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Heart failure is a major cause of morbidity and mortality, contributing significantly to global health expenditure. Heart failure patients often exhibit contractile dyssynchrony, which diminishes cardiac systolic function. Cardiac resynchronization therapy (CRT), a relatively new treatment modality that employs biventricular (bi-V) pacing to recoordinate the contraction of the heart, is a valuable therapeutic option for such patients. CRT has been shown to improve heart failure symptoms and reduce hospitalization, yet approximately 30% of patients fail to respond to the therapy. In the current environment, which emphasizes reducing health care costs and optimizing therapy, robust diagnostic approaches to identify patients who would and would not benefit from CRT would have a dramatic personal, medical, and economic impact on the lives of many Americans.

The poor predictive ability of current approaches to identify potential responders to CRT reflects the incomplete understanding of the complex pathophysiologic and electromechanical factors that underlie mechanical dyssynchrony. The goal of this chapter is to present the development, from magnetic resonance imaging (MRI) and diffusion tensor (DT) MRI scans, of individualized three-dimensional (3D) image-based multiscale computational models of ventricular electromechanics that incorporate the deleterious structural, mechanical, and electrophysiologic remodeling associated with dyssynchronous heart failure (DHF), from the level of the protein to that of the intact heart. We then demonstrate how this powerful predictive modeling approach could be used to provide mechanistic insight into heart failure contractile dyssynchrony and to possibly determine the optimal CRT strategy.

The development of a predictive model of ventricular electromechanics in the setting of DHF overcomes the inability of current experimental techniques to simultaneously record the 3D electrical and mechanical activity of the heart with high spatiotemporal resolution and thus to provide an understanding of dyssynchrony and CRT effectiveness. The new basic-science insights into the electromechanical behavior that can be acquired with this modeling approach will hopefully lead to rational optimization of CRT delivery and to improvements in the selection criteria for potential CRT candidates.

Dyssynchronous Heart Failure

Heart failure is a major cardiovascular disease affecting 5 million people in the United States alone and is associated with high morbidity and mortality rates.1 The syndrome is characterized by impaired pump function due to the deleterious remodeling of the ventricles, from the organ down to the molecular level, which significantly alters the electrical and mechanical behavior of the heart. High-resolution MRI and DTMRI scans2 have shown that in DHF, there is a substantial remodeling of ventricular geometry and structure. At the organ level, the ventricles become dilated, and wall thickness is reduced. At the tissue level, laminar sheet angle is altered, and the transmural gradient in fiber orientation is increased. Because chamber geometry and sheet structure are major determinants of left ventricular (LV) mechanics,3,4 the mechanical deformation of the failing heart is markedly different. Furthermore, altered heart geometry and fiber and sheet orientations directly affect 3D ...

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