Biomechanics and Modeling in Mechanobiology

, Volume 10, Issue 3, pp 295–306

Models of cardiac electromechanics based on individual hearts imaging data

Image-based electromechanical models of the heart
  • Viatcheslav Gurev
  • Ted Lee
  • Jason Constantino
  • Hermenegild Arevalo
  • Natalia A. Trayanova
Original Paper

DOI: 10.1007/s10237-010-0235-5

Cite this article as:
Gurev, V., Lee, T., Constantino, J. et al. Biomech Model Mechanobiol (2011) 10: 295. doi:10.1007/s10237-010-0235-5

Abstract

Current multi-scale computational models of ventricular electromechanics describe the full process of cardiac contraction on both the micro- and macro- scales including: the depolarization of cardiac cells, the release of calcium from intracellular stores, tension generation by cardiac myofilaments, and mechanical contraction of the whole heart. Such models are used to reveal basic mechanisms of cardiac contraction as well as the mechanisms of cardiac dysfunction in disease conditions. In this paper, we present a methodology to construct finite element electromechanical models of ventricular contraction with anatomically accurate ventricular geometry based on magnetic resonance and diffusion tensor magnetic resonance imaging of the heart. The electromechanical model couples detailed representations of the cardiac cell membrane, cardiac myofilament dynamics, electrical impulse propagation, ventricular contraction, and circulation to simulate the electrical and mechanical activity of the ventricles. The utility of the model is demonstrated in an example simulation of contraction during sinus rhythm using a model of the normal canine ventricles.

Keywords

Ventricular contractionComputational modelingImage-based modelsCardiac pump

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Viatcheslav Gurev
    • 1
  • Ted Lee
    • 1
  • Jason Constantino
    • 1
  • Hermenegild Arevalo
    • 1
  • Natalia A. Trayanova
    • 1
  1. 1.Institute for Computational Medicine, Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreUSA