Annals of Biomedical Engineering

, Volume 38, Issue 10, pp 3102–3111 | Cite as

Modeling Radial Viscoelastic Behavior of Left Ventricle Based on MRI Tissue Phase Mapping

  • Jan O. Mangual
  • Bernd Jung
  • James A. Ritter
  • Arash Kheradvar


The viscoelastic behavior of myocardial tissue is a measure that has recently found to be a deterministic factor in quality of contraction. Parameters imposing the viscoelastic behavior of the heart are influenced in part by sarcomere function and myocardial composition. Despite the overall agreement on significance of cardiac viscoelasticity, a practical model that can measure and characterize the viscoelastic behavior of the myocardial segments does not yet exist. Pressure–Volume (PV) curves are currently the only measure for stiffness/compliance of the left ventricle. However, obtaining PV curves requires invasive cardiac catheterization, and only provides qualitative information on how pressure and volume change with respect to each other. For accurate assessment of myocardial mechanical behavior, it is required to obtain quantitative measures for viscoelasticity. In this work, we have devised a model that yields myocardial elastic and viscous damping coefficient functions through the cardiac cycle. The required inputs for this model are kinematic information with respect to changes in LV short axes that were obtained by Magnetic Resonance Imaging (MRI) using a tissue phase mapping (TPM) pulse sequence. We evaluated viscoelastic coefficients of LV myocardium in two different age groups of 20–40 and greater than 60. We found that the magnitude of stiffness coefficients is noticeably greater in the older subjects. Additionally, we found that slope of viscous damping functions follow similar patterns for each individual age group. This method may shed light on dynamics of contraction through MRI in conditions where composition of myocardium is changed such as in aging, adverse remodeling, and cardiomyopathies.


Left ventricle Diastole Systole Cardiac viscoelasticity Contractility Tissue Phase Mapping MRI Image-based modeling 



This work was supported by a startup fund from the University of South Carolina Research Foundation, and an NSF/SC EPSCoR Grant (No. EPS-0447660) to Arash Kheradvar. Stipend and tuition support from the Sloan Foundation and travel support provided by SEAGEP to Jan O. Mangual for his travel to the BMES Fall 2009 Meeting were greatly appreciated. Authors would also like to acknowledge Ahmad Falahaptisheh for his invaluable assistance throughout the project.


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Copyright information

© Biomedical Engineering Society 2010

Authors and Affiliations

  • Jan O. Mangual
    • 1
  • Bernd Jung
    • 2
  • James A. Ritter
    • 1
  • Arash Kheradvar
    • 3
  1. 1.Department of Chemical EngineeringUniversity of South CarolinaColumbiaUSA
  2. 2.Department of Radiology, Medical PhysicsUniversity HospitalFreiburgGermany
  3. 3.Department of Mechanical EngineeringUniversity of South CarolinaColumbiaUSA

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