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Published on: January 6, 2018
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Investigating cartilage-related diseases by polarization-resolved second harmonic generation (P-SHG) imaging
Kausalya Neelavara Makkithaya1, Nirmal Mazumder1, Wei-Hsun Wang2
1Department of Biophysics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka 576104, India.
APL Bioengineering
|May 2, 2024
Summary
This study uses advanced imaging to identify collagen changes in cartilage, distinguishing healthy tissue from osteoarthritis and rheumatoid arthritis. These findings offer new quantitative markers for diagnosing cartilage diseases.
Area of Science:
- Biomedical Optics
- Materials Science
- Rheumatology
Background:
- Cartilage degradation is central to osteoarthritis (OA) and rheumatoid arthritis (RA).
- Understanding collagen fibril changes is key to diagnosing and managing these diseases.
- Current diagnostic methods may benefit from quantitative molecular insights.
Purpose of the Study:
- To establish quantitative parameters for differentiating healthy, OA, and RA cartilage.
- To investigate collagen fibril degradation patterns using advanced imaging techniques.
- To correlate imaging parameters with specific pathological changes in cartilage.
Main Methods:
- Analysis of normal, OA, and RA cartilage samples.
- Utilizing polarization-resolved second harmonic generation (P-SHG) imaging.
- Applying quantitative image texture analysis to P-SHG data.
Main Results:
- P-SHG imaging revealed distinct collagen parameters across different cartilage states.
- Normal cartilage showed different χ33/χ31 values compared to OA and RA.
- OA cartilage exhibited increased linear polarization and directional collagen orientation, linked to type-I collagen deposition.
- RA cartilage displayed heterogeneous collagen molecular orientation.
Conclusions:
- P-SHG imaging and quantitative analysis provide valuable parameters for cartilage disease diagnostics.
- The study offers a clear understanding of collagen fibril degradation in OA and RA.
- These quantitative markers can complement existing clinical diagnostic tools for cartilage-related diseases.

