Adaptation of bone to mechanical and nonmechanical stimuli: An integrated experimental and computational study
Description
Like many tissues in the body, bone has the ability to adapt its shape and material properties over time to meet the demands of its mechanical function. In addition, bone tissue is responsive to several nonmechanical influences including changes in serum hormone levels and treatment with various osteoactive agents. The responsiveness of bone to cues from its environment stems from the presence of a resident cell population that acts in concert to detect changes in the mechanical and systemic milieu and, if necessary, initiate local formation and resorption processes to modify bone form. The objective of this research was to study the interaction between mechanical and nonmechanical stimuli using an integrated experimental and computational approach In the experimental work we adopted the rat tibial four-point bending model as our in vivo controlled loading stimulus. This experiment has been shown to elicit endocortical bone formation at elevated load magnitudes. We augmented this loading procedure to include concurrent treatment with hPTH-(1-34), a pharmacologic agent that has also been shown to promote endcodortical bone formation. By applying these stimuli individually and simultaneously, we were able to establish an overall synergistic interaction between the two treatments types. Furthermore, by mapping the bone formation pattern about the endocortical perimeter of the tibial midshaft, we were able to observe the site-specific interaction between mechanical loading and hPTH-(1-34) treatment Computational techniques were developed to relate the measured formation to a number of mechanical signal distributions in the midshaft. A method was developed to extract mechanical signal data (and spatial gradients of a signal) from arbitrary cross sections of a finite element model. This technique facilitated comparison of the mechanical environment to the experimentally measured formation data In addition, we developed a new technique for the simulation of mechanically-driven shape change in long bone structures. This new method allows for the use of arbitrary scalar signals to drive shape adaptation. The implementation is particularly effective for simulations which produce large changes in bone morphology. This mechanical adaptation method was further extended to incorporate three possible forms of envelope-specific nonmechanical interaction into the remodeling rule