The purpose of the Imaging and Data Analysis Core (IDAC) is to provide all projects in the TOQIO with the infrastructure, expertise and tools to support customized imaging acquisition as well as image and data analysis, including 1) imaging sequence development, 2) image reconstruction and processing, 3) semi-quantitative clinical grading of images, 4) quantitative image analysis, 5) data integration and database development, and 6) statistical data analysis. Many of the procedures needed to provide this capability are novel and require specialized knowledge of imaging physics and mathematics as well as clinical aspects of osteoarthritis. This will require a close interaction between the researchers developing new imaging methodologies, computing specialists who develop reconstruction algorithms and software tools to perform quantitative analyses of the data, radiologists and other clinical investigators who will grade the images, and biostatisticians who contribute to the experimental design, hypothesis formulation and statistical analysis. It is anticipated that the Core will not only provide support for the four research projects and other pilot projects within the TOQIO, but will also act as a catalyst for introducing these technologies into a broad range of musculoskeletal translational research projects, throughout UCSF and its Clinical and Translational Science Institute (CTSI) and through the UC Davis Medical Center and its Clinical and Translational Science Center and other forms of outreach. The IDAC has three primary aims: 1) To provide quantitative magnetic resonance imaging sequences for tissues involved in osteoarthritis;2) To provide image grading and quantitative analysis;3) To provide Interpretation and statistical analysis of imaging and clinical data. The investigators involved in IDAC have established backgrounds in translational and basic research, including expertise in imaging sequence development, image processing, algorithm development, quantitative image analysis, MR and radiograph clinical grading and statistical analysis, with a focus on osteoarthritis. They have been performing studies that require similar expertise to the ones described in this application for many years and have developed a rapport that is critical for the highly collaborative and demanding studies that are being proposed. IDAC is also committed to disseminating information pertaining to the capabilities of the Core, increasing research collaborations, and providing educational sessions to major, minor users, residents, fellows and students. Its overarching goal will be to promote adoption of state-of-the-art imaging methodology in musculoskeletal research. In addition to the UCSF and UC Davis Medical Centers, the research images, software and data generated by TOQIO will be also available to researchers at other academic institutes upon request and with required paperwork.

Public Health Relevance

The purpose of the Imaging and Data Analysis Core (IDAC) is to provide all projects in the TOQIO with the infrastructure, expertise and tools to support customized imaging acquisition as well as image and data analysis. IDAC is also committed to the dissemination of information pertaining to the capabilities of the Core, and to promoting the adoption of state-of-the-art imaging methodology in musculoskeletal research.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Specialized Center (P50)
Project #
Application #
Study Section
Special Emphasis Panel (ZAR1-KM)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California San Francisco
San Francisco
United States
Zip Code
Joseph, G B; Nevitt, M C; McCulloch, C E et al. (2018) Associations between molecular biomarkers and MR-based cartilage composition and knee joint morphology: data from the Osteoarthritis Initiative. Osteoarthritis Cartilage 26:1070-1077
Amano, Keiko; Huebner, Janet L; Stabler, Thomas V et al. (2018) Synovial Fluid Profile at the Time of Anterior Cruciate Ligament Reconstruction and Its Association With Cartilage Matrix Composition 3 Years After Surgery. Am J Sports Med 46:890-899
Samaan, Michael A; Pedoia, Valentina; Zhang, Alan L et al. (2018) A novel mr-based method for detection of cartilage delamination in femoroacetabular impingement patients. J Orthop Res 36:971-978
Hofmann, Felix C; Neumann, Jan; Heilmeier, Ursula et al. (2018) Conservatively treated knee injury is associated with knee cartilage matrix degeneration measured with MRI-based T2 relaxation times: data from the osteoarthritis initiative. Skeletal Radiol 47:93-106
Pedoia, Valentina; Samaan, Michael A; Inamdar, Gaurav et al. (2018) Study of the interactions between proximal femur 3d bone shape, cartilage health, and biomechanics in patients with hip Osteoarthritis. J Orthop Res 36:330-341
Teng, Hsiang-Ling; Pedoia, Valentina; Link, Thomas M et al. (2018) Local associations between knee cartilage T1? and T2 relaxation times and patellofemoral joint stress during walking: A voxel-based relaxometry analysis. Knee 25:406-416
Pedoia, Valentina; Haefeli, Jenny; Morioka, Kazuhito et al. (2018) MRI and biomechanics multidimensional data analysis reveals R2 -R1? as an early predictor of cartilage lesion progression in knee osteoarthritis. J Magn Reson Imaging 47:78-90
Bolcos, Paul O; Mononen, Mika E; Mohammadi, Ali et al. (2018) Comparison between kinetic and kinetic-kinematic driven knee joint finite element models. Sci Rep 8:17351
Lansdown, Drew; Ma, Chunbong Benjamin (2018) The Influence of Tibial and Femoral Bone Morphology on Knee Kinematics in the Anterior Cruciate Ligament Injured Knee. Clin Sports Med 37:127-136
Schwaiger, Benedikt J; Mbapte Wamba, John; Gersing, Alexandra S et al. (2018) Hyperintense signal alteration in the suprapatellar fat pad on MRI is associated with degeneration of the patellofemoral joint over 48 months: data from the Osteoarthritis Initiative. Skeletal Radiol 47:329-339

Showing the most recent 10 out of 150 publications