Evaluation of Bone Healing, Damage, and Adaptation Using Computational Modeling and Image Processing Techniques

Doctoral Dissertation


Three-dimensional imaging and image processing provide tools that ultimately improve measurements in biomechanics research. With appropriate processing techniques, images can be used directly to assess bone geometry, or converted to more detailed computational models that can be applied to analyze the local mechanical environment of bone. The objective of this dissertation was to study bone healing, damage, and adaptation through the novel application of computational modeling and image processing techniques.

The local mechanical environment is vital to study of bone biomechanics. However, it is often difficult to determine the mechanical behavior of whole bones, because individual bones have complex geometry that varies between species and individuals within a species, heterogeneous composition, and relevant features that span multiple length scales. For this reason, specimen specific finite element models coupled with complimentary experiments have become a common tool for analyzing the detailed mechanics of bone and test specimens.

In an initial study, specimen specific, longitudinal imaging was employed to evaluate the efficacy of a hydroxyapatite-reinforced collagen scaffold for the treatment of critically-sized defects in rat femurs. Image processing was used to allow each animal to effectively serve as its own control. Ten weeks following implantation, the scaffolds failed to induce healing. However, the scaffolds improved when compared to defects implanted with porous collagen, or empty defects. Image processing allowed the time course of healing to be quantified for each experimental group, and identified important trends with only a small number of animals.

In a second study, specimen specific finite element models of rat femurs were used to interpret the outcomes of a fatigue loading experiment. Femurs that had been loaded in three-point bending to induce damage were analyzed. The locations of microdamage were correlated to the strain distribution using a probabilistic model. The results demonstrated that damage was dependent on strain, but also had a random component, which can be attributed to the presence of pores and other flaws smaller than the spatial resolution of the models. A Weibull distribution function was used to predict the damage distribution.

Finally, poroelastic finite element models of porcine femurs were validated and used to characterize the mechanical environment of bone marrow in a whole bone under cyclic loading. This is essential to understanding the role that mechanical signaling within the marrow plays in bone adaptation and other diseases associated with marrow abnormalities. To improve the fidelity of these models, orthotropic material orientations were first applied in the directions of principal stress, and then validated through microscale modeling. A poroelastic constitutive model enabled the calculation of pore pressures resulting from whole bone loading, and these were validated against experimental measurements. The calculated pore pressure gradients were further applied to estimate the shear stress using a Darcy flow model. Although this is a simplified model, shear stress was estimated far in excess of the mechanostimulatory threshold, suggesting that whole bone loading is mechanostimulatory to marrow cells.

Overall, this work has developed new approaches to the application of specimen specific 3-D imaging to biomechanical analysis. These approaches can be applied to a wide range of biomechanical studies. The initial multiscale techniques that have been developed have opened up the potential for simulations that that span from whole bones to tissues, and potentially the cellular level.


Attribute NameValues
Author Joshua A. Gargac
Contributor Matthew Ravosa, Committee Member
Contributor Ryan Roeder, Committee Member
Contributor Glen Niebur, Research Director
Degree Level Doctoral Dissertation
Degree Discipline Bioengineering
Degree Name Doctor of Philosophy
Defense Date
  • 2015-06-29

Submission Date 2015-07-15
Record Visibility Public
Content License
  • All rights reserved

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