Why the study?
Left atrial rapid AF activity co-localises with areas of successful AF termination by catheter ablation, prompting a technique to identify rapid and regular activity.
Does dominant cycle length (DCL) using kernel density estimation correlate with dominant frequency and averaging in identifying rapid atrial activity in patients with persistent AF?
Does dominant cycle length (DCL) using kernel density estimation correlate with dominant frequency and averaging in identifying rapid atrial activity in patients with persistent AF?
Dominant cycle length calculated via kernel density estimation correlates with dominant frequency and averaging, offering a potential tool to identify rapid atrial activity and psAF drivers for targeted ablation.
May aid identification of rapid atrial activity in persistent AF; leaves open whether it improves ablation targeting.
PURPOSE: Left atrial (LA) rapid AF activity has been shown to co-localise with areas of successful atrial fibrillation termination by catheter ablation. We describe a technique that identifies rapid and regular activity. METHODS: Eight-second AF electrograms were recorded from LA regions during ablation for psAF. Local activation was annotated manually on bipolar signals and where these were of poor quality, we inspected unipolar signals. Dominant cycle length (DCL) was calculated from annotation pairs representing a single activation interval, using a probability density function (PDF) with kernel density estimation. Cumulative annotation duration compared to total segment length defined electrogram quality. DCL results were compared to dominant frequency (DF) and averaging. RESULTS: In total 507 8 s AF segments were analysed from 7 patients. Spearman's correlation coefficient was 0.758 between independent annotators (P < 0.001), 0.837-0.94 between 8 s and ≥ 4 s segments (P < 0.001), 0.541 between DCL and DF (P < 0.001), and 0.79 between DCL and averaging (P < 0.001). Poorer segment organization gave greater errors between DCL and DF. CONCLUSION: DCL identifies rapid atrial activity that may represent psAF drivers. This study uses DCL as a tool to evaluate the dynamic, patient specific properties of psAF by identifying rapid and regular activity. If automated, this technique could rapidly identify areas for ablation in psAF.
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Nagy et al. (2021) studied this question.
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