Background: Osteoarthritis (OA), a degenerative cartilage disease, results in alterations of the chemical and structural properties of tissue. Arthroscopic evaluation of full-depth tissue composition is limited and would require tissue harvesting, which is inappropriate in daily routine. Fourier transform infrared (FT-IR) spectroscopy is a modality based on molecular vibrations of matrix components that can be used in conjunction with fiber optics to acquire quantitative compositional data from the cartilage matrix.
Purpose: To develop a model based on infrared spectra of articular cartilage to predict the histological Mankin score as an indicator of tissue quality.
Study design: Comparative laboratory study.
Methods: Infrared fiber optic probe (IFOP) spectra were collected from nearly normal and more degraded regions of tibial plateau articular cartilage harvested during knee arthroplasty (N = 61). Each region was graded using a modified Mankin score. A multivariate partial least squares algorithm using second-derivative spectra was developed to predict the histological modified Mankin score.
Results: The partial least squares model derived from IFOP spectra predicted the modified Mankin score with a prediction error of approximately 1.4, which resulted in approximately 72% of the Mankin-scored tissues being predicted correctly and 96% being predicted within 1 grade of their true score.
Conclusion: These data demonstrate that IFOP spectral parameters correlate with histological tissue grade and can be used to provide information on tissue composition.
Clinical relevance: Infrared fiber optic probe studies have significant potential for the evaluation of cartilage tissue quality without the need for tissue harvest. Combined with arthroscopy, IFOP analysis could facilitate the definition of tissue margins in debridement procedures.