Interactions between all the major joint tissues, including the articular cartilage, meniscus, and trabecular bone have been implicated in osteoarthritis (OA). Magnetic resonance (MR) images have been used to quantify the cartilage morphology, volume and thickness, relaxation times T2 and T1?. During the prior funding period, the relationship between cartilage T2 and T1? (mean and spatial heterogeneity), radiographic Kellgren-Lawrence (KL) score, the Western Ontario and McMaster University Osteoarthritis Index (WOMAC), changes in cartilage volume, thickness, trabecular bone volume fraction (BV/TV), trabecular number (Tb.N), fat/water ratios in bone marrow edema like lesions (BMEL) was established. Meniscus and cartilage have similar biochemical constituents, load-dissipating function, and undergo repetitive loading, thus, T2 and T1? methods may also be extended to studying meniscus. Differences in loaded and unloaded T2 and T1? of cartilage and meniscus may reflect biochemical composition and levels of degeneration may potentially be a metric for predicting the progression of OA. This renewal will add to the field of research by extending the quantitative approach of the original proposal to the meniscus, an important tissue in OA, acquire additional years of follow-up for cartilage and bone measures, and examine changes in the soft tissues with loading, where loading at 50% body weight will be accomplished using a device built in-house.
Specific Aim 1 : To quantify both cross-sectionally and longitudinally (annual over 3 years), differences in regional variations and spatial heterogeneity of T2 and T1? maps of the meniscus in controls and subjects with OA. To establish the correlation of the meniscus metrics with metrics from surrounding and overlying cartilage volume and thickness, cartilage T2 and T1? maps, trabecular bone morphology, morphological grades (WORMS), and functional scores (WOMAC).
Specific Aim 2 : To compare baseline and longitudinal differences in unloaded and loaded cartilage and meniscus T2 and T1? (loaded T2-unloaded T2 =?T2 and similarly ?T1A) in controls and OA subjects, and whether baseline ?T2 and ?T1A predict disease progression.

Public Health Relevance

This study will develop non invasive biomarkers for cartilage and meniscus degeneration in the knee. We will also examine differences in these tissues with loading. This will help individuals who have or are at risk for developing osteoarthritis.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR046905-12
Application #
8286838
Study Section
Skeletal Biology Structure and Regeneration Study Section (SBSR)
Program Officer
Lester, Gayle E
Project Start
1999-09-17
Project End
2016-05-31
Budget Start
2012-06-01
Budget End
2013-05-31
Support Year
12
Fiscal Year
2012
Total Cost
$621,349
Indirect Cost
$205,067
Name
University of California San Francisco
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
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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
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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
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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
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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