Rotors exhibit greater surface ECG variation during ventricular fibrillation than focal sources due to wavebreak, secondary rotors, and meander
Drs. Krummen, McCulloch, Villongco, and Ho have received grant support from the UCSD Clinical Translational Research Institute: Galvanizing Engineering in Medicine Grant. Dr. Villongco has received grant support from the NIH Training Grant (T32 HL007444). Dr. McCulloch has received grant support from the NIH National Biomedical Computation Resource (P41 RR008605).
Dr. Krummen has served as a consultant to Abbott Inc., and has received fellowship program support from Biosense-Webster, Biotronik, Boston Scientific, Medtronic, and St. Jude. Dr. Rappel is a coinventor on intellectual property owned by the University of California and licensed to Abbott. Dr. McCulloch has intellectual property and ownership interest in InSilicoMed Inc. Other authors: No disclosures.
Abstract
Introduction
Ventricular fibrillation is a common life-threatening arrhythmia. The ECG of VF appears chaotic but may allow identification of sustaining mechanisms to guide therapy.
Hypothesis
We hypothesized that rotors and focal sources manifest distinct features on the ECG, and computational modeling may identify mechanisms of such features.
Methods
VF induction was attempted in 31 patients referred for ventricular arrhythmia ablation. Simultaneous surface ECG and intracardiac electrograms were recorded using biventricular basket catheters. Endocardial phase maps were used to mechanistically classify each VF cycle as rotor or focally driven. ECGs were analyzed from patients demonstrating both mechanisms in the primary analysis and from all patients with induced VF in the secondary analysis. The ECG voltage variation during each mechanism was compared. Biventricular computer simulations of VF driven by focal sources or rotors were created and resulting ECGs of each VF mechanism were compared.
Results
Rotor-based VF exhibited greater voltage variation than focal source-based VF in both the primary analysis (n = 8, 110 ± 24% vs. 55 ± 32%, P = 0.02) and the secondary analysis (n = 18, 103 ± 30% vs. 67 ± 34%, P = 0.009). Computational VF simulations also revealed greater voltage variation in rotors compared to focal sources (110 ± 19% vs. 33 ± 16%, P = 0.001), and demonstrated that this variation was due to wavebreak, secondary rotor initiation, and rotor meander.
Conclusion
Clinical and computational studies reveal that quantitative criteria of ECG voltage variation differ significantly between VF-sustaining rotors and focal sources, and provide insight into the mechanisms of such variation. Future studies should prospectively evaluate if these criteria can separate clinical VF mechanisms and guide therapy.
