An automated fractionation mapping algorithm using optimal parameters identified 79% of VT ablation sites and generated 42.3 cm2 of fractionated area vs 4.9 cm2 in controls (P=0.001).
Observational (n=21)
Does an automated fractionation mapping algorithm accurately identify successful ablation sites in patients with scar-based ventricular tachycardia?
An automated fractionation mapping algorithm with optimized parameters can accurately identify successful ablation sites in scar-based VT, potentially reducing procedure time.
Absolute Event Rate: 42.3% vs 4.9%
p-value: p=0.001
Abstract Background Mapping and ablation of fractionated electrograms is a common treatment for scar‐based ventricular tachycardia (VT). An automated algorithm has been developed for rapid “fractionation mapping.” Methods Electroanatomic maps from 21 ablation procedures (14 scar‐based VT and seven control idiopathic VT/premature ventricular contractions with normal voltage) were retrospectively analyzed using the Ensite Precision fractionation map (fMap; Abbott Laboratories; Abbott Park, IL, USA) algorithm. For each study, voltage maps and 30 fMaps were generated using combinations of parameters: width (5, 10, 20 ms), refractory time (15, 30 ms), sensitivity (0.1, 0.2 mV), and fractionation threshold (2, 3, 5). Parameter sensitivity was assessed by overlap of fractionated areas (fArea) with successful VT ablation sites (defined by entrainment and/or pace mapping). Specificity was assessed by presence of fractionated areas in control patients. Results Of the 30 fMap parameter sets tested, seven identified >50% of scar‐based VT ablation sites, and 26 contained <5 cm 2 fractionation on control fMaps. Three combinations of fMap width/refractory/sensitivity/threshold parameters met both of the above criteria, and 20/30/0.1/2 identified the most VT ablation sites (79%) and generated 42.3 ± 28.2 cm 2 of fArea on scar‐based VT maps compared with 4.9 ± 3.2 cm 2 on control maps ( P = .001). None of the control patients and 23% of the scar‐based VT patients had VT recurrence at mean 15 month follow‐up. Conclusion Careful selection of signal processing parameters optimizes sensitivity and specificity of automated fractionation mapping for scar‐based VT. Real‐time use of fMap algorithms may reduce VT ablation procedure time and improve substrate modification, which may improve outcomes.
Launer et al. (Mon,) conducted a observational in Scar-based ventricular tachycardia (n=21). Automated fractionation mapping algorithm (Ensite Precision fMap) vs. Control idiopathic VT/PVCs with normal voltage was evaluated on Fractionated area (fArea) generated (p=0.001). An automated fractionation mapping algorithm using optimal parameters identified 79% of VT ablation sites and generated 42.3 cm2 of fractionated area vs 4.9 cm2 in controls (P=0.001).