Description): This proposal focusses on using Magnetic Resonance (MR) imaging to study injury induced joint degeneration and subsequent repair mechanisms and the manifested changes in articular cartilage, subchondral bone and peri-articular trabecular bone.
It aims to establish the relative role and interaction between cartilage and bone changes in injury induced osteoarthrosis (OA). Osteoarthrosis, often caused by injuries to the knee joint, alters mechanical joint loading, and all the major joint tissues, including the articular cartilage, synovium, subchondral and trabecular bone and muscle have been implicated. The condition is characterized by a long asymptomatic phase when articular cartilage degenerates, reparative changes occur and radiographic changes develop. A symptomatic or painful stage then develops after irreversible cartilage damage has occurred and radiographic changes progress. It has been hypothesized that articular degeneration and progression of OA may be preceded by changes in subchondral and trabecular bone. Although trabecular bone interactions are implicated in early OA, the changes in the trabecular bone adjoining the articular cartilage associated with OA, are unclear and the trend of changes has not been defined conclusively. In this context, magnetic resonance imaging (MR), which has recently been used to depict trabecular bone structure may potentially be a valuable tool, particularly since MR images may also be used to quantify the cartilage volume, thickness, water diffusion and relaxation time which characterize the biochemical status of the cartilage, as well as measure trabecular bone. The investigators propose to make use of recent advances in MR to accurately quantify (1) the 3-D morphology and relaxation time and water diffusion characteristics of articular cartilage, and (2) the 3-D architecture of the trabecular bone network adjoining the articular cartilage, subchondral bone thickness, and density in normal and osteoarthritic (mild and severe or Kellgren-Lawrence scale 1 and 4) subjects.
They aim to derive the relation of these measures to clinical measures such as pain and disability (WOMAC scale, Health Activity Questionnaire, etc.) and radiographic evidence of osteoarthrosis as demonstrated by Kellgren-Lawrence Scores. Subjects with mild OA and normals will also be followed longitudinally to determine the progression of joint degeneration, the relative chronological occurrence of bone and cartilage changes, and the ability of MR to predict joint degeneration and reflect the repair mechanisms postinjury.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
1R01AR046905-01
Application #
2850081
Study Section
Special Emphasis Panel (ZHD1-RRG-K (32))
Program Officer
Panagis, James S
Project Start
1999-09-17
Project End
2004-08-31
Budget Start
1999-09-17
Budget End
2000-08-31
Support Year
1
Fiscal Year
1999
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
073133571
City
San Francisco
State
CA
Country
United States
Zip Code
94143
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
Chanchek, Nattagan; Gersing, Alexandra S; Schwaiger, Benedikt J et al. (2018) Association of diabetes mellitus and biochemical knee cartilage composition assessed by T2 relaxation time measurements: Data from the osteoarthritis initiative. J Magn Reson Imaging 47:380-390
Rossi-deVries, Jasmine; Pedoia, Valentina; Samaan, Michael A et al. (2018) Using multidimensional topological data analysis to identify traits of hip osteoarthritis. J Magn Reson Imaging 48:1046-1058
Norman, Berk; Pedoia, Valentina; Majumdar, Sharmila (2018) Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry. Radiology 288:177-185
Samaan, Michael A; Facchetti, Luca; Pedoia, Valentina et al. (2017) Cyclops lesions are associated with altered gait patterns and medial knee joint cartilage degeneration at 1 year after ACL-reconstruction. J Orthop Res 35:2275-2281
Adusumilli, Gautam; Joseph, Solomon Eben; Samaan, Michael A et al. (2017) iPhone Sensors in Tracking Outcome Variables of the 30-Second Chair Stand Test and Stair Climb Test to Evaluate Disability: Cross-Sectional Pilot Study. JMIR Mhealth Uhealth 5:e166
Russell, C; Pedoia, V; Souza, R B et al. (2017) Cross-sectional and longitudinal study of the impact of posterior meniscus horn lesions on adjacent cartilage composition, patient-reported outcomes and gait biomechanics in subjects without radiographic osteoarthritis. Osteoarthritis Cartilage 25:708-717
Pedoia, Valentina; Li, Xiaojuan; Su, Favian et al. (2016) Fully automatic analysis of the knee articular cartilage T1? relaxation time using voxel-based relaxometry. J Magn Reson Imaging 43:970-80
Calixto, Nathaniel E; Kumar, Deepak; Subburaj, Karupppasamy et al. (2016) Zonal differences in meniscus MR relaxation times in response to in vivo static loading in knee osteoarthritis. J Orthop Res 34:249-61

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