Infrared Fiber-Optic Spectroscopy Detects Bovine Articular Cartilage Degeneration

Author:

Virtanen Vesa1ORCID,Nippolainen Ervin2,Shaikh Rubina2,Afara Isaac O.23ORCID,Töyräs Juha243,Solheim Johanne5,Tafintseva Valeria5,Zimmermann Boris5,Kohler Achim5,Saarakkala Simo16,Rieppo Lassi1

Affiliation:

1. Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland

2. Department of Applied Physics, University of Eastern Finland, Kuopio, Finland

3. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland, Australia

4. Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland

5. Biospectroscopy and Data Modeling Group, Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway

6. Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland

Abstract

Objective Joint injuries may lead to degeneration of cartilage tissue and initiate development of posttraumatic osteoarthritis. Arthroscopic surgeries can be used to treat joint injuries, but arthroscopic evaluation of articular cartilage quality is subjective. Fourier transform infrared spectroscopy combined with fiber optics and attenuated total reflectance crystal could be used for the assessment of tissue quality during arthroscopy. We hypothesize that fiber-optic mid-infrared spectroscopy can detect enzymatically and mechanically induced damage similar to changes occurring during progression of osteoarthritis. Design Bovine patellar cartilage plugs were extracted and degraded enzymatically and mechanically. Adjacent untreated samples were utilized as controls. Enzymatic degradation was done using collagenase and trypsin enzymes. Mechanical damage was induced by (1) dropping a weight impactor on the cartilage plugs and (2) abrading the cartilage surface with a rotating sandpaper. Fiber-optic mid-infrared spectroscopic measurements were conducted before and after treatments, and spectral changes were assessed with random forest, partial least squares discriminant analysis, and support vector machine classifiers. Results All models had excellent classification performance for detecting the different enzymatic and mechanical damage on cartilage matrix. Random forest models achieved accuracies between 90.3% and 77.8%, while partial least squares model accuracies ranged from 95.8% to 84.7%, and support vector machine accuracies from 91.7% to 80.6%. Conclusions The results suggest that fiber-optic Fourier transform infrared spectroscopy attenuated total reflectance spectroscopy is a viable way to detect minor and major degeneration of articular cartilage. Objective measures provided by fiber-optic spectroscopic methods could improve arthroscopic evaluation of cartilage damage.

Funder

Academy of Finland

H2020 LEIT Information and Communication Technologies

Publisher

SAGE Publications

Subject

Physical Therapy, Sports Therapy and Rehabilitation,Biomedical Engineering,Immunology and Allergy

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