Literature DB >> 20617382

Optimizing local capture of atrial fibrillation by rapid pacing: study of the influence of tissue dynamics.

Laurent Uldry1, Nathalie Virag, Vincent Jacquemet, Jean-Marc Vesin, Lukas Kappenberger.   

Abstract

While successful termination by pacing of organized atrial tachycardias has been observed in patients, rapid pacing of AF can induce a local capture of the atrial tissue but in general no termination. The purpose of this study was to perform a systematic evaluation of the ability to capture AF by rapid pacing in a biophysical model of the atria with different dynamics in terms of conduction velocity (CV) and action potential duration (APD). Rapid pacing was applied during 30 s at five locations on the atria, for pacing cycle lengths in the range 60-110% of the mean AF cycle length (AFCL(mean)). Local AF capture could be achieved using rapid pacing at pacing sites located distal to major anatomical obstacles. Optimal pacing cycle lengths were found in the range 74-80% AFCL(mean) (capture window width: 14.6 ± 3% AFCL(mean)). An increase/decrease in CV or APD led to a significant shrinking/stretching of the capture window. Capture did not depend on AFCL, but did depend on the atrial substrate as characterized by an estimate of its wavelength, a better capture being achieved at shorter wavelengths. This model-based study suggests that a proper selection of the pacing site and cycle length can influence local capture results and that atrial tissue properties (CV and APD) are determinants of the response to rapid pacing.

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Year:  2010        PMID: 20617382     DOI: 10.1007/s10439-010-0122-3

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  6 in total

Review 1.  Computational modeling of the human atrial anatomy and electrophysiology.

Authors:  Olaf Dössel; Martin W Krueger; Frank M Weber; Mathias Wilhelms; Gunnar Seemann
Journal:  Med Biol Eng Comput       Date:  2012-06-21       Impact factor: 2.602

2.  Estimating the time scale and anatomical location of atrial fibrillation spontaneous termination in a biophysical model.

Authors:  Laurent Uldry; Vincent Jacquemet; Nathalie Virag; Lukas Kappenberger; Jean-Marc Vesin
Journal:  Med Biol Eng Comput       Date:  2012-01-21       Impact factor: 2.602

Review 3.  Mathematical approaches to understanding and imaging atrial fibrillation: significance for mechanisms and management.

Authors:  Natalia A Trayanova
Journal:  Circ Res       Date:  2014-04-25       Impact factor: 17.367

Review 4.  How computer simulations of the human heart can improve anti-arrhythmia therapy.

Authors:  Natalia A Trayanova; Kelly C Chang
Journal:  J Physiol       Date:  2016-01-18       Impact factor: 5.182

Review 5.  Computational models in cardiology.

Authors:  Steven A Niederer; Joost Lumens; Natalia A Trayanova
Journal:  Nat Rev Cardiol       Date:  2019-02       Impact factor: 32.419

6.  Optimisation of ionic models to fit tissue action potentials: application to 3D atrial modelling.

Authors:  Amr Al Abed; Tianruo Guo; Nigel H Lovell; Socrates Dokos
Journal:  Comput Math Methods Med       Date:  2013-07-01       Impact factor: 2.238

  6 in total

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