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American Heart Association, Circulation: Arrhythmia and Electrophysiology, 3(9)

DOI: 10.1161/circep.115.003555

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Prospective, Tissue-Specific Optimization of Ablation for Multiwavelet Reentry

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

Background— Treatment of multiwavelet reentry (MWR) remains difficult. We previously developed a metric, the fibrillogenicity index, to assess the propensity of homogeneous, 2-dimensional tissues to support MWR. In this study, we demonstrate a method by which fibrillogenicity index can be generalized to heterogeneous tissues and validate an algorithm for prospective, tissue-specific optimization of ablation to reduce MWR burden. Methods and Results— We used a computational model to simulate and measure the duration of MWR in tissues with heterogeneously distributed action potential durations and then assessed the relative efficacy of a variety of ablation strategies for reducing tissues’ ability to support MWR. We then derived and tested a strategy in which multiple linear lesions partially divided a fibrillogenic tissue into functionally equivalent subsections. The composite action potential duration of heterogeneous tissue was well approximated by an inverse sum of cellular action potential durations ( R 2 =0.82). Linear ablation more efficiently reduced MWR duration than branching ablation patterns and optimally reduced disease burden when positioned at a tissue’s functional (rather than geometric) center. The duration of MWR after application of prospective, individually optimized ablation sets fell within 4.4% (95% confidence interval, 3–5.8) of the predicted target. Conclusions— We think that this study presents a novel approach for (1) quantifying the extent of a tissue’s electric derangement, (2) prospectively determining the amount of ablation required to minimize the burden of MWR, and (3) predicting the most efficient distribution of these ablation lesions in tissue refractory to standard ablation strategies.