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Circ Arrhythm Electrophysiol ; 8(2): 447-55, 2015 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-25740825

RESUMO

BACKGROUND: High-frequency periodic sources during cardiac fibrillation can be detected by phase mapping techniques. To enable practical therapeutic options for modulating periodic sources (existing techniques require high density multielectrode arrays and real time simultaneous mapping capability), a method to identify electrogram morphologies colocalizing to rotors that can be implemented on few electrograms needs to be devised. METHOD AND RESULTS: Multichannel ventricular fibrillation electrogram data from 7 isolated human hearts using Langendorff setup and intraoperative clinical data from 2 human hearts were included in the analysis. The spatial locations of rotors were identified using phase maps constructed from 112 electrograms. Electrograms were analyzed for repeating patterns and discriminating signal morphologies around the locations of rotors and nonrotors were identified and quantified. Features were extracted from the unipolar electrogram patterns, which corroborated well with the spatial location of rotors. The results suggest that using the proposed modulation index feature, and as low as 1 sample point in the vicinity of the rotors, an accuracy as high as 86% (P<0.001) was obtained in separating rotor locations versus nonrotor locations. The analysis of bipolar electrogram signatures in the vicinity of the rotor locations suggest that 62.5% of the rotors occur at locations where the bipolar electrogram demonstrates continuous activities during ventricular fibrillation. CONCLUSIONS: Unipolar electrogram extracted modulation index-based detection of rotors is feasible with few electrodes and has greater detection rate than bipolar approach. This strategy may be suitable for nonarray-based single mapping catheter enabled detection of rotors.


Assuntos
Eletrodos , Técnicas Eletrofisiológicas Cardíacas/instrumentação , Ventrículos do Coração/fisiopatologia , Fibrilação Ventricular/diagnóstico , Potenciais de Ação , Simulação por Computador , Entropia , Estudos de Viabilidade , Humanos , Modelos Cardiovasculares , Reconhecimento Automatizado de Padrão , Valor Preditivo dos Testes , Processamento de Sinais Assistido por Computador , Fatores de Tempo , Fibrilação Ventricular/fisiopatologia
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