title: Consistency of the CFAE phenomena using custom software for automated detection of complex fractionated atrial electrograms (CFAEs) in the left atrium during atrial fibrillation.
abstract: BACKGROUND
  Complex fractionated atrial electrograms (CFAEs) have been described as a potential target for ablation of atrial fibrillation (AF). The purpose of this study is to assess the consistency of the CFAE phenomena using custom software for automated detection of CFAEs in the left atrium during AF.
  
  
  RESULTS
  This prospective study included 10 patients referred for catheter ablation of symptomatic drug-refractory AF. Ten consecutive points at a single location (cluster) were acquired as electroanatomical points every 3 seconds. Atrial signals were automatically classified as CFAEs by the software algorithm. The number of intervals between 50 ms and 110 ms and in the voltage range 0.05-0.15 mV during the 2.5-second recordings was determined and referred to as the interval confidence level (ICL). A total of 2,226 points were acquired during mapping of AF. A dominant group of ICL using one of two different configurations of ICL fractionation was identified. A dominant group was defined as the ICL categorization occurring with greatest frequency in a given cluster of points. The results show the consistency ranged from 73%+/- 21 for the three-group configuration (ICL < or = 4; 4 < ICL < or = 7; ICL > 7) to 84%+/- 16 for the two-group configuration (ICL < or = 5; ICL > 5).
  
  
  CONCLUSIONS
  This novel software offers an objective method for CFAE analysis during atrial fibrillation. CFAE consistency ranged from 73% to 84% with wide standard deviation. Automated detection of CFAEs may remove the pitfalls associated with subjective visual detection, thus removing one variable in comparative studies of using CFAEs as AF ablation targets.
authors.affiliation: Florida Heart Institute, Florida Hospital, Orlando, Florida 32803, USA.
authors.forename: George
authors.initials: G
authors.lastname: Monir
authors.forename: Scott J
authors.initials: SJ
authors.lastname: Pollak
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001281:Atrial Fibrillation / Q000175:diagnosis* / Q000601:surgery; D018780:Body Surface Potential Mapping / Q000379:methods*; D017115:Catheter Ablation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006325:Heart Atria; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software