Virtual human heart modeling and its (clinical) applications.


Mathias Peirlinck, Ellen Kuhl

Stanford Medicine - 3rd Annual Cardiovascular Postdoctoral Research Conference

From an engineering perspective, understanding the heart involves solving a multi-scale, multi-physics problem. Over the last decade, solving these problems with high-fidelity computational models has provided a more and more patient-specific window on acute and chronic heart functioning. In this talk, we will present tfull 4-chamber computational heart models created from computer tomography and magnetic resonance images. We will showcase how these models allow us to explore and understand the human heart, both in a healthy state and in multiple pathological disease conditions (e.g. conduction disorders, hypertension, heart failure). Moreover, we will demonstrate how these models have provided, and will continue to provide, a realistic virtual testing environment to conceptualize, develop and/or improve medical devices and/or novel treatment strategies in terms of efficacy and durability. As such, these models are paving the way forwards towards in silico augmented clinical trials (most recently in collaboration with the FDA towards the development of novel mitral valve devices).