This thesis reports on methods developed to identify and quantify the normal morphology ofthe intra-articular synovial folds ofthe lateral atlanto-axial joints to aid in the identification and quantification of injury to these structures in patients. A system ofnaming and classifying the synovial folds was developed to remove the ambiguity surrounding the various terminologies applied to these structUres. A comprehensive .' critical review of the literature revealed that the potential role ofthe synovial folds in the generation ofneck pain and disability is poorly understood, primarily because ofthe limited techniques available to identify the synovial folds and to quantify their diinensions. New anatomical methods to quantify objectively the morphology ofthe synovial folds in vitro were developed. The precision and accuracy ofthese methods· . were established through a series of validation experiments and a robust statistical analysis ofthe results. To address the current difficulty in visualising and quantifying the synovial folds in vivo new methods of magnetic resonance (MR) imaging were developed and validated for precision and accuracy through statistically viable experiments. This is the first study10 develop an MR imaging protocol that enables the synovial folds of the lateral atlanto-axialjoints to be visualised in vivo. The statistical approaches commonly used in similar research for the determination ofmeasurement precision were critically reviewed and their strengths and limitations discussed. Using these newly developed anatomical and imaging methods, the normal morphology ofthe synovial folds of the lateral atlanto-axialjoints was determined and the results are presented. Future developments and applications of this work, including applications to investigations of pain and disability affecting the cervical spine, are discussed.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:485528 |
| Date | January 2007 |
| Creators | Webb, Alexandra Louise |
| Publisher | University of Southampton |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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