Defining and detecting meniscal heterogeneity : implications on treatment and diagnosis of osteoarthritis
Abstract/Contents
- Abstract
- Meniscal degeneration often precedes cartilage degeneration, and effective detection and treatment can be critical in preventing osteoarthritis. The meniscus is a heterogeneous tissue, and obtaining information on the varying characteristics of meniscal regions is important in investigating such strategies. However, no current method exists that can detect such meniscal heterogeneity in the tissue matrix. In addition, the lack of quantitative information on meniscal heterogeneity hinders the development an effective, long-term solution that can treat degeneration in the meniscus. The purpose of this dissertation was thus 1) to find quantitative characteristics that defined meniscal heterogeneity and 2) to evaluate non-invasive diagnostic methods that could reflect the matrix tissue properties and detect meniscal heterogeneity. To accomplish the first goal, gene expression profiles of meniscal cells were statistically analyzed to identify quantitative markers that could distinguish between different regions of the meniscus, describing its heterogeneous properties. This information was then used to evaluate cell sources for meniscal tissue engineering, demonstrating the potential application of these quantitative markers in developing an effective treatment for meniscal degeneration. Secondly, in order to detect meniscal heterogeneity, which is reflected in the changing tissue properties within the tissue, magnetic resonance imaging was used. The potential of the imaging parameters T1[rho] and T2 relaxation times in detecting various meniscal tissue properties, including the matrix composition and mechanical properties, was examined. Ultimately, such information would be useful in identifying internal degenerative changes that take place in the matrix of the tissue prior to macroscopic injuries. In this study, both T1[rho] and T2 relaxation times showed variation with tissue properties but were highly correlated with one another, indicating that only one imaging parameter might be necessary as a diagnostic tool in a clinical setting. In addition, an exploratory aim visualized the internal secondary collagen network in the meniscus and examined its deformation in different mechanical loading positions. This work significantly adds to the understanding of the heterogeneous properties of the meniscus and the potential of magnetic resonance imaging parameters as detection markers. It contributes to the advancement of diagnosis and treatment strategies for meniscal degeneration, which has further implications for preventing osteoarthritis progression.
Description
Type of resource | text |
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Form | electronic; electronic resource; remote |
Extent | 1 online resource. |
Publication date | 2013 |
Issuance | monographic |
Language | English |
Creators/Contributors
Associated with | Son, Min-Sun | |
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Associated with | Stanford University, Department of Bioengineering. | |
Primary advisor | Levenston, Marc Elliot | |
Thesis advisor | Levenston, Marc Elliot | |
Thesis advisor | Gold, Garry E | |
Thesis advisor | Hargreaves, Brian Andrew | |
Advisor | Gold, Garry E | |
Advisor | Hargreaves, Brian Andrew |
Subjects
Genre | Theses |
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Bibliographic information
Statement of responsibility | Min-Sun Son. |
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Note | Submitted to the Department of Bioengineering. |
Thesis | Ph.D. Stanford University 2013 |
Location | electronic resource |
Access conditions
- Copyright
- © 2013 by Minsun Son
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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