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International Journal for Multiscale Computational Engineering
IF: 1.016 5-Year IF: 1.194 SJR: 0.554 SNIP: 0.68 CiteScore™: 1.18

ISSN Print: 1543-1649
ISSN Online: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.2011002352
pages 171-188


Markus Boel
Department of Mechanical Engineering, TU Braunschweig, Germany
Oscar J. Abilez
Department of Surgery, Stanford University, Stanford, CA 94305
Ahmed N Assar
Department of Surgery, Stanford University, Stanford, CA 94305
Christopher K. Zarins
Department of Surgery, Stanford University, Stanford, CA 94305
Ellen Kuhl
Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic, Surgery, Stanford University, USA


We propose a novel, robust, and easily reproducible, in vitro/in silico model system to characterize active and passive stresses in electroactive cardiac muscle using a hybrid experimental/computational approach. We explore active and passive stresses in healthy explanted heart slices in vitro, design a virtual test bed to simulate the in vitro measured stresses in silico, and predict altered active force generation in infarcted hearts in silico. For the in vitro model, explanted rat heart tissue slices are mounted on a force transducer and stimulated electrically through biphasic pulses. Isometric forces are recorded and translated into active circumferential stress. For the in silico model, stresses are additively decomposed into passive and active contributions, with the latter being related to the measured isometric force. A hierarchical finite element model for cardiac muscle tissue is developed based on passive tetrahedral unit cells, representing a network of interconnected polymeric chains, and active trusses, representing the contracting muscle fibers. First, we calibrate the model against our experiments with healthy explanted rat heart slices. Then, we predict acute and chronic alterations in active stress generation in infarcted hearts. We virtually explore isometric forces generation for different infarct area fractions and infarct locations. This approach has the potential to precisely quantify global loss of cardiac function for a given infarct area fraction.


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