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Sci Data. 2019 Aug 30;6(1):164. doi: 10.1038/s41597-019-0170-y.

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

Author information

1
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland. jaakko.sarin@uef.fi.
2
Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland. jaakko.sarin@uef.fi.
3
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland. jari.torniainen@uef.fi.
4
Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland. jari.torniainen@uef.fi.
5
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
6
Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland.
7
A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.
8
Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland.
9
School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia.

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.

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