Dynamic Approximate Entropy Electroanatomic Maps Detect Rotors in a Simulated Atrial Fibrillation Model
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Novák, Daniel
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There is evidence that rotors could be drivers that maintain atrial fibrillation.
Complex fractionated atrial electrograms have been located in rotor tip areas.
However, the concept of electrogram fractionation, defined using time intervals, is
still controversial as a tool for locating target sites for ablation. We hypothesize that
the fractionation phenomenon is better described using non-linear dynamic
measures, such as approximate entropy, and that this tool could be used for
locating the rotor tip. The aim of this work has been to determine the relationship
between approximate entropy and fractionated electrograms, and to develop a new
tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial
fibrillation were simulated in a 3D human atrial model, in which rotors were
observed. Dynamic approximate entropy maps were calculated using unipolar
electrogram signals generated over the whole surface of the 3D atrial model. In
addition, we optimized the approximate entropy calculation using two real multimulticenter
databases of fractionated electrogram signals, labeled in 4 levels of
fractionation. We found that the values of approximate entropy and the levels of
fractionation are positively correlated. This allows the dynamic approximate entropy
maps to localize the tips from stable and meandering rotors. Furthermore, we
assessed the optimized approximate entropy using bipolar electrograms generated
over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that
high approximate entropy values are able to detect a high level of fractionation andto locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic
approximate entropy maps could become a tool for atrial fibrillation rotor mapping.
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