Literature DB >> 15720461

Defibrillation depends on conductivity fluctuations and the degree of disorganization in reentry patterns.

Gernot Plank1, L Joshua Leon, Shane Kimber, Edward J Vigmond.   

Abstract

UNLABELLED: Defibrillation depends on conductivity and disorganization.
INTRODUCTION: Cardiac fibrillation is the deterioration of the heart's normally well-organized activity into one or more meandering spiral waves, which subsequently break up into many meandering wave fronts. Delivery of an electric shock (defibrillation) is the only effective way of restoring the normal rhythm. This study focuses on examining whether higher degrees of disorganization requires higher shock strengths to defibrillate and whether microscopic conductivity fluctuations favor shock success. METHODS AND
RESULTS: We developed a three-dimensional computer bidomain model of a block of cardiac tissue with straight fibers immersed in a conductive bath. The membrane behavior was described by the Courtemanche human atrial action potential model incorporating electroporation and an acetylcholine- (ACh) dependent potassium current. Intracellular conductivities were varied stochastically around nominal values with variations of up to 50%. A single rotor reentry was initiated and, by adjusting the spatial ACh variation, the level of organization could be controlled. The single rotor could be stabilized or spiral wave breakup could be provoked leading to fibrillatory-like activity. For each level of organization, multiple shock timings and strengths were applied to compute the probability of shock success as a function of shock strength.
CONCLUSIONS: Our results suggest that the level of the small-scale conductivity fluctuations is a very important factor in defibrillation. A higher variation significantly lowers the required shock strength. Further, we demonstrated that success also heavily depends on the level of organization of the fibrillatory episode. In general, higher levels of disorganization require higher shock strengths to defibrillate.

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Year:  2005        PMID: 15720461     DOI: 10.1046/j.1540-8167.2005.40140.x

Source DB:  PubMed          Journal:  J Cardiovasc Electrophysiol        ISSN: 1045-3873


  19 in total

1.  Evaluating intramural virtual electrodes in the myocardial wedge preparation: simulations of experimental conditions.

Authors:  G Plank; A Prassl; E Hofer; N A Trayanova
Journal:  Biophys J       Date:  2007-11-09       Impact factor: 4.033

2.  Shock-induced termination of reentrant cardiac arrhythmias: comparing monophasic and biphasic shock protocols.

Authors:  Jean Bragard; Ana Simic; Jorge Elorza; Roman O Grigoriev; Elizabeth M Cherry; Robert F Gilmour; Niels F Otani; Flavio H Fenton
Journal:  Chaos       Date:  2013-12       Impact factor: 3.642

3.  Note on a possible proarrhythmic property of antiarrhythmic drugs aimed at improving gap-junction coupling.

Authors:  Aslak Tveito; Glenn Terje Lines; Mary M Maleckar
Journal:  Biophys J       Date:  2012-01-18       Impact factor: 4.033

4.  Muscle Thickness and Curvature Influence Atrial Conduction Velocities.

Authors:  Simone Rossi; Stephen Gaeta; Boyce E Griffith; Craig S Henriquez
Journal:  Front Physiol       Date:  2018-10-29       Impact factor: 4.566

5.  Optimal control approach to termination of re-entry waves in cardiac electrophysiology.

Authors:  Chamakuri Nagaiah; Karl Kunisch; Gernot Plank
Journal:  J Math Biol       Date:  2012-06-09       Impact factor: 2.259

6.  Automatically generated, anatomically accurate meshes for cardiac electrophysiology problems.

Authors:  Anton J Prassl; Ferdinand Kickinger; Helmut Ahammer; Vicente Grau; Jürgen E Schneider; Ernst Hofer; Edward J Vigmond; Natalia A Trayanova; Gernot Plank
Journal:  IEEE Trans Biomed Eng       Date:  2009-02-06       Impact factor: 4.538

7.  Low energy defibrillation in human cardiac tissue: a simulation study.

Authors:  Stuart W Morgan; Gernot Plank; Irina V Biktasheva; Vadim N Biktashev
Journal:  Biophys J       Date:  2009-02-18       Impact factor: 4.033

Review 8.  From mitochondrial ion channels to arrhythmias in the heart: computational techniques to bridge the spatio-temporal scales.

Authors:  Gernot Plank; Lufang Zhou; Joseph L Greenstein; Sonia Cortassa; Raimond L Winslow; Brian O'Rourke; Natalia A Trayanova
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2008-09-28       Impact factor: 4.226

Review 9.  Solvers for the cardiac bidomain equations.

Authors:  E J Vigmond; R Weber dos Santos; A J Prassl; M Deo; G Plank
Journal:  Prog Biophys Mol Biol       Date:  2007-08-11       Impact factor: 3.667

10.  Generation of histo-anatomically representative models of the individual heart: tools and application.

Authors:  Gernot Plank; Rebecca A B Burton; Patrick Hales; Martin Bishop; Tahir Mansoori; Miguel O Bernabeu; Alan Garny; Anton J Prassl; Christian Bollensdorff; Fleur Mason; Fahd Mahmood; Blanca Rodriguez; Vicente Grau; Jürgen E Schneider; David Gavaghan; Peter Kohl
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2009-06-13       Impact factor: 4.226

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