Dataset on equine cartilage near infrared spectra, composition, and functional properties

Abstract

Near infrared (NIR) spectroscopy is a well-established technique that is widely employed in agriculture, chemometrics, and pharmaceutical engineering. Recently, the technique has shown potential in clinical orthopaedic applications, for example, assisting in the diagnosis of various knee-related diseases ( e . g ., osteoarthritis) and their pathologies. NIR spectroscopy (NIRS) could be especially useful for determining the integrity and condition of articular cartilage, as the current arthroscopic diagnostics is subjective and unreliable. In this work, we present an extensive dataset of NIRS measurements for evaluating the condition, mechanical properties, structure, and composition of equine articular cartilage. The dataset contains NIRS measurements from 869 different locations across the articular surfaces of five equine fetlock joints. A comprehensive library of reference values for each measurement location is also provided, including results from a mechanical indentation testing, digital densitometry imaging, polarized light microscopy, and Fourier transform infrared spectroscopy. The published data can either be used as a model of human cartilage or to advance equine veterinary research.

Deciphering pathological remodelling of the human cartilage extracellular matrix in osteoarthritis at the supramolecular level

“…characterization techniques, including infrared 16 and nearinfrared spectroscopy, 17 second harmonic generation 18 and Raman spectroscopy, 19 can be used to probe the cartilage ECM. However, all these techniques can only probe changes in a semi-quantitative way.…”

“…Indeed, common procedures are based on biochemical methods, which require the digestion of the tissue, so that the global supramolecular structure is not preserved. As an alternative, immunohistology, or other label-free characterization techniques, including infrared 16 and near-infrared spectroscopy, 17 second harmonic generation 18 and Raman spectroscopy, 19 can be used to probe the cartilage ECM. However, all these techniques can only probe changes in a semi-quantitative way.…”

Vibrational Spectroscopy in Assessment of Early Osteoarthritis—A Narrative Review

“…Their study indicated that the SVM model can distinguish anterior cruciate ligament transection (ACLT) from non-operationally operated control (CNTRL) samples, the DNN model can discriminate between different types of OA, and LR can differentiate between contralateral (CL) and CNTRL samples. NIR spectroscopy, in combination with machine learning techniques, can provide a powerful tool for the classification of cartilage integrity [ 71 ], with the potential to accurately distinguish between normal and early osteoarthritic cartilage [ 72 , 73 ].…”

Model Averaging Estimation for Partially Linear Functional Score Models

“…This data set 3 contains NIR spectroscopy measurements (functional predictor X) within the spectrum region of 700-1050 nm from 869 different locations across the articular surfaces of five equine fetlock joints, paired with comprehensive reference measurements from biomechanics, chemical composition and internal structure of the tissue, such as, instantaneous moduli (Y ), collagen contents (Z 1 ), proteoglycan contents (Z 2 ), cartilage thickness (Z 3 ), and calcified layer thickness (Z 4 ), etc. More details are available [30]. The sample data with size 530 were retained after removing all incomplete records.…”