Osteoarthritis (OA) is a major health concern affecting more than 20 million people in US. The disease is predominantly characterized by a gradual degeneration of the load-bearing tissue in joint, articular cartilage. Before the earliest clinical diagnosis of OA, a series of complex and depth-dependent events at various molecular and structural levels has already taken place inside cartilage. A lack of non-invasive and molecular-specific markers to detect the early degradation events in cartilage has so far prevented a fundamental understanding of the development of OA, as well as early diagnosis of and intervention in OA. Due to its multi-level hierarchical organization, multidisciplinary measurements that interrogate cartilage at different technical modalities are warranted. Due to its depth-dependent and heterogeneous structure, a thorough understanding of tissue's response to external loading requires microscopic imaging. Recently, we have successfully imaged the load-induced ultrastructural adaptability in cartilage using at high resolution. We use static loading as a tool to force the tissue to reach a new equilibrium with the environment in order to probe cartilage's intrinsic properties and structural adaptability in a depth-resolved manner in imaging. In essence, static loading becomes a controllable mechanism to induce additional contrast and to enhance weak contrast in our imaging work. The overarching goal of this proposal is to detect the early changes in the in situ molecular architecture of diseased articular cartilage. We hypothesize that the load-induced changes in cartilage at the structural and molecular levels can be detected by a combination of microscopic imaging modalities and that the degradation in cartilage due to diseases or mechanical injury could affect load-induced ultrastructural changes, which will be calibrated by immunohistochemistry imaging. The three specific aims of this study will determine a set of multidisciplinary parameters that detects various changes in tissue's response to static loading due to biochemical digestion, natural lesion, and repetitive/dynamic loading. In combination, this proposal will go beyond the level of describing and characterizing the imaging signals.
It aims to put these imaging techniques to work as the predictors of disease progression, and monitors of injury and repair. Osteoarthritis, which is a major health concern affecting more than 20 million people in US, is predominantly characterized by a gradual degeneration of the load-bearing tissue in joint, articular cartilage. This project aims to detect the early changes in the in situ molecular architecture of diseased cartilage using a set of multidisciplinary microscopic imaging techniques.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR052353-05
Application #
8242811
Study Section
Microscopic Imaging Study Section (MI)
Program Officer
Tyree, Bernadette
Project Start
2008-04-30
Project End
2014-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
5
Fiscal Year
2013
Total Cost
$422,505
Indirect Cost
$117,162
Name
Oakland University
Department
Physics
Type
Schools of Arts and Sciences
DUNS #
041808262
City
Rochester
State
MI
Country
United States
Zip Code
48309
Zhuang, Zhiguo; Lee, Ji Hyun; Badar, Farid et al. (2016) The influences of different spatial resolutions on the characteristics of T2 relaxation times in articular cartilage: A coarse-graining study of the microscopic magnetic resonance imaging data. Microsc Res Tech 79:754-65
Jia, Haoruo; Ma, Xiaoyuan; Tong, Wei et al. (2016) EGFR signaling is critical for maintaining the superficial layer of articular cartilage and preventing osteoarthritis initiation. Proc Natl Acad Sci U S A 113:14360-14365
Mao, Zhi-Hua; Yin, Jian-Hua; Zhang, Xue-Xi et al. (2016) Discrimination of healthy and osteoarthritic articular cartilage by Fourier transform infrared imaging and Fisher's discriminant analysis. Biomed Opt Express 7:448-53
Xia, Yang; Stilbs, Peter (2016) The First Study of Cartilage by Magnetic Resonance: A Historical Account. Cartilage 7:293-7
Wang, Nian; Badar, Farid; Xia, Yang (2015) MRI properties of a unique hypo-intense layer in degraded articular cartilage. Phys Med Biol 60:8709-21
Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua et al. (2015) Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis. J Biomed Opt 20:060501
Lee, Ji Hyun; Badar, Farid; Kahn, David et al. (2015) Loading-induced changes on topographical distributions of the zonal properties of osteoarthritic tibial cartilage - A study by magnetic resonance imaging at microscopic resolution. J Biomech 48:3634-42
Wang, Nian; Kahn, David; Badar, Farid et al. (2015) Molecular origin of a loading-induced black layer in the deep region of articular cartilage at the magic angle. J Magn Reson Imaging 41:1281-90
Kahn, David; Les, Clifford; Xia, Yang (2015) Effects of cryopreservation on the depth-dependent elastic modulus in articular cartilage and implications for osteochondral grafting. J Biomech Eng 137:054502
Yin, Jianhua; Xia, Yang (2014) Proteoglycan concentrations in healthy and diseased articular cartilage by Fourier transform infrared imaging and principal component regression. Spectrochim Acta A Mol Biomol Spectrosc 133:825-30

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