Mathematical Modelling of the Human Cardiovascular System

Alfio Quarteroni is Professor of Numerical Analysis at Politecnico di Milano. He has authored twenty-five books and over 350 papers in international scientific journals and conference proceedings. He received many awards and honours in recognition of his work, and is a member of the Italian Academy of Science, the European Academy of Science and the Academia Europaea. His research interests include mathematical modelling and its applications. Luca Dedè is Assistant Professor in Numerical Analysis at Politecnico di Milano. His research involves the development of efficient and accurate numerical methods for the approximation of partial differential equations, multiphysics and multiscale problems, and computational fluid dynamics. Andrea Manzoni is Assistant Professor in Numerical Analysis at Politecnico di Milano. His 2012 Ph.D. thesis won one of two ECCOMAS Awards for the best Ph.D. theses in Europe about Computational Methods in Applied Sciences and Engineering. His research interests include the development of reduced order modelling techniques for partial differential equations, uncertainty quantification, PDE-constrained optimization, and computational and statistical inverse problems. Christian Vergara is Associate Professor in Numerical Analysis at Politecnico di Milano. He works on the development of numerical methods for the cardiovascular system, in particular for the fluid-structure interaction problems and the electro-physiology of the ventricles. He has collaborated with hospitals and clinicians to use numerical and computational methods to address several problems of clinical interest.

• Introduction; Part I. Arterial Circulation: 1. Basic facts about quantitative physiology; 2. An insight into vascular data; 3. Modelling blood flow; Part II. Heart Function: 4. Basic facts on quantitative cardiac physiology; 5. An insight into cardiac data; 6. Modelling the heart; Part III. Optimization, Control, Uncertainty and Complexity Reduction: 7. Beyond direct simulation; 8. Control and optimization; 9. Parameter estimation from clinical data; 10. Accounting for uncertainty; 11. Reduced-order modelling; References; Index.

'Overall, there is a nice interplay between the basic biology and physiology needed to understand the model, the pros and cons of different techniques of obtaining clinical data, and the implementation of the numerical methods. Each section includes beautifully colored schematic representations of the cardiovascular system …' Sarah Patterson, Mathematical Association of America