Key result
Automatic annotation of local activation time showed good correlation with manual annotation (r = 0.655; P < 0.0001), despite a systematic delayed detection of LAT by the automatic system.
Why the study?
Does automatic local activation time annotation correlate with manual annotation and accurately identify the effective ablation site in patients undergoing focal PVC ablation?
Observational (n=40)
Yes
Does automatic local activation time annotation correlate with manual annotation and accurately identify the effective ablation site in patients undergoing focal PVC ablation?
Effect estimate: r = 0.655
p-value: p=< 0.0001
Automatic local activation time annotation correlates well with manual annotation and accurately identifies the effective ablation site during focal PVC ablation, despite a systematic delay in LAT detection.
May support automated LAT mapping for PVC ablation site selection; leaves open prospective validation of systematic delay effects.
Aims: Current navigation systems incorporate algorithms for automatic identification of local activation time (LAT). However, data about their utility and accuracy in premature ventricular complex (PVC) ablation procedures are scarce. This study analyses the accuracy of an algorithmic method based on automatic annotation of the maximal negative slope of the unipolar electrogram within the window demarcated by the bipolar electrogram compared with conventional manual annotation during PVC ablation procedures. Methods and results: Forty patients with successful ablation of focal PVC in three centres were included. Electroanatomical activation maps obtained with the automatic system (WF-map) were compared with manual annotation maps (M-map). Correlation and concordance of LAT obtained with both methods were assessed at 3536 points. The distance between the earliest activation site (EAS) and the effective radiofrequency application point (e-RFp) were determined in M-map and WF-map. The distance between WF-EAS and M-EAS was assessed. Successful ablation sites included left ventricular outflow tract (LVOT; 55%), right ventricular outflow tract (40%), and tricuspid annulus (5%). Good correlation was observed between the two annotation approaches (r = 0.655; P < 0.0001). Bland-Altman analysis revealed a systematic delayed detection of LAT by WF-map (bias 33.8 ± 30.9 ms), being higher in LVOT than in the right ventricle (42.6 ± 29.2 vs. 27.2 ± 30.5 ms, respectively; P < 0.0001). No difference in EAS-eRFp distance was observed between M-map and WF-map (1.8 ± 2.8 vs. 1.8 ± 3.4 mm, respectively; P = 0.986). The median (interquartile range) distance between WF-EAS and M-EAS was 2.2(0-6) mm. Conclusion: Good correlation was found between M-map and WF-map. Local activation time detection was systematically delayed in WF-map, especially in LVOT. Accurate identification of e-RFp was achieved with both annotation approaches.
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Acosta et al. (2017) conducted an observational in Focal premature ventricular complex (PVC) (n=40). Automatic annotation of local activation time (WF-map) vs. Conventional manual annotation (M-map) was evaluated on Correlation of local activation time between automatic and manual annotation (r = 0.655, p=< 0.0001). Automatic annotation of local activation time showed good correlation with manual annotation (r = 0.655; P < 0.0001), despite a systematic delayed detection of LAT by the automatic system.
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