Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675788
Title: Articulated statistical shape models for the analysis of bone destruction in mouse models of rheumatoid arthritis
Author: Brown, James
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2015
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Abstract:
Rheumatoid arthritis is an autoimmune disease that affects approximately 1% of the population, where chronic inflammation of the synovial joints can lead to active destruction of cartilage and bone. New therapeutic targets are discovered by investigating genes or processes that exacerbate or ameliorate disease progression. Mouse models of inflammatory arthritis are commonly employed for this purpose, in conjunction with biomedical imaging techniques and suitable measures of disease severity. This thesis investigated the hypothesis that a statistical model of non-pathological bone shape variation could be used to quantify bone destruction present in micro-CT images. A framework for constructing statistical shape models of the hind paw was developed, based on articulated registration of a manually segmented reference image. Successful registration of the reference towards ten healthy hind paw samples was followed by statistical shape analysis. Mouse models of inflammatory arthritis were then investigated and compared by identifying bone abnormalities as deviations from the model statistics. Validation of the model against digital phantoms and clinical scores indicates that the method is largely successful in this effort. Application of the method in a novel study of macrophage-mediated inflammation shows promising results that are supportive of previous findings.
Supervisor: Not available Sponsor: Engineering and Physical Sciences Research Council (EPSRC)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.675788  DOI: Not available
Keywords: QA75 Electronic computers. Computer science ; QA76 Computer software ; QH301 Biology ; QR180 Immunology ; RC Internal medicine
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