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Near Infrared Spectroscopic Evaluation of Ligament and Tendon Biomechanical Properties

Overview of attention for article published in Annals of Biomedical Engineering, September 2018
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Title
Near Infrared Spectroscopic Evaluation of Ligament and Tendon Biomechanical Properties
Published in
Annals of Biomedical Engineering, September 2018
DOI 10.1007/s10439-018-02125-9
Pubmed ID
Authors

Jari Torniainen, Aapo Ristaniemi, Jaakko K. Sarin, Santtu Mikkonen, Isaac O. Afara, Lauri Stenroth, Rami K. Korhonen, Juha Töyräs

Abstract

Knee ligaments and tendons are collagen-rich viscoelastic connective tissues that provide vital mechanical stabilization and support to the knee joint. Deterioration of ligaments has an adverse effect on the health of the knee and can eventually lead to ligament rupture and osteoarthritis. In this study, the feasibility of near infrared spectroscopy (NIRS) was, for the first time, tested for evaluation of ligament and tendon mechanical properties by performing measurements on bovine stifle joint ligament (N = 40) and patellar tendon (N = 10) samples. The mechanical properties of the samples were determined using a uniaxial tensile testing protocol. Partial least squares regression models were then developed to determine if morphological, viscoelastic, and quasi-static properties of the samples could be predicted from the NIR spectra. Best performance of NIRS in predicting mechanical properties was observed for toughness at yield point (median [Formula: see text], median normalized [Formula: see text]), toughness at failure point (median [Formula: see text], median normalized [Formula: see text]), and the ultimate strength of the ligament/tendon (median [Formula: see text], median normalized [Formula: see text]). Thus, we show that NIRS is capable of estimating ligament and tendon biomechanical properties, especially in parameters related to tissue failure. We believe this method could substantially enhance the currently limited arthroscopic evaluation of ligaments and tendons.

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Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 14%
Student > Ph. D. Student 6 11%
Student > Doctoral Student 6 11%
Student > Master 6 11%
Student > Bachelor 4 7%
Other 9 16%
Unknown 17 30%
Readers by discipline Count As %
Engineering 7 13%
Medicine and Dentistry 6 11%
Sports and Recreations 6 11%
Physics and Astronomy 3 5%
Immunology and Microbiology 2 4%
Other 8 14%
Unknown 24 43%