Patient-Specific Modeling of the Cardiovascular System

The main purpose of the book is to demonstrate the design of a variety of patient-specific models within the cardiovascular system in computational biology. The maturation of computational biology could lead to a new approach to medicine. During the last five to ten years, there have been many improvements in diagnostic medical technologies such as multi-slice cardiac CT imaging, 3-D electroanatomic mapping, and many types of applications of Magnetic Resonance Imaging (i.e. magnetic resonance tagging and diffusion tensor imaging). Combined with more powerful computing resources and more accurate predictive computational models it is feasible to begin developing mechanistic patient-specific models that may help diagnosis, guide therapy or surgery, and predict outcomes of the latter. Many questions need to be answered before computational modeling can be fully integrated with standard care, such as what is the minimal data set needed from the patient in order to build a reliable predictive model? What accuracy is needed? How will the initial baseline model be validated? What are reasonable computation times? Is some type of perturbation of the patient's physiology necessary? How could they be integrated with current practices? Are physicians willing to accept these models? These questions will also serve as guidelines throughout the chapters. The book will try to cover, such as cardiac electrophysiology, cardiac (muscle) mechanics, circulation dynamics, arterial and venous flow, angiogenesis, remodeling, metabolism, or combinations between these such as cardiac electromechanics or fluid-solid interactions.