abstract

The contraction of the heart is triggered by an electrical impulse that propagates from one muscle cell to another. This organized activity generates a potential field that can be measured as an electrocardiogram (ECG) on the skin, or with a catheter inside the heart. The measured signals provide a wealth of diagnostic information. This information has traditionally been decoded by clinicians in a strictly empirical way. As more and more becomes known about the membrane-level processes that generate the underlying ionic currents, it becomes more common to hypothesise links between malfunctions on the cellular level and ECG abnormalities. Due to the startling complexity of the basic processes and the heart's anatomy, the use of large-scale computer models can be inevitable. In this presentation I will outline how modern heart models are constructed, and show with examples that they have become a crucial part of translational research in cardiology. Technically, these models are closely related to neurological models such as the Blue Brain. However, the simpler structure of the heart as compared to the brain makes it possible already to model the entire organ, while whole-brain models are still a distant perspective. The challenge in heart modeling is therefore not to scale things up, but to increase resolution, allowing us to model diseases that cause heterogeneity in the heart muscle on a very small scale. Computationally though, it means the same thing: with larger computers, we can do more.

funding

Computational resources for this work were provided by the Réseau québécois de calcul de haute performance (RQCHP). The author gratefully acknowledges financial support from the Research Center of Sacré-Coeur Hospital, Montréal, Québec, Canada; and The Netherlands Heart Foundation (NHS) grant 2005B092.