all the clinical cases have been visualized on the atrial geometries. The visualization of the CV on the atrium represents insight into the regional behavior of the atrial substrate. The benefit of the region-specific study in clinical context is that it could enable the localization of critical sites in the patient specific atrial anatomies. Thus, this could aid physicians in cardiac therapies.

Abstract:

The success rate of the cardiac ablation procedure to cure atrial fibrillation is moderate and depends on the experience and expertise of the physicians. It could be increased by precisely locating arrhythmogenic substrates. The aim of this work is to present a simple and feasible method to analyze intraatrial electrograms to identify the arrhythmogenic substrate on the atrium, under sinus rhythm and pacing sequences. The change in the depolarization wavefront propagation, resulting from consecutive triggering at a point in the coronary sinus (CS), can be an indication of the arrhythmogenic substrate. The region specific study enables the localization of critical sites in the patient specific atrial anatomy. This could aid the physicians in ascertaining the efficacy of cardiac therapies. In this work the point- to-point analysis of the intraatrial electrograms was carried out.

Abstract:

Catheter ablation is the most widely used minimum invasive technique to cure atrial arrhythmias. However, the success rate of the treatment is still moderate and depends on the experience and expertise of the physicians. The aim of this work is to present a simple and feasible method to identify the arrhythmogenic areas on the atrium based on the duration of atrial activities in the intraatrial electrograms. Depolarization waves are created by giving pacing impulses from coronary sinus (CS). The duration of the activity triggered from sinus node (SN) and pacing sequences are analysed by calculating the duration of the activity to mark regions with long atrial activitywaves. The intraatrial electrograms have been analysed on the basis of temporal and spatial information. The region specific study may favour the localization of the critical sites in the patient specific atrial anatomy and aid the physician in ascertaining the efficacy of the cardiac therapies. The identification of suitable markers for critical patterns of the depolarization waves may be crucial to guide an effective ablation treatment. In this work a novel study for point-to-point analysis of the intraatrial electrograms was carried out.

Abstract:

Today, patients suffering from atrial arrhythmias like atrial flutter (AFlut) or atrial fibrillation (AFib) are examined in the EP-lab (electrophysiology lab) in order to understand and treat the disease. Multichannel catheters are advanced into the atria in order to measureelectric signals at manyintracardiacpositions simultaneously. Complementary to clinical learning,comprehension of the disease and therapeutic strategies can be improved with computer modeling of the heart. This way, hypotheses about initiation and perpetuation of the arrhythmia can be tested and ablation strategies can be assessed in-silico. Modeling and biosignal analysis can benefit from mutual fertilization. On the one hand, modeling can be improved and personalization can be achieved via high density mapping of the atria. On the other hand, new algorithms for the interpretation of multichannel electrograms can be developed and evaluated with synthetic signals from computer models of the atria. This article illustrates the synergetic potential by examples and highlights challenges to be addressed in the future.

Abstract:

By means of computer modeling general comprehension of electrophysiology (EP) of human atria can be improved and simulated patterns of ectopic foci, reentry and rotors can be created. On the other hand atrial electrograms are measured in the EP lab of many hospitals every day. In this contribution simulated and measured clinical signals are compared critically aiming at better understanding of atrial fibrillation and validation of computer modeling.

Abstract:

Post-ablation atrial flutter(AF) is a frequently occurring arrhythmia after treatment for persistent atrial fibrillation. However, mapping the flutter circuit using intracardiac electrograms is often challenging due to low signal voltage and scar areas caused by prior substrate modification. In addition, signals are frequently compromised by ventricular far field (VFF) artifacts, which obscure atrial activity (AA). This work introduces a new approach for VFF removal, which is based on the Periodic Component Analysis (&#1113099;CA). It utilizes the stable temporal relationship between AA and VFF, which poses a problem for other techniques like Principal Component Analysis (PCA) when both components superpose. A benchmark using simulated electrograms demonstrated significantly better correlation for this case when comparing pure AA to the reconstructed data using &#1113099;CA instead of PCA (0.98 vs. 0.90, p<0.001). Its benefit for diagnosis is demonstrated on clinical data.