BACKGROUND: Fractionated electrograms are used by some as targets for ablation in atrial and ventricular arrhythmias. Fractionation has been demonstrated to result when there is repetitive or asynchronous activation of separate groups of cells within the recording region of a mapping electrode(s). METHODS AND RESULTS: Using a computer model, we generated tissue activation patterns with increasing spatiotemporal variation and calculated virtual electrograms from electrodes with decreasing resolution. We then quantified electrogram fractionation. In addition, we recorded unipolar electrograms during atrial fibrillation in 20 patients undergoing atrial fibrillation ablation. From these we constructed bipolar electrograms with increasing interelectrode spacing and quantified fractionation. During modeling of spatiotemporal variation, fractionation varied directly with electrode length, diameter, height, and interelectrode spacing. When resolution was held constant, fractionation increased with increasing spatiotemporal variation. In the absence of spatial variation, fractionation was independent of resolution and proportional to excitation frequency. In patients with atrial fibrillation, fractionation increased as interelectrode spacing increased. CONCLUSIONS: We created a model for distinguishing the roles of spatial and temporal electric variation and electrode resolution in producing electrogram fractionation. Spatial resolution affects fractionation attributable to spatiotemporal variation but not temporal variation alone. Electrogram fractionation was directly proportional to spatiotemporal variation and inversely proportional to spatial resolution. Spatial resolution limits the ability to distinguish high-frequency excitation from overcounting. In patients with atrial fibrillation, complex fractionated atrial electrogram detection varies with spatial resolution. Electrode resolution must therefore be considered when interpreting and comparing studies of fractionation.
BACKGROUND: Fractionated electrograms are used by some as targets for ablation in atrial and ventricular arrhythmias. Fractionation has been demonstrated to result when there is repetitive or asynchronous activation of separate groups of cells within the recording region of a mapping electrode(s). METHODS AND RESULTS: Using a computer model, we generated tissue activation patterns with increasing spatiotemporal variation and calculated virtual electrograms from electrodes with decreasing resolution. We then quantified electrogram fractionation. In addition, we recorded unipolar electrograms during atrial fibrillation in 20 patients undergoing atrial fibrillation ablation. From these we constructed bipolar electrograms with increasing interelectrode spacing and quantified fractionation. During modeling of spatiotemporal variation, fractionation varied directly with electrode length, diameter, height, and interelectrode spacing. When resolution was held constant, fractionation increased with increasing spatiotemporal variation. In the absence of spatial variation, fractionation was independent of resolution and proportional to excitation frequency. In patients with atrial fibrillation, fractionation increased as interelectrode spacing increased. CONCLUSIONS: We created a model for distinguishing the roles of spatial and temporal electric variation and electrode resolution in producing electrogram fractionation. Spatial resolution affects fractionation attributable to spatiotemporal variation but not temporal variation alone. Electrogram fractionation was directly proportional to spatiotemporal variation and inversely proportional to spatial resolution. Spatial resolution limits the ability to distinguish high-frequency excitation from overcounting. In patients with atrial fibrillation, complex fractionated atrial electrogram detection varies with spatial resolution. Electrode resolution must therefore be considered when interpreting and comparing studies of fractionation.
Authors: Olaf Dössel; Martin W Krueger; Frank M Weber; Mathias Wilhelms; Gunnar Seemann Journal: Med Biol Eng Comput Date: 2012-06-21 Impact factor: 2.602
Authors: Keryn B Palmer; Nathaniel C Thompson; Peter S Spector; Jérôme Kalifa; Jason H T Bates Journal: J Clin Monit Comput Date: 2014-07-15 Impact factor: 2.502
Authors: Sanjiv M Narayan; Kalyanam Shivkumar; David E Krummen; John M Miller; Wouter-Jan Rappel Journal: Circ Arrhythm Electrophysiol Date: 2013-02-07
Authors: Nathaniel C Thompson; Justin Stinnett-Donnelly; Nicole Habel; Bryce Benson; Jason H T Bates; Burton E Sobel; Peter S Spector Journal: J Clin Monit Comput Date: 2013-09-26 Impact factor: 2.502