Visualization and evaluation tools of quantitative MRI in an ACL-injured population
Abstract/Contents
- Abstract
- Osteoarthritis (OA) is a degenerative whole joint disease that affects 27 million US adults and has societal health care expenditures of close to $189 billion annually. Research demonstrates that an anterior cruciate ligament injury (ACL-injury) is a risk factor for the development of posttraumatic OA. Studies have reported that ~50% of ACL-injured knees develop OA 10-20 years post-initial injury. Unfortunately, this disease has no cure and detection happens too late in the degenerative process where management of pain or total knee replacement is the standard of care. Amongst the many tissues involved in OA, the cartilage is widely studied and has been shown to degenerate with the disease. Pre-morphological changes to its biochemical composition have been shown to correlate with changes in quantitative magnetic resonance imaging (MRI) parameters. In particular, focal defects in cartilage are an important pathology of OA, however, the quantitative MRI literature on this feature is sparse. There remains a significant need to adequately capture and quantify pathological focal changes present in early cartilage degeneration as well as in other tissues. This objective assessment of the many tissues involved may lead to early OA detection and a way to effectively evaluate new therapies. In this thesis, we present a method to assess focal defects using quantitative MRI data and use this method in an ACL-injured group over time. This method involves converting full 3D acquired quantitative MRI data into sufficiently reproducible vi projection maps that we then use to develop an objective outcome measure for quantifying changes in focal cartilage defects. Applying this tool to assess the focal lesions present in ACL-injured knees, we subsequently show significant differences in these knees compared to a healthy group. Next, we apply this tool to assess the presence of focal lesions in the uninjured contralateral knees and observe comparable quantitative MRI focal changes over one year. Finally, we demonstrate the feasibility of using this tool to assess the bone, another tissue involved in the OA degenerative process by analyzing the positron emission tomography (PET) tracer uptake values and studying the interaction of bone metabolic activity with adjacent cartilage composition using a simultaneous PET-MRI system. As OA is a whole joint disease that is detected too late, it is important to study key premorphological features as well as the interactions across multiple tissues. A lot of advancements have been made in studying the cartilage composition and new developments in imaging systems and sequences will enable improved assessments. Our developed tool motivates the importance of studying focal lesions within the ACLinjured group as a way of developing a more sensitive measure of onset. By using this tool to characterize this feature within the cartilage and across multiple tissues, we may be able to further understand this complex disease and objectively assess the effectiveness of drug therapies that may be developed.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2017 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Monu, Uchechukwuka Diana | |
|---|---|---|
| Associated with | Stanford University, Department of Electrical Engineering. | |
| Primary advisor | Hargreaves, Brian Andrew | |
| Primary advisor | McWalter, Emily Jane | |
| Thesis advisor | Hargreaves, Brian Andrew | |
| Thesis advisor | McWalter, Emily Jane | |
| Thesis advisor | Gold, Garry E | |
| Thesis advisor | Nishimura, Dwight George | |
| Advisor | Gold, Garry E | |
| Advisor | Nishimura, Dwight George |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Uchechukwuka Diana Monu. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2017. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2017 by Uchechukwuka Diana Monu
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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