INTRODUCTION: Different analysis techniques have been developed to help understand and characterize the mechanisms responsible for atrial arrhythmias. We tested the hypothesis that Fast Fourier Transform (FFT) analysis of recorded atrial electrograms (AEGs) will rapidly and accurately identify regular and irregular patterns of atrial activation, and, thereby, may provide evidence suggestive of underlying mechanisms of atrial tachyarrhythmias. METHODS AND RESULTS: During induced atrial tachyarrhythmias in both the canine sterile pericarditis model and canine rapid ventricular pacing-induced congestive heart failure model; 380-404 AEGs were recorded simultaneously from epicardial electrodes on both atria. From AEGs, atrial activation sequences were determined during atrial flutter (AFL), focal atrial tachycardia (AT), and atrial fibrillation (AF). Four-second recording segments of each AEG were subjected to FFT analysis. Frequencies found during FFT analyses in all studies precisely corresponded to the cycle lengths of the AEGs. In AFL and AT, one dominant frequency peak was found throughout both atria. In AF due to multiple unstable reentry circuits, multiple and broad frequency peaks were found in both atria. In AF due to a stable rapid rhythm (driver) in the left atrium with fibrillatory conduction to the rest of the atria, one dominant frequency peak in areas with 1:1 conduction from the driver, and multiple and/or broad frequency peaks in areas with fibrillatory conduction produced by the driver were found. Computation time for all FFT analyses took <5 minutes. CONCLUSION: FFT analysis accurately and rapidly identifies global atrial activation patterns during AFL, AT, and AF, thereby assisting in determining arrhythmia mechanisms.
INTRODUCTION: Different analysis techniques have been developed to help understand and characterize the mechanisms responsible for atrial arrhythmias. We tested the hypothesis that Fast Fourier Transform (FFT) analysis of recorded atrial electrograms (AEGs) will rapidly and accurately identify regular and irregular patterns of atrial activation, and, thereby, may provide evidence suggestive of underlying mechanisms of atrial tachyarrhythmias. METHODS AND RESULTS: During induced atrial tachyarrhythmias in both the canine sterile pericarditis model and canine rapid ventricular pacing-induced congestive heart failure model; 380-404 AEGs were recorded simultaneously from epicardial electrodes on both atria. From AEGs, atrial activation sequences were determined during atrial flutter (AFL), focal atrial tachycardia (AT), and atrial fibrillation (AF). Four-second recording segments of each AEG were subjected to FFT analysis. Frequencies found during FFT analyses in all studies precisely corresponded to the cycle lengths of the AEGs. In AFL and AT, one dominant frequency peak was found throughout both atria. In AF due to multiple unstable reentry circuits, multiple and broad frequency peaks were found in both atria. In AF due to a stable rapid rhythm (driver) in the left atrium with fibrillatory conduction to the rest of the atria, one dominant frequency peak in areas with 1:1 conduction from the driver, and multiple and/or broad frequency peaks in areas with fibrillatory conduction produced by the driver were found. Computation time for all FFT analyses took <5 minutes. CONCLUSION: FFT analysis accurately and rapidly identifies global atrial activation patterns during AFL, AT, and AF, thereby assisting in determining arrhythmia mechanisms.
Authors: Thomas H Everett; Emily E Wilson; Sander Verheule; Jose M Guerra; Scott Foreman; Jeffrey E Olgin Journal: Am J Physiol Heart Circ Physiol Date: 2006-07-28 Impact factor: 4.733
Authors: Catalina Tobón; Carlos A Ruiz-Villa; Elvio Heidenreich; Lucia Romero; Fernando Hornero; Javier Saiz Journal: PLoS One Date: 2013-02-11 Impact factor: 3.240