Abstract

BackgroundMuch of the experimental work in soft tissue mechanics has been focused on fitting approximate relations for specific tissue types from aggregate data on multiple samples of the tissue. Such relations are needed for modeling applications and have reasonable predictability – especially given the natural variance in specimens. There is, however, much theoretical and experimental work to be done in determining constitutive behaviors for particular specimens and tissues. In so doing, it may be possible to exploit the natural variation in tissue ultrastructure – so to relate ultrastructure composition to tissue behavior. Thus, this study focuses on an experimental method for determining constitutive behaviors and illustrates the method with analysis of a porcine pulmonary artery strip. The method characterizes the elastic part of the response (implicitly in terms of stretch) and the inelastic part in terms of short term stretch history (i.e., stretch-rate) Ht2, longer term stretch history Ht1, and time since the start of testing T.MethodsA uniaxial testing protocol with a random stretch and random stretch-rate was developed. The average stress at a particular stretch was chosen as the hyperelastic stress response, and deviation from the mean at this particular stretch is chosen as the inelastic deviation. Multivariable Linear Regression Analysis (MLRA) was utilized to verify if Ht2, Ht1, and T are important factors for characterizing the inelastic deviation. For acquiring Ht2 and Ht1, an integral function type of stretch history was employed with time constants chosen from the relaxation spectrum of an identical size strip from the same tissue with the same orientation. Finally, statistical models that characterize the inelasticity were developed at various, nominal values of stretch, and their predictive capability was examined.ResultsInelastic deviation from hyperelasticity was high (31%) for low stretch and declined significantly with increasing stretch to a nadir of 3.6% for a stretch of 1.7. The inelastic deviation then increased with increasing stretch at the same point in the stress-strain curve where stiffness began to increase strikingly. MLRA showed that T is a major inelastic parameter at low deformation. For moderate and high deformations, Ht2 and Ht1 were dominant.DiscussionA randomized uniaxial testing protocol was applied to a strip of porcine pulmonary artery to characterize the elasticity and inelasticity of a soft tissue. We were successful in determining the elastic response and the factors that gave rise to the inelastic deviation. This investigation seeks methods to better define, phenomenologically, the elastic and inelastic behavior of soft tissues.

Highlights

  • A great challenge in biomechanics, and its related disciplines such as mechanobiology, is the determination of mechanical constitutive behaviors for tissues that undergo high strain

  • Heterogeneous tissues with behavior that is anisotropic and visco-elastic, much theoretical and experimental work remains [2], and this work is a small step toward improving experimental methods to delineate tissue behavior

  • There are, approximate constitutive relations for most tissue types that have been validated with fits to experimental data and that have enabled modeling applications in biomechanics

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Summary

Introduction

A great challenge in biomechanics, and its related disciplines such as mechanobiology, is the determination of mechanical constitutive behaviors for tissues that undergo high strain. There are, approximate constitutive relations for most tissue types that have been validated with fits to experimental data and that have enabled modeling applications in biomechanics. Each specimen has differing amounts of elastin, collagen, water, etc.; and with experimental methods that delineate rather than aggregate behavior, we seek to relate ultrastructure parameters to tissue response parameters. Much of the experimental work in soft tissue mechanics has been focused on fitting approximate relations for specific tissue types from aggregate data on multiple samples of the tissue. Such relations are needed for modeling applications and have reasonable predictability – especially given the natural variance in specimens. The method characterizes the elastic part of the response (implicitly in terms of stretch) and the inelastic part in terms of short term stretch history (i.e., stretch-rate) Ht2, longer term stretch history Ht1, and time since the start of testing T

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