Far-field contributions in multi-electrodes atrial recordings blur distinction between anatomical and functional reentries and may cause imaginary phase singularities – A computational study. (May 2019)

• Record Type: Journal Article
• Authors: Martinez-Mateu, Laura; Romero, Lucia; Saiz, Javier; Berenfeld, Omer
• Is Part Of: Computers in biology and medicine. Volume 108(2019)
• Page Start: 276
• Page End: 287
• Publication Date: 2019-05
• Subjects: Mapping -- Electrogram -- Phase analysis -- Far-field -- Rotors -- Reentry; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2019.02.022
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia and the most important cause of embolic stroke, requiring new technologies for its better understanding and therapies. Recent approaches to map the electrical activity during AF with multi-electrode systems aim at localizing patient-specific ablation targets of reentrant patterns. However, there is a critical need to determine the accuracy of those mapping systems. We performed computer simulations as a numerical approach of systematically evaluating the influence of far-field sources on the electrical recordings and detection of rotors. Methods: We constructed 2 computer models of atrial tissue: (i) a 2D sheet model with varying non-active cells area in its center, and (ii) a whole realistic 3D atrial model. Phase maps were built based on the Hilbert transform of the unipolar electrograms recorded by virtual 2D and 3D multi-electrode systems and rotors were tracked through phase singularities detections. Results: Analysis of electrograms recorded away from the 2D atrial model shows that the larger the distance between an electrode and the tissue model, the stronger the far-field sources contribution to the electrogram is. Importantly, even if an electrode is positioned in contact with the tissue, the electrogram contains significant contributions from distal sources that blur the distinction between anatomical and functional reentries. Moreover, when mapping the 3D atrial model, remote activity generated false phase singularities at locations without local reentrant excitation patterns. Conclusions: Far-field contributions to electrograms during AF reduce the accuracy of detecting and interpreting reentrant activity. Highlights: Far-field effect reduces accuracy of multi-electrode maps of fibrillatory waves. Far-field could lead to false reentries in multi-electrode recordings maps. Distinction of anatomical and functional reentries is blurred by far-field effect. Phase mapping is effective for characterizing low amplitude fibrillatory waves. Low spatial resolution worsens phase mapping for small electrode-tissue distances.