4.7 Article

Searching for order in atrial fibrillation using electrogram morphology recurrence plots

Journal

COMPUTERS IN BIOLOGY AND MEDICINE
Volume 65, Issue -, Pages 220-228

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2015.07.018

Keywords

Atrial fibrillation; Electrograms; Dynamics; Mapping; Non-linear analysis

Funding

  1. American Heart Association [12GRNT12070241]
  2. NIH National Heart Lung and Blood Institute [R01 HL093490]

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Background: Bipolar electrograms recorded during atrial fibrillation (AF) can have an appearance of chaotic/random behavior. The aim of this study was to use a novel electrogram morphology recurrence (EMR) analysis to quantify the level of order in the morphology patterns in AF. Methods: Rapid atrial pacing was performed in seven dogs at 600 bpm for 3 weeks leading to sustained AF. Open chest high density electrical recordings were made in multiple atrial sites. EMR plots of bipolar electrograms at each site were created by cross-correlating morphologies of each detected activations with morphologies of every other activation. The following features of the EMR plots were quantified: recurrence rate (RR), determinism (DET), laminarity (LAM), average diagonal line length (L), trapping time (TT), divergence (DIV), and Shannon's entropy (ENTR). For each recording site, these measures were calculated for the normal sequence of morphologies and also after random shuffling of the electrogram orders. Results: Electrograms recordings from a total of 3961 sites had average cycle lengths of 104 +/- 22 ms resulting in an average of 100 +/- 19 activations detected per 10-s recording and an average RR of 0.38 +/- 0.28 (range 0.02-1.00). Shuffling the order of the activation morphologies resulted in significant decreases in DET, LAM, L, TT, and ENTR and significant increases in DIV. Conclusions: EMR plots of AF electrograms show varying rates of recurrence with patterns that suggest an underlying deterministic structure to the activation sequences. A better understanding of AF dynamics could lead to improved methods in mapping and treating AF. (C) 2015 Elsevier Ltd. All rights reserved.

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