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Title: The effects of vertebral variation on the mechanical outcomes of vertebroplasty
Author: Day, Gavin Antony
ISNI:       0000 0004 7961 1989
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2018
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Osteoporotic vertebral compression fractures are a commonly encountered clinical problem that causes a reduced quality of life for a large proportion of those affected. One of the treatments for this type of fracture is vertebroplasty, where the injection of bone cement into the vertebral body aims to stabilise the vertebra and relieve pain. Despite being a frequently used treatment a number of studies and randomised clinical trials have questioned the efficacy of the procedure. These clinical trials and studies have suggested that the procedure is no more effective than a placebo in terms of pain relief. Finite Element (FE) models allow an investigation into the structural and geometric variation that affect the response to augmentation. However, current specimen specific FE models are limited due to the poor reproduction of cement augmentation behaviour. The aims of this thesis were to develop new methods of modelling the vertebral body in an augmented state, using these models as an input to a statistical shape and appearance model (SSAM). Methods were developed for experimental testing, cement augmentation and modelling through a specimen specific modelling approach to create and solve FE models. These methods were initially used with bovine tail vertebrae and then refined for the use of human lumbar vertebrae. These latter models formed the input set for the creation of a SSAM, where vertebral and augmentation variables were examined. Models of augmentation in human lumbar vertebrae achieved a good agreement with their experimental counterparts through the development of novel modelling techniques. A new SSAM method has been developed for human lumbar vertebrae and applied to evaluate the mechanical performance of vertebroplasty. The tools developed can now be applied to examine wider patient cohorts and other clinical therapies.
Supervisor: Wilcox, Ruth K. ; Jones, Alison C. Sponsor: ERC ; EPSRC
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available