Monitoring the Progression of Spontaneous Articular Cartilage Healing with Infrared Spectroscopy. (July 2015)

• Record Type: Journal Article
• Authors: O'Brien, Megan P.; Penmatsa, Madhuri; Palukuru, Uday; West, Paul; Yang, Xu; Bostrom, Mathias P. G.; Freeman, Theresa; Pleshko, Nancy
• Is Part Of: Cartilage. Volume 6:Number 3(2015)
• Page Start: 174
• Page End: 184
• Publication Date: 2015-07
• Subjects: cartilage -- repair tissue -- infrared fiber-optic probe -- FTIR spectroscopy; Cartilage -- Periodicals; 616.7
• DOI: 10.1177/1947603515572874
• Languages: English
• ISSNs: 1947-6035

Abstract

Objective: Evaluation of early compositional changes in healing articular cartilage is critical for understanding tissue repair and for therapeutic decision-making. Fourier transform infrared imaging spectroscopy (FT-IRIS) can be used to assess the molecular composition of harvested repair tissue. Furthermore, use of an infrared fiber-optic probe (IFOP) has the potential for translation to a clinical setting to provide molecular information in situ . In the current study, we determined the feasibility of IFOP assessment of cartilage repair tissue in a rabbit model, and assessed correlations with gold-standard histology. Design: Bilateral osteochondral defects were generated in mature white New Zealand rabbits, and IFOP data obtained from defect and adjacent regions at 2, 4, 6, 8, 12, and 16 weeks postsurgery. Tissues were assessed histologically using the modified O'Driscoll score, by FT-IRIS, and by partial least squares (PLS) modeling of IFOP spectra. Results: The FT-IRIS parameters of collagen content, proteoglycan content, and collagen index correlated significantly with modified O'Driscoll score ( P = 0.05, 0.002, and 0.02, respectively), indicative of their sensitivity to tissue healing. Repair tissue IFOP spectra were distinguished from normal tissue IFOP spectra in all samples by PLS analysis. However, the PLS model for prediction of histological score had a high prediction error, which was attributed to the spectral information being acquired from the tissue surface only. Conclusion: The strong correlations between FT-IRIS data and histological score support further development of the IFOP technique for clinical applications, although further studies to optimize data collection from the full sample depths are required.