Non-invasive assessment of bone strength

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Bone is a remarkably adaptive tissue that can rapidly remodel as a result of disease or injury. The three-dimensional (3D) microstructure of bone is key to understanding bone mechanics, and advancements of computed tomography (CT), coupled with customized finite element (FE) analysis methods, permit the analysis of how bone remodeling signals are distributed through the complex structure. Since 2002, my lab has made significant strides towards efficient and accurate computational modeling. This leads to enormous opportunities to advance our understandings of the mechanisms of bone adaptation through integration of technologies and the development of new computational approaches. Continuing with the long-term objective of my research program, this next phase will utilize novel longitudinal datasets to establish the fundamental mechanisms of bone adaptation under a variety of scenarios. It will couple analysis of time-series image data with FE modeling to directly link biological adaptations of bone to its mechanical and physiological functions. New directions also include developing multi-modal imaging approaches that integrate magnetic resonance imaging (MRI) and CT so that the functional interaction of key biological tissues, specifically cartilage and bone, can be explored. There are three main objectives of the next phase of my research program. First, establish a mechanistic model of bone adaptation that takes experimental longitudinal data of subjects who have (i) been exposed to microgravity for periods of six months (International Space Station astronauts), (ii) represent normal aging through our population-based study, and (iii) are undergoing experimental therapies to augment their bone strength. Coupling patient-specific FE models with measured local changes to bone microarchitecture provides a unique basis to learn about the mechanisms of bone adaptation. Second, advance high-throughput image processing, with the strategy to allow analysis of large volumes of 3D image data representing multi-year datasets. The natural variability of bone adaptation among individuals is large, and necessitates high-throughput approaches to maximum the number of serial observations. The third objective establishes methods to integrate hard and soft tissue measurements at high resolution so that comprehensive FE models can be developed that represent integrated biomechanical models of joints to study the tissue interactions. Overall, this research program uses advanced imaging and high-performance FE modeling to establish mechanistic models of tissue adaptation, and applies it to large, rich datasets that have been acquired through several recent studies in my lab. This approach provides an important biomedical engineering contribution toward understanding mechanisms of bone adaptation.