Three-dimensional micro-CT imaging of human cortical bone porosity: A novel method for estimating age at death

Age-related change in human bone is of great interest to numerous areas of research within the disciplines of anthropology and biomedicine. The biomedical sciences seek an understanding of normal patterns of aging to help identify and mitigate pathological conditions. Biological anthropologists use changes in the skeleton as the basis for estimating age at death and interpreting the effects of biocultural factors. To date, analysis of the microscopic remodeling of cortical bone has primarily been limited to the two-dimensional realm. Therefore, the overarching goal of this dissertation is to contribute to a greater understanding of the three-dimensional microstructure of this tissue. Specifically, the utility of 3D analysis for age at death estimation is examined. High resolution micro-computed tomography (micro-CT) is employed as a novel method for the visualization and quantification of cortical microstructure in 3D. This method is limited to biphasic (solid and porous) analysis of bone and therefore a porosity-based theoretical model for predicting 3D microstructural change is developed and tested. In essence, this model predicts the cortical canal network increases in complexity with age through the superimposition of new Haversian canals via remodeling. Due to the novel nature of the application of micro-CT to cortical bone, the method is validated against microradiography. Following this, the impact of scan resolution on quantitative analysis is explored in order to aid in the optimization of scan protocols. Hypotheses predicting age-dependent change, derived from the theoretical model, are tested using a sample of human midshaft femoral specimens collected at autopsy. Sex, height, and weight are included as potential confounding factors. The patterns observed are consistent with the proposed model, although changes in canal dimensions complicate the trajectory of structural change. Age is the most important factor related to microstructure, although sex is also a significant source of variation. Age prediction, based upon multiple regression, is possible, although limited due to relatively large standard errors. The micro-CT method is also highly effective for visualizing and measuring resorption spaces associated with cortical turnover, thereby providing novel insight into the process of remodeling itself.