Assessment of the anabolic effects of PTH drug treatment and mechanical loading on bone using high-resolution imaging and in silico modelling
AffiliationSurgery (St Vincent's)
Document TypePhD thesis
Access StatusOpen Access
© 2018 Dr. Silvia Trichilo
Osteoporosis (OP) is a progressive bone disease characterised by significant reduction of bone mineral density (BMD) due to loss of bone matrix and changes in bone tissue properties. OP is regarded as a worldwide health issue and identifying novel treatments is of central clinical importance. Daily injections of parathyroid hormone (PTH) and exercise have been proven to have an anabolic effect on bone, i.e., are capable of restoring bone mass. In this thesis, the anabolic action of PTH drug treatment and mechanical loading was investigated using in silico modelling and high-resolution imaging techniques. Novel drugs are continuously developed to reduce the risk of bone fractures in osteoporotic patients. PTH peptides such as PTH(1-34) are the first anabolic agents approved to treat severe OP. Despite its success to restore bone mass, PTH mechanism of action on bone cells is still unclear. Recently, the understanding of OP pathophysiology has considerably improved. Biomarkers reflecting bone physiology have been identified at cellular, tissue and organ levels. Cellular biomarkers reflect the dynamics of bone remodelling on a short time scale, whereas tissue and organ scale biomarkers show changes of BMD on a larger time scale. Computational modelling is a novel approach that allows to quantitatively characterise the effect of a drug treatment on the disease progression integrating physiology, disease progression, drug treatment and biomarker data in a comprehensive mechanism-based in silico model. In this context, part of this work was focused on the development of a full time-dependent mechanistic pharmacokinetic-pharmacodynamic (PK/PD) model of the action of PTH(1-34) on bone modelling and remodelling. This model was applied to rat models of OP to shed light on the inter-cellular and tissue scale mechanisms involved in the action of PTH(1-34) on bone cells. This in silico model has the potential to predict the long-term effects of drug treatments on clinical outcomes and provide a means for patient-specific estimation of bone fracture risk. Furthermore, it is well known that bone adapts its mass and structure in response to stresses and strains induced by an external mechanical load. The most extensively used animal model to test hypotheses related to mechanical loading is the in vivo axial compression of the mouse tibia. Common outcome measures of these models are bone geometric dimensions and bone mineral density using high-resolution imaging techniques, i.e., micro-computed tomography (micro-CT). In this thesis, end-point micro-CT imaging data were analysed to quantify the local adaptation response of bone to both mechanical loading and PTH(1-34) drug treatment in the mouse tibia loading model. An innovative image post-processing algorithm was developed to quantify the cortical thickness locally along the periosteum. Furthermore, an algorithm was developed to estimate stresses, strains and strain energy density (SED) on periosteal surfaces of the tibia, combining micro- finite element analysis and beam theory to compute animal-specifi c SED. Bone adaptation to mechanical loading was variable along the periosteum. Results suggest that bone adaptation is higher in regions with higher SED. Moreover, mechanical loading and PTH induce a combined anabolic adaptation effect on bone suggesting that the association of PTH(1-34) administration and exercise may be an effective treatment for OP.
KeywordsPTH; osteoporosis; bone remodelling; micro-CT images; computational modelling; bone adaptation; axial compression of mouse tibia
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