Understanding Heart Tissue through Waves

D. Nordsletten

Biomedical Engineering Department, King’s College, London

Thursday 15th February 2018

14:00:00

Aula Consiglio VII Piano - Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO

Personalised models of cardiac mechanics have evolved into a powerful tool for studying the human heart in health and disease. Combining detailed information on the heart kinematics extracted from medical images, with mathematical models of cardiac function, patient-specific models provide a mathematical representation of individual hearts. As model parameters are linked to intrinsic tissue properties such as stiffness and contractility, unique and accurate parameter estimates are a prerequisite for the potential translation of personalised models to the clinic. In parallel, magnetic resonance elastography (MRE) has evolved into a powerful tool for interrogating material stiffness. MRE has been exploited in the liver, breast, and brain using measured periodic waves to extract material stiffness properties. Transducing waves via external vibrations, MRE provides a more direct measure of the characteristics of tissues and their potential diseases. Integrating this work into the heart is complicated by a myriad of challenges including the inherent cardiac motion of the heart, evolving material properties due to the contractile state of the muscle, and the nonlinear effects of deformation on the apparent stiffness of the material. In this talk, we discuss the merger of these two worlds, bridging between the nearly quasi-static model-based assessment of heart function and the high frequency wave-based assessment. In particular, we discuss the simple influence of deformation on apparent stiffness, explaining both from the realm of traditional wave mechanics and biomechanical theory. Contact: christian.vergara@polimi.it This seminar is organized within the Research project «An Integrated Heart Model for the simulation of the cardiac function - iHEART» Grant Agreement number 740132, funded by ERC (2016-ADG). Principal investigator: Prof. Alfio Maria Quarteroni

David Nordsletten is a Senior Lecturer at King's College London in the Division of Biomedical Engineering and Imaging Sciences. He graduated with a DPhil in Computer Science and Biomedical Engineering from the University of Oxford.