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      Distribution of normal human left ventricular myofiber stress at end diastole and end systole: a target for in silico design of heart failure treatments.

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          Abstract

          Ventricular wall stress is believed to be responsible for many physical mechanisms taking place in the human heart, including ventricular remodeling, which is frequently associated with heart failure. Therefore, normalization of ventricular wall stress is the cornerstone of many existing and new treatments for heart failure. In this paper, we sought to construct reference maps of normal ventricular wall stress in humans that could be used as a target for in silico optimization studies of existing and potential new treatments for heart failure. To do so, we constructed personalized computational models of the left ventricles of five normal human subjects using magnetic resonance images and the finite-element method. These models were calibrated using left ventricular volume data extracted from magnetic resonance imaging (MRI) and validated through comparison with strain measurements from tagged MRI (950 ± 170 strain comparisons/subject). The calibrated passive material parameter values were C0 = 0.115 ± 0.008 kPa and B0 = 14.4 ± 3.18; the active material parameter value was Tmax = 143 ± 11.1 kPa. These values could serve as a reference for future construction of normal human left ventricular computational models. The differences between the predicted and the measured circumferential and longitudinal strains in each subject were 3.4 ± 6.3 and 0.5 ± 5.9%, respectively. The predicted end-diastolic and end-systolic myofiber stress fields for the five subjects were 2.21 ± 0.58 and 16.54 ± 4.73 kPa, respectively. Thus these stresses could serve as targets for in silico design of heart failure treatments.

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          Author and article information

          Journal
          J. Appl. Physiol.
          Journal of applied physiology (Bethesda, Md. : 1985)
          1522-1601
          0161-7567
          Jul 15 2014
          : 117
          : 2
          Affiliations
          [1 ] Surgery Department, University of California at San Francisco, San Francisco, California; Marie-Curie International Outgoing Fellow, Brussels, Belgium;
          [2 ] Surgery Department, University of California at San Francisco, San Francisco, California;
          [3 ] Radiology and Biomedical Imaging Department, School of Medicine, University of California at San Francisco, San Francisco, California;
          [4 ] Veterans Affairs Medical Center, San Francisco, California; and.
          [5 ] Institute for Biomedical Engineering, University and ETH, Zürich, Switzerland.
          [6 ] Surgery Department, University of California at San Francisco, San Francisco, California; julius.guccione@ucsfmedctr.org.
          Article
          japplphysiol.00255.2014
          10.1152/japplphysiol.00255.2014
          4101610
          24876359
          a450a629-651a-4741-908a-1d1cce0352cf
          Copyright © 2014 the American Physiological Society.
          History

          computational modeling,normal human subjects,patient-specific modeling,tagged MRI

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