Surpoint algorithm for improved guidance of ablation for ventricular tachycardia (SURFIRE‐VT): A pilot study

Author:

Sanders David1,Du‐Fay‐de‐Lavallaz Jeanne M.2,Winterfield Jeffrey3,Santangeli Pasquale4ORCID,Liang Jackson5ORCID,Rhodes Paul6,Ravi Venkatesh1ORCID,Badertscher Patrick2,Mazur Alexander1,Larsen Timothy1,Sharma Parikshit S.1,Huang Henry D.1ORCID

Affiliation:

1. Department of Cardiology Rush University Medical Center Chicago Illinois USA

2. Department of Cardiology University Hospital of Basel Basel Switzerland

3. Department of Cardiology Medical University of South Carolina Charleston South Carolina USA

4. Department of Cardiology Cleveland Clinic Cleveland Ohio USA

5. Department of Cardiology University of Michigan Ann Arbor Michigan USA

6. Biosense‐Webster Irvine California USA

Abstract

AbstractIntroductionThe utility of ablation index (AI) to guide ventricular tachycardia (VT) ablation in patients with structural heart disease is unknown. The aim of this study was to assess procedural characteristics and clinical outcomes achieved using AI‐guided strategy (target value 550) or conventional non‐AI‐guided parameters in patients undergoing scar‐related VT ablation.MethodsConsecutive patients (n = 103) undergoing initial VT ablation at a single center from 2017 to 2022 were evaluated. Patient groups were 1:1 propensity‐matched for baseline characteristics. Single lesion characteristics for all 4707 lesions in the matched cohort (n = 74) were analyzed. The impact of ablation characteristics was assessed by linear regression and clinical outcomes were evaluated by Cox proportional hazard model.ResultsAfter propensity‐matching, baseline characteristics were well‐balanced between AI (n = 37) and non‐AI (n = 37) groups. Lesion sets were similar (scar homogenization [41% vs. 27%; p = .34], scar dechanneling [19% vs. 8%; p = .18], core isolation [5% vs. 11%; p = .4], linear and elimination late potentials/local abnormal ventricular activities [35% vs. 44%; p = .48], epicardial mapping/ablation [11% vs. 14%; p = .73]). AI‐guided strategy had 21% lower procedure duration (−47.27 min, 95% confidence interval [CI] [−81.613, −12.928]; p = .008), 49% lower radiofrequency time per lesion (−13.707 s, 95% CI [−17.86, −9.555]; p < .001), 21% lower volume of fluid administered (1664 cc [1127, 2209] vs. 2126 cc [1750, 2593]; p = .005). Total radiofrequency duration (−339 s [−24%], 95%CI [−776, 62]; p = .09) and steam pops (−155.6%, 95% CI [19.8%, −330.9%]; p = .08) were nonsignificantly lower in the AI group. Acute procedural success (95% vs. 89%; p = .7) and VT recurrence (0.97, 95% CI [0.42–2.2]; p = .93) were similar for both groups. Lesion analysis (n = 4707) demonstrated a plateau in the magnitude of impedance drops once reaching an AI of 550–600.ConclusionIn this pilot study, an AI‐guided ablation strategy for scar‐related VT resulted in shorter procedure time and average radiofrequency time per lesion with similar acute procedural and intermediate‐term clinical outcomes to a non‐AI‐guided approach utilizing traditional ablation parameters.

Publisher

Wiley

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