Functional Grading of a Transversely Isotropic Hyperelastic Model with Applications in Modeling Tricuspid and Mitral Valve Transition Regions

Abstract

Surgical simulators and injury-prediction human models require a combination of representative tissue geometry and accurate tissue material properties to predict realistic tool–tissue interaction forces and injury mechanisms, respectively. While biological tissues have been individually characterized, the transition regions between tissues have received limited research attention, potentially resulting in inaccuracies within simulations. In this work, an approach to characterize the transition regions in transversely isotropic (TI) soft tissues using functionally graded material (FGM) modeling is presented. The effect of nonlinearities and multi-regime nature of the TI model on the functional grading process is discussed. The proposed approach has been implemented to characterize the transition regions in the leaflet (LL), chordae tendinae (CT) and the papillary muscle (PM) of porcine tricuspid valve (TV) and mitral valve (MV). The FGM model is informed using high resolution morphological measurements of the collagen fiber orientation and tissue composition in the transition regions, and deformation characteristics predicted by the FGM model are numerically validated to experimental data using X-ray diffraction imaging. The results indicate feasibility of using the FGM approach in modeling soft-tissue transitions and has implications in improving physical representation of tissue deformation throughout the body using a scalable version of the proposed approach.

Document Details

Document Type
Pub Defense Publication
Publication Date
Sep 05, 2020
Source ID
10.3390/ijms21186503

Entities

People

  • Caleb Yow
  • Eric Warren Jr.
  • Joseph Orgel
  • Kevin Lister
  • Rajarshi Roy
  • Rama S Madhurapantula
  • Yaoyao Xu

Organizations

  • United States Army Medical Research and Development Command

Tags

Readers

  • Computational Modeling and Simulation
  • Medical Imaging.
  • Reinforced Composite Materials