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Measurement of cartilage sub-component distributions through the surface by Raman spectroscopy-based multivariate
Daniel Mason1, Sangeeta Murugkar2, Andrew D Speirs1
1Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, Canada.
Journal of Biophotonics
|September 14, 2020
Summary
Surface Raman spectroscopy non-destructively measures articular cartilage composition up to 0.5 mm deep. This technique shows promise for in situ analysis of joint tissues, aiding osteoarthritis research.
Area of Science:
- Biomedical Engineering
- Materials Science
- Spectroscopy
Background:
- Articular cartilage has unique depth-dependent material properties.
- Raman spectroscopy quantifies cartilage composition via cross-sections, but this is destructive and not practical in situ.
- Non-destructive methods are needed for in situ analysis of cartilage composition.
Purpose of the Study:
- To develop and validate a non-destructive, in situ method for measuring articular cartilage composition.
- To quantify collagen, glycosaminoglycan, and water distributions through the cartilage surface.
- To assess the utility of an optical clearing agent for improving measurement depth.
Main Methods:
- Raman spectroscopy-based multivariate curve resolution (MCR) was applied to porcine cartilage samples (n=12).
- Measurements were taken through the cartilage surface and compared against cross-section standards.
- A fructose-based optical clearing agent (OCA) was tested to enhance depth resolution.
Main Results:
- Surface Raman spectroscopy reliably predicted composition distribution up to a depth of approximately 0.5 mm.
- The OCA did not improve depth resolution due to high spectral overlap with cartilage components.
- The developed method provides a non-destructive means to assess cartilage composition.
Conclusions:
- Surface Raman spectroscopy-MCR is a viable technique for non-destructively measuring cartilage composition in situ.
- This method has potential applications in understanding the etiology of joint diseases like osteoarthritis (OA).
- Further optimization is needed to improve measurement depth beyond 0.5 mm.
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