ArticleApplied spectroscopy2014
The contribution of bone and cartilage to the near-infrared spectrum of osteochondral tissue.
Article in Applied spectroscopy, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Visible and near-infrared spectroscopic method for correlative joint tissue analysis and visual and histologic grading.MethodsX · 2026Article
- Evaluating Normalization Methods for Robust Spectral Performance Assessments of Hyperspectral Imaging Cameras.Biosensors · 2025Article
- Near-Infrared Spectroscopy Enables Arthroscopic Histologic Grading of Human Knee Articular Cartilage.Arthroscopy, sports medicine, and rehabilitation · 2022Article
- Article
- Applications of Vibrational Spectroscopy for Analysis of Connective Tissues.Molecules (Basel, Switzerland) · 2021Review
- Characterization of connective tissues using near-infrared spectroscopy and imaging.Nature protocols · 2021Article
- Wavelength weightings in machine learning for ovine joint tissue differentiation using diffuse reflectance spectroscopy (DRS).Biomedical optics express · 2020Article
- Dual-comb photoacoustic spectroscopy.Nature communications · 2020Article
- Non-Destructive Spectroscopic Assessment of High and Low Weight Bearing Articular Cartilage Correlates with Mechanical Properties.Cartilage · 2019Article
- Dataset on equine cartilage near infrared spectra, composition, and functional properties.Scientific data · 2019Article
- Arthroscopic near infrared spectroscopy enables simultaneous quantitative evaluation of articular cartilage and subchondral bone in vivo.Scientific reports · 2018Article
- Characterizing human subchondral bone properties using near-infrared (NIR) spectroscopy.Scientific reports · 2018Article
- Near-Infrared Spectroscopy Predicts Compositional and Mechanical Properties of Hyaluronic Acid-Based Engineered Cartilage Constructs.Tissue engineering. Part A · 2018Article
- Non-destructive NIR spectral imaging assessment of bone water: Comparison to MRI measurements.Bone · 2017Article
- Monitoring osteoarthritis progression using near infrared (NIR) spectroscopy.Scientific reports · 2017Article
- Characterization of Articular Cartilage Recovery and Its Correlation with Optical Response in the Near-Infrared Spectral Range.Cartilage · 2017Article
- Nondestructive Assessment of Engineered Cartilage Composition by Near Infrared Spectroscopy.Annals of biomedical engineering · 2016Article
- Article
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5 authors.
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Abstract
Near-infrared (NIR) spectroscopy has been used to assess hyaline cartilage quality in human and animal osteochondral tissues. However, due to the lack of NIR signal from bone phosphate and the relatively deep penetration depth of the radiation, the separate contributions of cartilage and bone to the spectral signatures have not been well defined. The objectives of the current study were (1) to improve the understanding of the contributions of bone and cartilage to NIR spectra acquired from osteochondral tissue and (2) to assess the ability of this nondestructive method to predict cartilage thickness and modified Mankin grade of human tibial plateau articular cartilage. Near-infrared spectra were acquired from samples of bovine bone and cartilage with varying thicknesses and from 22 tibial plateaus harvested from patients undergoing knee replacement surgery. The spectra were recorded from regions of the tibial plateaus with varying degrees of degradation, and the cartilage thickness and modified Mankin grade of these regions were assessed histologically. The spectra from bone and cartilage samples of known thicknesses were investigated to identify spectral regions that were distinct for these two tissues. Univariate and multivariate linear regression methods were used to correlate modified Mankin grade and cartilage thickness with NIR spectral changes. The ratio of the NIR absorbances associated with water at 5270 and 7085 cm(-1) was the best differentiator of cartilage and bone spectra. The NIR prediction models for thickness and Mankin grade calculated using partial least squares regression were more accurate than were univariate-based prediction models, with a root mean square errors of cross-validation of 0.42 mm (for thickness) and 1.3 (for modified Mankin grade). We conclude that NIR spectroscopy may be used to simultaneously assess articular cartilage thickness and modified Mankin grade, based in part on differences in spectral contributions from bone and cartilage.
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