Abstract
Mechanical properties and morphological features of the vertebral cancellous bone are related to resistance to fracture and capability of withstanding surgical treatments. In particular, vertebral strength is related to its elastic properties, whereas the ease of fluid motion, related to the success of incorporation orthopedic materials (eg, bone cement), is regulated by the hydraulic permeability (K). It has been shown that both elastic modulus and permeability of a material are affected by its morphology. The objective of this study was to establish relations between local values of K and the aggregate modulus (H), and parameters descriptive of the bone morphology. We hypothesized that multivariate statistical models, by including the contribution of several morphology parameters at once, would provide a strong correlation with K and H of the vertebral cancellous bone. Hence, μCT scans of human lumbar vertebra were used to determine a set of bone morphology descriptors. Subsequently, indentation tests on the bone samples were conducted to determine local values of K and H. Finally, a multivariate approach supported by principal component analysis was adopted to develop predictive statistical models of bone permeability and aggregate modulus as a function of bone morphology descriptors. It was found that linear combinations of bone volume fraction, trabecular thickness, trabecular spacing, structure model index, connectivity density, and degree of anisotropy provide a strong correlation (R (2) ~ 76%) with K and a weaker correlation (R (2) ~ 47%) with H. The results of this study can be exploited in computational mechanics frameworks for investigating the potential mechanical behavior of human vertebra and to develop strategies to treat or prevent pathological conditions such as osteoporosis, age-related bone loss, and vertebral compression fractures. © 2020 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.