Computational Tools for Cardiac Mechanics (COMPCARDMECH)
Computational Tools for Cardiac Mechanics
Start date: Sep 1, 2012,
End date: Aug 31, 2015
Cardiovascular disease is the leading cause of death and disability in Europe and in the World. Heart failure itself, primarily caused by myocardial infarction, has now reached epidemic proportions. If past clinical therapies have been developed by trial-and-error, new therapies must now be designed through the scientific understanding of the functional and structural changes in diseased hearts. The ultimate aspiration of our research project is to use theoretical modeling, in combination with new imaging modalities and modern simulation tools, to provide greater insight into cardiac disease and thereby guide the design of new successful treatment strategies.To achieve our goal, we propose to develop cutting-edge computational tools, including 22 state-of-the-art patient-specific computational models of healthy and diseased human bi-ventricular units, as well as a theoretical and computational framework to predict the remodeling of heart tissues induced by myocardial infarction. Their design and validation will be supported by world class imaging facilities. Here are typical benefits of our research to cardiac medicine. First, our tools will allow us to quantitatively characterize the morphology and mechanics of infarcted areas, as well as predict their evolution in time, thus providing to cardiologists a significant new methodology for the diagnosis of heart patients. Moreover, they will allow us to predict the reinforcement of heart tissues induced by the implantation of biomaterial in and around infarcted areas, thus providing to cardiologists a clear statement to design new therapies.Relying on unique synergies with leading experts in theoretical and numerical mechanics, as well as life science and medicine, this project will advance knowledge in computational cardiac mechanics, and may establish an entirely new way of thinking in cardiovascular medicine, inspired by predictive, patient-specific, simulation-based interventional planning.
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