Abstract
AbstractOsteoarthritis degenerates cartilage and impairs joint function. Early intervention opportunities are missed as current diagnostic methods are insensitive to early tissue degeneration. We investigated the capability of visible light-near-infrared spectroscopy (Vis-NIRS) to differentiate normal human cartilage from early osteoarthritic one. Vis-NIRS spectra, biomechanical properties and the state of osteoarthritis (OARSI grade) were quantified from osteochondral samples harvested from different anatomical sites of human cadaver knees. Two support vector machines (SVM) classifiers were developed based on the Vis-NIRS spectra and OARSI scores. The first classifier was designed to distinguish normal (OARSI: 0–1) from general osteoarthritic cartilage (OARSI: 2–5) to check the general suitability of the approach yielding an average accuracy of 75% (AUC = 0.77). Then, the second classifier was designed to distinguish normal from early osteoarthritic cartilage (OARSI: 2–3) yielding an average accuracy of 71% (AUC = 0.73). Important wavelength regions for differentiating normal from early osteoarthritic cartilage were related to collagen organization (wavelength region: 400–600 nm), collagen content (1000–1300 nm) and proteoglycan content (1600–1850 nm). The findings suggest that Vis-NIRS allows objective differentiation of normal and early osteoarthritic tissue, e.g., during arthroscopic repair surgeries.
Funder
Academy of Finland
Sigrid Juséliuksen Säätiö
Strategic Funding of the University of Eastern Finland
Keski-Suomen Rahasto
Maire Lisko Foundation
Emil Aaltonen Foundation
Orionin Tutkimussäätiö
Saastamoisen säätiö
Alfred Kordelinin Säätiö
University of Eastern Finland (UEF) including Kuopio University Hospital
Publisher
Springer Science and Business Media LLC
Cited by
5 articles.
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