Technical Considerations on Phase Mapping for Identification of Atrial Reentrant Activity in Direct- and Inverse-Computed Electrograms. (September 2017)

• Record Type: Journal Article
• Authors: Rodrigo, Miguel; Climent, Andreu M.; Liberos, Alejandro; Fernández-Avilés, Francisco; Berenfeld, Omer; Atienza, Felipe; Guillem, Maria S.
• Is Part Of: Circulation. Volume 10:Number 9(2017)
• Publication Date: 2017-09
• Subjects: atrial fibrillation -- atrial flutter -- body surface potential mapping -- electrocardiography; Arrhythmia -- Periodicals; Heart -- Electric properties -- Periodicals; 616.128
• DOI: 10.1161/CIRCEP.117.005008
• Languages: English
• ISSNs: 1941-3149

Abstract

Abstract : Background: Phase mapping has become a broadly used technique to identify atrial reentrant circuits for ablative therapy guidance. This work studies the phase mapping process and how the signal nature and its filtering affect the reentrant pattern characterization in electrogram (EGM), body surface potential mapping, and electrocardiographic imaging signals. Methods and Results: EGM, body surface potential mapping, and electrocardiographic imaging phase maps were obtained from 17 simulations of atrial fibrillation, atrial flutter, and focal atrial tachycardia. Reentrant activity was identified by singularity point recognition in raw signals and in signals after narrow band-pass filtering at the highest dominant frequency (HDF). Reentrant activity was dominantly present in the EGM recordings only for atrial fibrillation and some atrial flutter propagations patterns, and HDF filtering allowed increasing the reentrant activity detection from 60% to 70% of time in atrial fibrillation in unipolar recordings and from 0% to 62% in bipolar. In body surface potential mapping maps, HDF filtering increased from 10% to 90% the sensitivity, although provoked a residual false reentrant activity ≈30% of time. In electrocardiographic imaging, HDF filtering allowed to increase ⩽100% the time with detected rotors, although provoked the apparition of false rotors during 100% of time. Nevertheless, raw electrocardiographic imaging phase maps presented reentrant activity just in atrial fibrillation recordings accounting for ≈80% of time. Conclusions: Rotor identification is accurate and sensitive and does not require additional signal processing in measured or noninvasively computed unipolar EGMs. Bipolar EGMs and body surface potential mapping do require HDF filtering to detect rotors at the expense of a decreased specificity. Abstract : Supplemental Digital Content is available in the text.