Key result
Bipolar electrogram attributes effectively detect AF rotor regions despite non-conductive fibrosis in in-silico models.
Why the study?
The occurrence and characteristics of rotors described by phase singularities in the presence of non-conductive fibrotic areas during AF required investigation.
How do non-conductive fibrotic areas of varying densities affect the occurrence and characteristics of phase singularities and bipolar EGM attributes in an in-silico model of atrial fibrillation?
How do non-conductive fibrotic areas of varying densities affect the occurrence and characteristics of phase singularities and bipolar EGM attributes in an in-silico model of atrial fibrillation?
Bipolar electrogram attributes such as sample entropy and determinism offer a complementary method for detecting rotors in the presence of non-conductive fibrosis during atrial fibrillation.
In-silico cardiac patches with a non-conductive fibrotic areas were used to investigate the occurrence and characteristics of rotors described by phase singularities (PSs). A rotor was generated in a virtual tissue patch represented by a Courtemanche model adapted to mimic AF conditions. Non-conductive fibrotic elements were incorporated around the center of the patch (densities of 20%, 30%, and 40%). Electrograms (EGMs) were calculated and their phase was determined using Hilbert transform. PSs were detected and PS density maps (PSDMs) were generated. Six attributes were used to investigate bipolar EGMs obtained from the original signals: sample entropy (SampEn), determinism (DET), peak-to-peak (PP), wave similarity (WS), organization index (OI), and cycle length (CL). 77.1% of the PSs occurred inside the fibrotic regionwith a higher density in the border zonefor 20% density; 99.8% for 30%; 99.7% for 40%. SampEn was significantly higher in regions with PSDM5, while DET, PP, and WS were significantly lower (P<0.0001). PSs tended to meander outside the fibrotic area for lower fibrotic density. Bipolar EGM attributes offer a complementary way for rotor detection in the presence of non-conductive fibrosis.
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Almeida et al. (2020) studied Atrial Fibrillation. Bipolar EGM attributes (SampEn, DET, WS, PP) vs. Regions without phase singularities was evaluated on Detection of regions with phase singularities (PSDM ≥ 5) (p=<0.0001). In an in-silico cardiac patch model of atrial fibrillation, bipolar electrogram attributes such as sample entropy and wave similarity effectively detected regions with rotors in the presence of non-conductive fibrosis.
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