As a structural material, bone tissue has the unique ability to adapt to its constantly changing mechanical demands. Although considerable effort has been directed toward revealing the nature of bone's mechanical adaptation, the phenomenon has not yet been quantitatively characterized. One reason is our inadequate understanding of bone's in vivo mechanical environment. The objective of this work was to investigate the mechanical strain response of a long bone to dynamic physiological loading.

The first goal of our investigation was to characterize the ume-varying in vivo strain field in a long bone during normal physical acuvity. Using strain gages, we measured in vivo strains at several locadons on a long bone during gait. We then performed a 3-D interpolauon on this sparse set of experimental data to calculate the dynamic strain field for the entire bone. This combined experimental and computadonal approach enabled us to quantify local magnitudes of strain throughout the experimental bone during typical dynamic loading.

Our second goal was to develop a computadonal model of the experimental bone that would accurately simulate its mechanical behavior during dynamic loading. A 3-D finite element model of the instrumented bone was constructed from computed tomography (CT) image data. Tune-dependent loading conditions were then reconstructed from the previously recorded strain gage data using numerical methods. The resuldng finite element model produced 3-D strain patterns which were consistent with the in vivo strain field.

A final goal of this work was to quantify the effect of an altered load environment on bone’s strain history. Using our dynamic finite element model, we determined the timedependent, 3-D strain field for "normal" loading and calculated several strain history measures that may be possible regulators of bone adaptation. The model was then altered to simulate "pathological" loading and the strain history measures were recalculated. Local changes in the strain history parameters may represent possible stimuli for bone adaptation.

Using these methods, we can now quantify a number of strain history measures for a variety of physiological loading activities. Such information may provide new insights regarding the spatial distribution of strain history measures to sites of bone adaptation.