EP News: Basic and Translational

Abstract

Extracellular electrograms recorded during atrial fibrillation (AF) are challenging to interpret because of beat-to-beat variability in amplitude and duration. Phase mapping represents these voltage signals in terms of relative position within the cycle and has been widely applied to unipolar electrogram data of fibrillation but not to bipolar recordings, which are commonly acquired clinically. Roney et al (Ann Biomed Eng 2017;45:910, PMID 27921187) presented a novel algorithm for calculating phase from both unipolar and bipolar electrograms recorded during AF. A sequence of signal filters and processing steps are used to calculate phase from simulated, experimental, and clinical, unipolar, and bipolar electrograms. The algorithm is validated against action potential phase using simulated data; between experimental multielectrode array unipolar and bipolar phase; and for wavefront identification in clinical atrial tachycardia. For clinical AF, rotational content and propagation maps were measured using either unipolar or bipolar recordings. The authors conclude that the algorithm is robust, uses standard signal processing techniques, and accurately quantifies AF wavefronts and sources. Identifying critical sources, such as rotors, in AF may allow for more accurate targeting of ablation therapy and improved patient outcomes.