Optimizing prediction and understanding of osteoporotic insufficiency fractures using surrogate models, numerical simulation and quantification of local anisotropies by X-ray Vector Radiography

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Osteoporosis is the most frequent systemic skeletal disorder. It is characterized by a reduction of bone mass and deterioration of bone microarchitecture, resulting in an increased susceptibility to fracture. Consecutive vertebral fractures are associated with a massive increase in mortality. To predict fracture risk, currently only bone mineral density (BMD) is assessed in addition to clinical risk factors (e.g. by the FRAX of the WHO); however multiple studies demonstrated a significant improve in assessing biomechanical strength in vitro as well as fracture risk in vivo by using numerical simulations, based on bone macro- and micro-architecture.In this project, we will improve both understanding and prediction of biomechanical properties of osteoporotic bone and consecutive fracture development. To achieve these goals, we will analyze local anisotropy of trabecular and cortical bone using micro-CT and dark field imaging (X-ray Vector Radiography). Dark field imaging is a new modality, complementary to conventional X-ray imaging. It will be optimized for bone imaging and will give insight into the anisotropy of the trabecular network. Material models will be optimized regarding the image quality available in vitro and in vivo. We will simulate bone remodeling using surrogates for different dynamic loading conditions and interactions between osteoclasts, osteoblasts and medications. These results will be integrated in different numerical simulations. Finally, the optimized numerical simulations will be applied to patient data, to improve the prediction of individual fracture risk in the context of clinical risk factors and biomarkers.