GUI for CARDIOWAVE

For macroscopic models of the heart to have greater predictive ability they must be able to incorporate the effects of diseased-induced tissue structure inhomogeneities on conduction and potential timecourses. The objectives of this research are to develop improved discretization schemes for robustly modeling conduction in regions with spatially varying material and membrane properties. These objectives are being accomplished by creating the simulation system, CARDIOWAVE, which uses a module-based paradigm to produce a problem-specific code. This approach allows any advances made in any one component to lead directly to an advancement of the whole program. CARDIOWAVE is being used to evaluate the use of structured and unstructured finite volume methods, that involve quadrilateral and triangular grids, to discretize the computational domains of interest. The speed, accuracy and stability of both types of methods are being examined using explicit and implicit time stepping algorithms. To ensure that the spatial discretization methods are able to accommodate any advances in the dynamical models of the ion fluxes across the membrane,  state-of-the-art kinetic models are being evaluated over a range of physiological conditions. Finally, strategies for using spatially adaptive gridding in regions with abrupt changes in tissue properties, such as those expected in diseased myocardium, are being developed. This proposal represents a research and educational collaboration between Biomedical Engineering and Computer Science at Duke University and is providing a set of tools and methods that is expected also to benefit mathematicians and physicists interested in studying the dynamics of general excitable media. David Harrild, John Pormann, Kevin Sampson, Joe Tranquillo, Chris Penland

Funding for this work comes in part from the National Science Foundation