6533b7d1fe1ef96bd125d7a7

RESEARCH PRODUCT

Quantification of synchronization during atrial fibrillation by Shannon entropy: Validation in patients and computer model of atrial arrhythmias

Marco ScaglioneLuca FaesMichela MasèRenzo AntoliniFlavia Ravelli

subject

Signal processingmedicine.medical_specialtyTime delaysPhysiologyEntropyBiomedical EngineeringBiophysicsSensitivity and SpecificitySynchronizationHeart Conduction SystemArrhythmia (mechanisms)Internal medicinePhysiology (medical)medicineHumansIn patientDiagnosis Computer-AssistedMathematicsBody Surface Potential MappingModels CardiovascularCardiac arrhythmiaReproducibility of ResultsAtrial fibrillationAtrial arrhythmiasComputer simulationmedicine.diseaseAtrial fibrillationElectrophysiologyElectrophysiologymedicine.anatomical_structureBiophysicCardiologyRight atriumAlgorithms

description

Atrial fibrillation (AF), a cardiac arrhythmia classically described as completely desynchronized, is now known to show a certain amount of synchronized electrical activity. In the present work a new method for quantifying the level of synchronization of the electrical activity recorded in pairs of atrial sites during atrial fibrillation is presented. A synchronization index (Sy) was defined by quantifying the degree of complexity of the distribution of the time delays between sites by Shannon entropy estimation. The capability of Sy to discriminate different AF types in patients was assessed on a database of 60 pairs of endocardial recordings from a multipolar basket catheter. The analysis showed a progressive and significant decrease of Sy with increasing AF complexity classes as defined by Wells (AF type I Sy = 0.73 ± 0.07, type II Sy = 0.56 ± 0.07, type III Sy = 0.36 ± 0.04, p < 0.001). The extension of Sy calculation to the whole right atrium showed the existence of spatial heterogeneities in the synchronization level. Moreover, experiments simulated by a computer model of atrial arrhythmias showed that propagation patterns with different complexity could be the basis of different synchronization levels found in patients. In conclusion the quantification of synchronization by Shannon entropy estimation of time delay dispersion may facilitate the identification of different propagation patterns associated with AF, thus enhancing our understanding of AF mechanisms and helping in its treatment. © 2005 IOP Publishing Ltd.

10.1088/0967-3334/26/6/003http://hdl.handle.net/10447/276975