3D bone microarchitecture modeling and fracture risk prediction

Abstract

As prevalence and awareness of osteoporosis increase and treatments of proven efficacy become available, the demand for management of patients with the disease will also rise. It calls for innovative research on understanding of osteoporosis and fracture mechanisms, allowing early and more accurate prediction of bone disease progression. The most widely validated technique for the diagnosis of osteoporosis is Bone Mineral Density (BMD) measurement based on dual energy X-ray absorptiometry (DXA). However, a major limitation of BMD is that it incompletely reflects the variation in bone strength. In this paper we develop and evaluate a novel three-dimensional (3D) computational bone framework capable of providing: (1) Spatio-temporal 3D microstructure bone model; (2) Derived quantitative measures of 3D bone microarchitecture; (3) Analysis of BMD and bone strength; and (4) A state-of-the-art probabilistic approach to analyze bone fracture risk factors including demographic attributes and life styles. Beyond efficient 3D bone microstructure representation, quantitative assessment is considered not only for identifying critical elements in bone microstructure, but also ensuring effective predictioin of bone diseases in advance. The simulation network model of 3D bone microarchitecture and extensive empirical study on fracture risk improve our understanding of bone disease risk arising from the complex interplay of the human BMD assessment result with presence of major risk factors.