Characterization of temporal electrical activity patterns for detection of critical isthmus regions of recurrent atypical atrial flutter

Author:

Vonderlin Nadine12,Siebermair Johannes12,Mahabadi Amir1,Pesch Elena1ORCID,Koehler Miriam1,Dobrev Dobromir345,Janosi Rolf Alexander1,Rassaf Tienush1,Wakili Reza126ORCID

Affiliation:

1. Department of Cardiology and Vascular Medicine, West‐German Heart and Vascular Center Essen, University of Essen Medical School University Duisburg‐Essen Essen Germany

2. German Centre for Cardiovascular Research (DZHK) Berlin Germany

3. Institute of Pharmacology, West German Heart and Vascular Center University Duisburg‐Essen Essen Germany

4. Department of Molecular Physiology and Biophysics Baylor College of Medicine Houston Texas USA

5. Department of Medicine and Research Center, Montreal Heart Institute Université de Montréal Montréal Quebec Canada

6. Department of Cardiology and Vascular Medicine, University Hospital Frankfurt Goethe University Frankfurt Germany

Abstract

AbstractIntroductionIdentifying the critical isthmus region (CIR) of atrial re‐entry tachycardias (AT) is challenging. The Lumipoint® (LP) software, developed for the Rhythmia® mapping system, aims to facilitate the successful ablation of ATs by identifying the CIR.ObjectiveThe objective of this study was to evaluate the quality of LP regarding the percentage of arrhythmia‐relevant CIR in patients with atypical atrial flutter (AAF).MethodsIn this retrospective study, we analyzed 57 AAF forms. Electrical activity (EA) was mapped over tachycardia cycle length resulting in a two‐dimensional EA pattern. The hypothesis was that EA minima suggest potential CIRs with slow‐conduction‐zone.ResultsA total of n = 33 patients were included, with the majority of patients being already preablated (69.7%). LP algorithm identified a mean of 2.4 EA minima and 4.4 suggested CIRs per AAF form. Overall, we observed a low probability of identifying only the relevant CIR (POR) at 12.3% but a high probability that at least one CIR is detected (PALO) at 98.2%. Detailed analysis revealed EA minima depth (≤20%) and width (>50 ms) as the best predictors of relevant CIRs. Wide minima occurred rarely (17.5%), while low minima were more frequently present (75.4%). Minima depth of EA ≤ 20% showed the best PALO/POR overall (95% and 60%, respectively). Analysis in recurrent AAF ablations (five patients) revealed that CIR in de novo AAF was already detected by LP during the index procedure.ConclusionThe LP algorithm provides an excellent PALO (98.2%), but poor POR (12.3%) to detect the CIR in AAF. POR improved by preselection of the lowest and widest EA minima. In addition, there might be the role of initial bystander CIRs becoming relevant for future AAFs.

Publisher

Wiley

Subject

Cardiology and Cardiovascular Medicine,General Medicine

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