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Testing Two Predictions for Fracture Load Using Computer Models of Trabecular Bone

Michael A. K. Liebschner ^*, Ralph Müller , Sunil J. Wimalawansa , Chamith S. Rajapakse  and Gemunu H. Gunaratne  ^¶

^* Department of Bioengineering, Rice University, Houston, Texas; Institute for Biomedical Engineering, Swiss Federal Institute of Technology and University of Zürich, Zürich, Switzerland; Department of Medicine, Robert Wood Johnson Medical School, New Brunswick, New Jersey; Department of Physics, University of Houston, Houston, Texas; and ^¶ The Institute of Fundamental Studies, Kandy, Sri Lanka

Correspondence: Address reprint requests to Gemunu H. Gunaratne, E-mail: gemunu{at}uh.edu.

Aging induces several types of architectural changes in trabecular bone including thinning, increased levels of anisotropy, and perforation. It has been determined, on the basis of analysis of mathematical models, that reduction in fracture load caused by perforation is significantly higher than those due to equivalent levels of thinning or anisotropy. The analysis has also provided an expression which relates the fractional reduction of strength to the fraction of elements that have been removed from a network. Further, it was proposed that the ratio of the elastic constant of a sample and its linear response at resonance can be used as a surrogate for . Experimental validation of these predictions requires following architectural changes in a given sample of trabecular bone; techniques to study such changes using microcomputed tomography are only beginning to be available. In the present study, we use anatomically accurate computer models constructed from digitized images of bone samples for the purpose. Images of healthy bone are subjected to successive levels of synthetic degradation via surface erosion. Computer models constructed from these images are used to calculate their fracture load and other mechanical properties. Results from these computations are shown to be consistent with predictions derived from the analysis of mathematical models. Although the form of () is known, parameters in the expression are expected to be sample-specific, and hence is not a reliable predictor of strength. We provide an example to demonstrate this. In contrast, analysis of model networks shows that the linear part of () depends only on the structure of trabecular bone. Computations on models constructed from samples of iliac crest trabecular bone are shown to be in agreement with this assertion. Since can be computed from a vibrational assessment of bone, we argue that the latter can be used to introduce new surrogates for bone strength and hence diagnostic tools for osteoporosis.