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Characterization of temporal electrical activity patterns for detection of critical isthmus regions of recurrent atypical atrial flutter
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  • Nadine Vonderlin,
  • Johannes Siebermair,
  • Elena Pesch,
  • Miriam Köhler,
  • Lisa Riesinger,
  • Elif Kaya,
  • Simon Kochhäuser,
  • Rolf Janosi,
  • Tienush Rassaf,
  • Reza Wakili
Nadine Vonderlin
West-German Heart and Vascular Center Essen, University of Essen Medical School, University Duisburg-Essen
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Johannes Siebermair
West-German Heart and Vascular Center Essen, University of Essen Medical School, University Duisburg-Essen
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Elena Pesch
West-German Heart and Vascular Center Essen, University of Essen Medical School, University Duisburg-Essen
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Miriam Köhler
West-German Heart and Vascular Center Essen, University of Essen Medical School, University Duisburg-Essen
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Lisa Riesinger
West German Heart Centre Essen
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Elif Kaya
University Hospital Essen
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Simon Kochhäuser
West-German Heart and Vascular Center Essen, University of Essen Medical School, University Duisburg-Essen
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Rolf Janosi
West-German Heart and Vascular Center Essen, University of Essen Medical School, University Duisburg-Essen
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Tienush Rassaf
West-German Heart and Vascular Center Essen, University of Essen Medical School, University Duisburg-Essen
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Reza Wakili
West-German Heart and Vascular Center Essen, University of Essen Medical School, University Duisburg-Essen
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Abstract

Introduction Identifying the critical isthmus region (CIR) of complex atrial tachycardias (AT) is challenging. The Lumipoint® (LP) software, developed for the Rhythmia® mapping system, aims to facilitate successful termination of ATs by identifying the CIR. Objective Objective of this study was to evaluate specificity and sensitivity of LP regarding arrhythmia-relevant CIR detection in patients with atypical-atrial-flutter (AAF). Methods In this retrospective analysis we analyzed 57 AAF-forms. Electrical activity (EA) was mapped over tachycardia cycle length resulting in 2-dimensional EA pattern. The hypothesis was that an EA minimum suggests a potential CIR with slow-conduction-zone. Results A total of n=33 patients were included. LP-algorithm identified a mean of 2.4 EA minima and 4.4 suggested CIRs per AAF-form. Overall, we observed a low specificity with 12.3% but a high sensitivity of 98.2%. Detailed EA analysis revealed that depth (≤20%) and width (>50ms) of EA minima were the best predictors of relevant CIRs. Wide minima occurred rarely (17.5%), while low minima were more frequently present (75.4%). Minima with a depth of EA≤20% showed the best sensitivity and specificity overall (95% and 60%, respectively). Analysis in recurrent ablations in 5 patients presenting de-novo AAF revealed that the CIR of de-novo AAF was already detected by LP during the index procedure. Conclusion The LP algorithm provides an excellent sensitivity (98.2%), but poor specificity (12.3%) to detect the CIR in AAF. Specificity improved by preselection of the lowest and widest EA minima. In addition, there might be role of initial bystander CIRs becoming relevant for future AAFs