Abstract Title
The Statistical Model of the Interaction Between Imaging and Biological Factors in the Osteoarthritis Initiative Database
Additional Funding Sources
The project described was supported by the Pacific Northwest Louis Stokes Alliance for Minority Participation through the National Science Foundation under Award No. HRD-1410465.
Abstract
Objective: Osteoarthritis (OA) is a multifactorial disease – many variable anatomic and biological factors contribute to disease initiation and progression. Understanding how these factors are interrelated can help understand the mechanisms of (OA). The objective of this study is to develop 3D knee model representations of a subject in the Osteoarthritis Initiative (OAI) from magnetic resonance imaging (MRI) and compare the structural change with their clinical information and pain progress over a period of time.
Materials and Methods: The OAI is a longitudinal study for knee osteoarthritis and has provided researchers with data from eight year. We selected an OAI patient, who had a large change in their Kellgren and Lawrence scale. We used MRI data at three time points — 0, 24, 48 months and reconstructed these images into a 3D model using Amira software. We extracted this subject’s clinical and biological data that was provided in the OAI dataset.
Results: We compared joint anatomy across all these 3D models, and recorded the change in cartilage and growth of osteophytes. We are in process of comparing these structural changes with overall anatomy and clinical and biological factors.
Conclusions: This study is a preliminary assessment of the relationships between multiple factors that contribute to OA. In future we will expand on this work to incorporate mechanical factors using finite element simulator, and perform thorough investigation of relationships between structural, biological and mechanical factors.
The Statistical Model of the Interaction Between Imaging and Biological Factors in the Osteoarthritis Initiative Database
Objective: Osteoarthritis (OA) is a multifactorial disease – many variable anatomic and biological factors contribute to disease initiation and progression. Understanding how these factors are interrelated can help understand the mechanisms of (OA). The objective of this study is to develop 3D knee model representations of a subject in the Osteoarthritis Initiative (OAI) from magnetic resonance imaging (MRI) and compare the structural change with their clinical information and pain progress over a period of time.
Materials and Methods: The OAI is a longitudinal study for knee osteoarthritis and has provided researchers with data from eight year. We selected an OAI patient, who had a large change in their Kellgren and Lawrence scale. We used MRI data at three time points — 0, 24, 48 months and reconstructed these images into a 3D model using Amira software. We extracted this subject’s clinical and biological data that was provided in the OAI dataset.
Results: We compared joint anatomy across all these 3D models, and recorded the change in cartilage and growth of osteophytes. We are in process of comparing these structural changes with overall anatomy and clinical and biological factors.
Conclusions: This study is a preliminary assessment of the relationships between multiple factors that contribute to OA. In future we will expand on this work to incorporate mechanical factors using finite element simulator, and perform thorough investigation of relationships between structural, biological and mechanical factors.
Comments
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