Fibrillatory conduction in branching atrial tissue - Insight from volumetric and monolayer computer models

Increased local load in branching atrial tissue (muscle fibers and bundle insertions) influences wave propagation during atrial fibrillation (AF). This computer model study reveals two principal phenomena: if the branching is distant from the driving rotor (>19 mm), the load causes local slowing of conduction or wavebreaks. If the driving rotor is close to the branching, the increased load causes first a slow drift of the rotor towards the branching. Finally, the rotor anchors, and a stable, repeatable pattern of activation can be observed. Variation of the bundle geometry from a cylindrical, volumetric structure to a flat strip of a comparable load in a monolayer model changed the local activation sequence in the proximity of the bundle. However, the global behavior and the basic effects are similar in all models. Wavebreaks in branching tissue contribute to the chaotic nature of AF (fibrillatory conduction). The stabilization (anchoring) of driving rotors by branching tissue might contribute to maintain sustained AF.

[1]  Alan Garfinkel,et al.  Electrical refractory period restitution and spiral wave reentry in simulated cardiac tissue. , 2002, American journal of physiology. Heart and circulatory physiology.

[2]  A Garfinkel,et al.  Role of pectinate muscle bundles in the generation and maintenance of intra-atrial reentry: potential implications for the mechanism of conversion between atrial fibrillation and atrial flutter. , 1998, Circulation research.

[3]  C. Henriquez,et al.  Study of atrial arrhythmias in a computer model based on magnetic resonance images of human atria. , 2002, Chaos.

[4]  Robert H. Anderson,et al.  Anatomy of the Left Atrium: , 1999, Journal of cardiovascular electrophysiology.

[5]  S. Nattel New ideas about atrial fibrillation 50 years on , 2002, Nature.

[6]  Mark-Anthony Bray,et al.  Use of topological charge to determine filament location and dynamics in a numerical model of scroll wave activity , 2002, IEEE Transactions on Biomedical Engineering.

[7]  Martin Dugas,et al.  Complexity of biomedical data models in cardiology: the Intranet-based AF registry , 2002, Comput. Methods Programs Biomed..

[8]  K H W J Ten Tusscher,et al.  Reentry in heterogeneous cardiac tissue described by the Luo-Rudy ventricular action potential model. , 2003, American journal of physiology. Heart and circulatory physiology.

[9]  Steeve Zozor,et al.  A numerical scheme for modeling wavefront propagation on a monolayer of arbitrary geometry , 2003, IEEE Transactions on Biomedical Engineering.

[10]  José Jalife,et al.  Frequency-Dependent Breakdown of Wave Propagation Into Fibrillatory Conduction Across the Pectinate Muscle Network in the Isolated Sheep Right Atrium , 2002, Circulation research.

[11]  RaviMandapati,et al.  Stable Microreentrant Sources as a Mechanism of Atrial Fibrillation in the Isolated Sheep Heart , 2000 .

[12]  Hsuan-Ming Tsao,et al.  Frequency analysis in different types of paroxysmal atrial fibrillation. , 2006, Journal of the American College of Cardiology.

[13]  Mark Potse,et al.  A Comparison of Monodomain and Bidomain Reaction-Diffusion Models for Action Potential Propagation in the Human Heart , 2006, IEEE Transactions on Biomedical Engineering.

[14]  J. Rogers Wave front fragmentation due to ventricular geometry in a model of the rabbit heart. , 2002, Chaos.

[15]  N Trayanova,et al.  Reentry in a Morphologically Realistic Atrial Model , 2001, Journal of cardiovascular electrophysiology.

[16]  C. Henriquez,et al.  A computer model of normal conduction in the human atria. , 2000, Circulation research.

[17]  José Jalife,et al.  Anchoring of vortex filaments in 3D excitable media , 1994 .

[18]  Y Rudy,et al.  Mechanistic Insights Into Very Slow Conduction in Branching Cardiac Tissue: A Model Study , 2001, Circulation research.

[19]  A. Garfinkel,et al.  An advanced algorithm for solving partial differential equation in cardiac conduction , 1999, IEEE Transactions on Biomedical Engineering.

[20]  Natalia A. Trayanova,et al.  Computational techniques for solving the bidomain equations in three dimensions , 2002, IEEE Transactions on Biomedical Engineering.

[21]  Vincent Jacquemet,et al.  Finite volume stiffness matrix for solving anisotropic cardiac propagation in 2-D and 3-D unstructured meshes , 2005, IEEE Transactions on Biomedical Engineering.

[22]  R. Gray,et al.  Incomplete reentry and epicardial breakthrough patterns during atrial fibrillation in the sheep heart. , 1996, Circulation.

[23]  J Jalife,et al.  Dynamics of wavelets and their role in atrial fibrillation in the isolated sheep heart. , 2000, Cardiovascular research.

[24]  A. Skanes,et al.  Spatiotemporal periodicity during atrial fibrillation in the isolated sheep heart. , 1998, Circulation.

[25]  B Tilg,et al.  A finite element formulation for atrial tissue monolayer. , 2008, Methods of information in medicine.

[26]  Robert Modre,et al.  Lead field computation for the electrocardiographic inverse problem - finite elements versus boundary elements , 2005, Comput. Methods Programs Biomed..

[27]  L. J. Leon,et al.  Cholinergic Atrial Fibrillation in a Computer Model of a Two-Dimensional Sheet of Canine Atrial Cells With Realistic Ionic Properties , 2002, Circulation research.

[28]  K. Murray,et al.  Rapid stimulation causes electrical remodeling in cultured atrial myocytes. , 2005, Journal of molecular and cellular cardiology.

[29]  M. Mansour,et al.  Mother rotors and fibrillatory conduction: a mechanism of atrial fibrillation. , 2002, Cardiovascular research.

[30]  S Nattel,et al.  Mathematical analysis of canine atrial action potentials: rate, regional factors, and electrical remodeling. , 2000, American journal of physiology. Heart and circulatory physiology.