TY - CHAP M1 - Book, Section TI - Chapter 14. Computational Cardiac Electrophysiology: Modeling Tissue and Organ A1 - Bishop, Martin J. A1 - Arevalo, Hermenegild J. A1 - Boyle, Patrick M. A1 - Trayanova, Natalia A. A1 - Vigmond, Edward A1 - Plank, Gernot A2 - Pahlm, Olle A2 - Wagner, Galen S. Y1 - 2011 N1 - T2 - Multimodal Cardiovascular Imaging: Principles and Clinical Applications AB - The heart is characterized by a complex electromechanical activity essential for the sustenance of body function. Cardiac disease is the leading cause of morbidity and mortality in the industrialized world,1 imposing a major burden on health care systems. Current therapies rely, to a large extent, on implantable devices, administration of drugs, or the ablation of tissue. Although these therapies may improve a patient's condition significantly, they are palliative rather than curative, and undesired adverse effects of varying degrees of severity are quite common.2-5 In the quest of devising novel, safer, and more effective therapies to reduce medical costs and treatment duration, developing a comprehensive understanding of cardiac structure and function in health and disease is the strategy most likely to succeed and, thus, is a central focus of basic and clinical heart research. Traditionally, experimental work in conjunction with clinical studies was the dominant, if not exclusive, approach for inquiries into physiological function. Today, in the postgenomic era, a wider portfolio of techniques is employed, with computational modeling being another accepted approach, either as a complement to experimental work or as a stand-alone tool for exploratory testing of hypotheses. The need for computational modeling is mainly driven by the difficulty in dealing with the vast amount of available data, obtained from various subsystems of the heart, at different hierarchical levels of organization from different species, and with the complexity involved in the dynamics of interactions between subsystems within and across levels of organization. Computational modeling plays a pivotal, if not indispensable, role in harnessing these data for further advancing our mechanistic understanding of cardiac function. SN - PB - The McGraw-Hill Companies CY - New York, NY Y2 - 2024/03/28 UR - accessmedicine.mhmedical.com/content.aspx?aid=8762969 ER -