AIMS: Catheter ablation for paroxysmal atrial fibrillation (AF) is rapidly becoming a standard practice. There is literature to support that catheter ablation of persistent AF requires additional 'substrate modification'. In clinical practice, operators rely on automated fractionation maps created by three-dimensional anatomic mapping systems to rapidly assess complex 'fractionated' signals (CFAE). These systems use differing algorithms to automate the process. The agreement between operators and contemporary algorithms has not been examined. We sought to assess the agreement between operators and a novel method of quantification calculating percentage fractionation (PF). METHODS AND RESULTS: Expert opinion on 80 atrial electrogram 4 s signals of varying levels of activity were gathered and pooled for comparison. Twelve independent experts visually quantified the signal fractionation and offered a threshold level for ablation. We developed an algorithm to find sites with high continuous electrical activity, or high PF. Correlation between experts and PF was 0.78 [P < 0.01, 95% confidence interval (CI) (0.68-0.86)]. Receiver operating characteristics curve sensitivity and specificity for PF were 0.7727 and 0.8103 at the optimal cut-off point of 58.45 PF with area under curve 0.89 CI (0.80-0.99). CONCLUSION: The PF statistic represents a more robust and intuitive measure to represent fractionated atrial activity; importantly it demonstrates excellent agreement with expert users and presents a new standard for algorithm assessment. Use of a PF statistic should be considered in automated mapping systems.
AIMS: Catheter ablation for paroxysmal atrial fibrillation (AF) is rapidly becoming a standard practice. There is literature to support that catheter ablation of persistent AF requires additional 'substrate modification'. In clinical practice, operators rely on automated fractionation maps created by three-dimensional anatomic mapping systems to rapidly assess complex 'fractionated' signals (CFAE). These systems use differing algorithms to automate the process. The agreement between operators and contemporary algorithms has not been examined. We sought to assess the agreement between operators and a novel method of quantification calculating percentage fractionation (PF). METHODS AND RESULTS: Expert opinion on 80 atrial electrogram 4 s signals of varying levels of activity were gathered and pooled for comparison. Twelve independent experts visually quantified the signal fractionation and offered a threshold level for ablation. We developed an algorithm to find sites with high continuous electrical activity, or high PF. Correlation between experts and PF was 0.78 [P < 0.01, 95% confidence interval (CI) (0.68-0.86)]. Receiver operating characteristics curve sensitivity and specificity for PF were 0.7727 and 0.8103 at the optimal cut-off point of 58.45 PF with area under curve 0.89 CI (0.80-0.99). CONCLUSION: The PF statistic represents a more robust and intuitive measure to represent fractionated atrial activity; importantly it demonstrates excellent agreement with expert users and presents a new standard for algorithm assessment. Use of a PF statistic should be considered in automated mapping systems.