Cardiovascular disease is the major cause of mortality and morbidity in the Western Hemisphere. While significant progress has been made in treating a major sub-category of cardiac disease, arrhythmias, significant unmet needs remain. In particular, every day, thousands of patients die because of arrhythmias in the US alone, and atrial fibrillation is the most common arrhythmia affecting millions of patients in the US alone at a given time. Therefore, there is a public need to continue to develop new and better therapies for arrhythmias. Accordingly, an ever increasing number of biomedical, pharmaceutical, and medical personnel is interested in studying various aspects of arrhythmias at a basic, translational, and applied level, both in industry (ie Biotech, Pharmaceutical and device), and in academia. Not only has our overall understanding of molecular bases of disease dramatically increased, but so has the number of available and emerging molecular, pharmacological or device treatment based therapies. This practical, state-of-the art handbook will summarize and review key research methods and protocols, their advantages and pitfalls, with a focus on practical implementation, and collaborative cross-functional research. The volume will include visual and easy-to-use graphics, bulleted summaries, boxed summary paragraphs, links to reference websites, equipment manufacturers where appropriate, photographs of typical experimental setups and so forth, to keep this book very focused on practical methods and implementation, and yet, provide enough theory that the principles are clearly understood and can be easily applied.

This book covers the main mathematical and numerical models in computational electrocardiology, ranging from microscopic membrane models of cardiac ionic channels to macroscopic bidomain, monodomain, eikonal models and cardiac source representations. These advanced multiscale and nonlinear models describe the cardiac bioelectrical activity from the cell level to the body surface and are employed in both the direct and inverse problems of electrocardiology. The book also covers advanced numerical techniques needed to efficiently carry out large-scale cardiac simulations, including time and space discretizations, decoupling and operator splitting techniques, parallel finite element solvers. These techniques are employed in 3D cardiac simulations illustrating the excitation mechanisms, the anisotropic effects on excitation and repolarization wavefronts, the morphology of electrograms in normal and pathological tissue and some reentry phenomena. The overall aim of the book is to present rigorously the mathematical and numerical foundations of computational electrocardiology, illustrating the current research developments in this fast-growing field lying at the intersection of mathematical physiology, bioengineering and computational biomedicine. This book is addressed to graduate student and researchers in the field of applied mathematics, scientific computing, bioengineering, electrophysiology and cardiology.

This book is devoted to computer-based modeling in cardiology, by taking an educational point of view, and by summarizing knowledge from several, commonly considered delimited areas of cardiac research in a consistent way. First, the foundations and numerical techniques from mathematics are provided, with a particular focus on the finite element and finite differences methods. Then, the theory of electric fields and continuum mechanics is introduced with respect to numerical calculations in anisotropic biological media. In addition to the presentation of digital image processing techniques, the following chapters deal with particular aspects of cardiac modeling: cardiac anatomy, cardiac electro physiology, cardiac mechanics, modeling of cardiac electro mechanics. This book was written for researchers in modeling and cardiology, for clinical cardiologists, and for advanced students.

Cardiovascular diseases (CVD) including heart diseases, peripheral vascular disease and heart failure, account for one-third of deaths throughout the world. CVD risk factors include systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, and diabetic status. Clinical trials have demonstrated that when modifiable risk factors are treated and corrected, the chances of CVD occurring can be reduced. This illustrates the importance of this book's elaborate coverage of cardiovascular physiology by the application of mathematical and computational methods.This book has literally transformed Cardiovascular Physiology into a STEM discipline, involving (i) quantitative formulations of heart anatomy and physiology, (ii) technologies for imaging the heart and blood vessels, (iii) coronary stenosis hemodynamics measure by means of fractional flow reserve and intervention by grafting and stenting, (iv) fluid mechanics and computational analysis of blood flow in the heart, aorta and coronary arteries, and (v) design of heart valves, percutaneous valve stents, and ventricular assist devices.So how is this mathematically and computationally configured landscape going to impact cardiology and even cardiac surgery? We are now entering a new era of mathematical formulations of anatomy and physiology, leading to technological formulations of medical and surgical procedures towards more precise medicine and surgery. This will entail reformatting of (i) the medical MD curriculum and courses, so as to educate and train a new generation of physicians who are conversant with medical technologies for applying into clinical care, as well as (ii) structuring of MD-PhD (Computational Medicine and Surgery) Program, to train competent medical and surgical specialists in precision medical care and patient-specific surgical care.This book provides a gateway for this new emerging scenario of (i) science and engineering based medical educational curriculum, and (ii) technologically oriented medical and surgical procedures. As such, this book can be usefully employed as a textbook for courses in (i) cardiovascular physiology in both the schools of engineering and medicine of universities, as well as (ii) cardiovascular engineering in biomedical engineering departments worldwide.

This book provides a thorough introduction to the topic of mathematical modeling of electrical activity in the heart, from molecular details of ionic channel dynamics to clinically derived patient-specific models. It discusses how cellular ionic models are formulated, introduces commonly used models and explains why there are so many different models available. The chapters cover modeling of the intracellular calcium handling that underlies cellular contraction as well as modeling molecular-level details of cardiac ion channels, and also focus on specialized topics such as cardiomyocyte energetics and signalling pathways. It is an excellent resource for experienced and specialised researchers in the field, but also biological scientists with a limited background in mathematical modelling and computational methods. Part of Biophysical Society-IOP series.

Since the dawn of computing, the quest for a better understanding of Nature has been a driving force for technological development. Groundbreaking achievements by great scientists have paved the way from the abacus to the supercomputing power of today. When trying to replicate Nature in the computer’s silicon test tube, there is need for precise and computable process descriptions. The scienti?c ?elds of Ma- ematics and Physics provide a powerful vehicle for such descriptions in terms of Partial Differential Equations (PDEs). Formulated as such equations, physical laws can become subject to computational and analytical studies. In the computational setting, the equations can be discreti ed for ef?cient solution on a computer, leading to valuable tools for simulation of natural and man-made processes. Numerical so- tion of PDE-based mathematical models has been an important research topic over centuries, and will remain so for centuries to come. In the context of computer-based simulations, the quality of the computed results is directly connected to the model’s complexity and the number of data points used for the computations. Therefore, computational scientists tend to ?ll even the largest and most powerful computers they can get access to, either by increasing the si e of the data sets, or by introducing new model terms that make the simulations more realistic, or a combination of both. Today, many important simulation problems can not be solved by one single computer, but calls for parallel computing.

This book describes mathematical models and numerical techniques for simulating the electrical activity in the heart. It gives an introduction to the most important models, followed by a detailed description of numerical techniques. Particular focus is on efficient numerical methods for large scale simulations on both scalar and parallel computers. The results presented in the book will be of particular interest to researchers in bioengineering and computational biology.

Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications.