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Title: Multi-scale imaging and modelling of bone
Author: Chen, B.
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2013
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The multi-level organization of bone facilitates the exploitation of in-vivo micro-scale information which is currently lacking for clinical applications. The three sub-projects presented in this thesis investigate the human skeletal system at multiple scales using magnetic resonance imaging (MRI) with the aim of providing new techniques for extracting finer scale information in-vivo. At the whole organ level, human knee joint kinematics was studied using a combined MRI strategy. This new strategy enables the in-vivo investigation of tibiofemoral locomotion under body weight-bearing conditions by modelling the knee flexion angle as a function of the femur and tibia cartilage surfaces in contact. The resultant "contact" trajectory may potentially be used to understand the mechanical cause of cartilage degeneration and as a biomarker to detect abnormalities in the lower limb. At the molecular level, in-vivo MR diffusion tensor imaging (DTI) has been performed for the first time in the human tibia epiphysis. By tracking the water molecules inside the red marrow, the organization of trabecular bone network may be understood as the streamlines formed by anisotropic diffusion trajectories. This sub-project aims to understand the organization of trabecular bone networks non-invasively, which is usually performed ex-vivo through biopsies. The feasibility and reproducibility of DTI is studied. Finally, a new MR imaging protocol named multi-directional sub-pixel enhancement (mSPENT) is proposed and developed to quantify the trabecular bone structural arrangement at the meso-scale. By modulating a dephasing gradient to manipulate the underlying spin system inside each voxel, the resulting mSPENT image contrast varies with gradient at different directions based on the magnetization at the corresponding voxel. A tensor-based method is further developed to model this contrast change, leading to a localized quantification of tissue structural orientation beyond the conventional MR imaging resolution.
Supervisor: Todd-Pokropek, A. ; Fry, M. ; Offiah, A. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available