Atrial fibrillation is the most common form of heart arrhythmia and is associated with a 5-6 fold increase in the incidence of stroke. Computer models describing the temporal evolution of the action potential over realistic atrial geometries are very useful to understand or predict the effect of drugs acting as inhibitors on single or multiple ion-channels. In particular, these models make it possible to relate the dynamics of the action potential propagation to drug effects on the single cell level. This in turn permits in silico reconstruction and investigation of phenomena like atrial flutter and fibrillation.
In this work we have developed a framework for modeling and simulation of electro-chemical activity in large scale cell networks. The framework allows incorporation of different geometrical models and cell models in a plug-in fashion, as well as methods for definition of myocyte fiber orientation and distribution of myocyte subtype. On the single cell level the myocytes are described by a set of coupled non-linear ordinary differential equations. On the tissue level the cells are connected according to monodomain assumptions, forming a network represented by a connectivity matrix defined by the geometrical model. This constitutes the basis for the full atrial tissue model. In order to ensure good scalability with respect to model complexity, i.e., the total number of differential equations to be solved, the framework has been implemented in a multi-processor environment.
Within the simulation framework, a geometric model of the canine atria has been constructed utilizing ultra sound imaging data. A realistic fiber structure and cell type distribution has also been incorporated in the model, based on extensive literature studies and consultation with clinical experts.
The simulation framework has been used to induce fibrillation and flutter like electro-dynamic activity in cell networks and the effect of ion-channel modulation on this behavior has subsequently been investigated. Qualitatively the results are in good accordance with in vivo observations, which indicates that the approach is viable for this application and motivates further extensions and studies. The type of simulations presented in this work has great potential to provide insights into the underlying mechanisms of atrial fibrillation and flutter, as well as a basis for prediction of drug effects.
Authors and Affiliations
- Mikael Wallman, Fraunhofer-Chalmers Centre
- Mats Jirstrand, Fraunhofer-Chalmers Centre
- Liming Gan, AstraZeneca R&D, Mölndal
- Ingemar Jacobson, AstraZeneca R&D, Mölndal