Journal Article
Cycle Length Evaluation in Persistent Atrial Fibrillation Using Kernel Density Estimation to Identify Transient and Stable Rapid Atrial Activity
Szabolcs Z. Nagy; Patrick Kasi; Valtino X. Afonso; Nathaniel Bird; Brian Pederson; Ian E. Mann; Steven Kim; Nicholas W. F. Linton; David C. Lefroy; Zachary I. Whinnett; Fu Siong Ng; Michael Koa-Wing; Prapa Kanagaratnam; Nicholas S. Peters; Norman A. Qureshi; Phang Boon Lim
Cardiovascular Engineering and Technology · Vol. 13, Issue 2 · pp. 219-233 · 2022
Abstract
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.