? Fitzpatrick Osteoarthritis (OA) is a degenerative joint condition affecting over one third of the US population over age 65. Analysts expect numbers to rise over the coming decades, given the increasingly aging and obese population. Knee OA is most prevalent, and can result in severe pain and debilitation. Since articular cartilage has little regenerative ability, no treatment offers a cure. Therefore, preventing OA initiation and limiting progression is critical to reducing incidence and severity. Historically, clinicians have seen OA as a ?wear-and-tear? condition driven by mechanical loads. However, it is becoming increasingly apparent that initiation and progression is multifaceted. Our goal is to enhance researcher and clinician understanding of OA and improve their ability to predict and then treat early onset and progression. Our objective is to develop the data-driven computational models needed to quantify interactions between the biomechanical, structural, and biological factors. Our hypothesis is that particular combinations of mechanical, structural, and biological factors effectively predict OA, and a computational model can help researchers and clinicians to quantify interactions and significantly improve their ability to apply effective early intervention strategies. Results would have an enormous functional, social, and economic impact across an aging population. Our proposed work focuses on three applications of computational modeling to understand OA: (1) longitudinal cartilage degeneration and relationship to baseline biological and bioimaging markers, (2) the adaptive response of cartilage structure to biological and mechanical inputs, and (3) evaluation of computational models as a potential guidance tool for surgical, rehabilitation, or musculoskeletal adaptation. Our long-term vision is to develop a computational platform that we can efficiently customize for individual subjects to represent their key biomechanical, structural, and biological parameters, enabling pre-clinical evaluation of surgical interventions or of therapies such as exercise/muscle training programs or gait adaptation strategies.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory Grants (P20)
Project #
2P20GM109095-06
Application #
9786634
Study Section
Special Emphasis Panel (ZGM1)
Project Start
Project End
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
6
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Boise State University
Department
Type
DUNS #
072995848
City
Boise
State
ID
Country
United States
Zip Code
83725
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