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.

Highlights

  • Background & SummaryOsteoarthritis (OA) is the most common musculoskeletal disorder[1], characterized by the deterioration of articular cartilage and subchondral bone

  • While the main focus of the dataset is in the development of NIR spectroscopy (NIRS) techniques for evaluating cartilage condition, the broad library of reference variables can be used to study the structure-function relationship of articular cartilage

  • The NIRS measurements combined with the structural and compositional properties of cartilage could, for instance, be used to model the interaction between Near infrared (NIR) light and articular cartilage in order to gain a better understanding of the sensitivity of the NIRS technique as a function of penetration depth

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Summary

Background & Summary

Osteoarthritis (OA) is the most common musculoskeletal disorder[1], characterized by the deterioration of articular cartilage and subchondral bone. To develop any of these techniques, large data library from human cadavers or suitable animal models (i.e., large mammals) is often required These datasets should consist of multiple cartilage samples with varying degrees of tissue defects. While the main focus of the dataset is in the development of NIRS techniques for evaluating cartilage condition, the broad library of reference variables can be used to study the structure-function relationship of articular cartilage. These functional, compositional, and structural properties could be utilized, for instance, in. The NIRS measurements combined with the structural and compositional properties of cartilage could, for instance, be used to model the interaction between NIR light and articular cartilage in order to gain a better understanding of the sensitivity of the NIRS technique as a function of penetration depth

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