What is the clinical evidence from this study?

Study design: Other. Population: Atrial Fibrillation and Atrial Tachycardia (n=40). Intervention: Automated cycle length estimation algorithm vs. Expert physician annotation. Primary outcome: Mean absolute error (MAE) of cycle length estimation.

December 31, 2022

Cycle Length Estimation Using Accurate Adaptive Detection of Local Activations in Atrial Intracardiac Electrograms

Key Result

The proposed automated cycle length estimation algorithm accurately processed complex mapping signals, achieving a mean absolute error of 5.38 ms for atrial fibrillation and 2.9 ms for atrial tachycardia.

Structured PICO

Population

Intracardiac bipolar electrograms (EGM) recorded during atrial arrhythmias ablation

Intervention

Cycle length estimator using accurate adaptive detection of local activations

Outcome

Reliable estimation of cycle length (frequency of periodic activity)

A new cycle length estimator is proposed to reliably process complex intracardiac electrograms and estimate cycle length during atrial fibrillation ablation.

Limitations

Over detection of activations in the case of equidistant double potential waves or ventricular far field artifacts.
Algorithm was initially designed for rapid rhythms, requiring adaptation for slow rhythms with cycle lengths ≥ 3 seconds.
Annotations of cycle length are susceptible to inter-annotator variability and measurement errors.

Abstract

The normal electrical potential propagates throughout the atria periodically.During atrial arrhythmias its propagation is modified because the substrate is not homogeneous and new sources of punctual electrical activity appear.The periodic behavior of activation remains predominant, but becomes local in different parts of the atria.It is characterized by cycle length (CL) which measures the frequency of activation and can be computed from intracardiac bipolar electrograms (EGM) recorded by a mapping catheter during the catheter ablation procedure.The CL value of different mapped zones is an extremely important resource for physicians when performing persistent Atrial Fibrillation (AF) ablation because it helps to identify pathological zones and define the ablation strategy.Thus, a reliable estimation of the CL of atrial tissue is essential.The complexity of this task stems from the large variability in EGM morphology influenced by multiple wavefronts, fragmentation and added noise.In this work, we propose a cycle length estimator that can process the complex mapping signals recorded during atrial arrhythmias ablation and reliably provide the frequency of their periodic activity.

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