Data Driven Modeling of Cardiac Dynamics and Model Evaluation
The development of detailed physiological models of the heart, the availability of large quantities of high-quality structural and functional experimental data, and ever-increasing computational power have significantly enhanced the understanding of cardiac dynamics and hold the promise of new clinical applications for diagnosis and treatment of heart disease. However, the systematic integration of experimental data into high-dimensional, multi-scale models and their subsequent evaluation, validation and analysis remains a major challenge. Therefore, we are developing a data driven, integrative strategy that combines high-resolution imaging techniques with state of the art numerical modeling through innovative state estimation methods. Within this approach, model evaluation plays an important role for the validation and the selection of model complexity on all relevant scales from subcellular, cell, tissue to organ and organism level. The models will be used to study genetic and environmental factors contributing to initiation, perpetuation and termination of cardiac arrhythmias. In the following, we will briefly describe the experimental techniques used to characterize detailed anatomical structure and high-resolution spatial-temporal dynamics of the heart, the available mathematical models, and provide examples of state and parameter estimation.