I Afara1, I Prasadam, R Crawford, Y Xiao, A Oloyede. 1. School of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia.
Abstract
OBJECTIVE: The aim of this study was to demonstrate the potential of near-infrared (NIR) spectroscopy for categorizing cartilage degeneration induced in animal models. METHOD: Three models of osteoarthritic degeneration were induced in laboratory rats via one of the following methods: (1) menisectomy (MSX); (2) anterior cruciate ligament transection (ACLT); and (3) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group. After 8 weeks, the animals were sacrificed and tibial knee joints were collected. A custom-made near-infrared (NIR) probe of diameter 5 mm was placed on the cartilage surface and spectral data were acquired from each specimen in the wave number range 4,000-12,500 cm(-1). Following spectral data acquisition, the specimens were fixed and Safranin-O staining was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis based on principal component analysis and partial least squares regression, the spectral data were then related to the Mankin scores of the samples tested. RESULTS: Mild to severe degenerative cartilage changes were observed in the subject animals. The ACLT models showed mild cartilage degeneration, MSX models moderate, and MIA severe cartilage degenerative changes both morphologically and histologically. Our result demonstrates that NIR spectroscopic information is capable of separating the cartilage samples into different groups relative to the severity of degeneration, with NIR correlating significantly with their Mankin score (R(2) = 88.85%). CONCLUSION: We conclude that NIR is a viable tool for evaluating articular cartilage health and physical properties such as change in thickness with degeneration.
OBJECTIVE: The aim of this study was to demonstrate the potential of near-infrared (NIR) spectroscopy for categorizing cartilage degeneration induced in animal models. METHOD: Three models of osteoarthritic degeneration were induced in laboratory rats via one of the following methods: (1) menisectomy (MSX); (2) anterior cruciate ligament transection (ACLT); and (3) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group. After 8 weeks, the animals were sacrificed and tibial knee joints were collected. A custom-made near-infrared (NIR) probe of diameter 5 mm was placed on the cartilage surface and spectral data were acquired from each specimen in the wave number range 4,000-12,500 cm(-1). Following spectral data acquisition, the specimens were fixed and Safranin-O staining was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis based on principal component analysis and partial least squares regression, the spectral data were then related to the Mankin scores of the samples tested. RESULTS: Mild to severe degenerative cartilage changes were observed in the subject animals. The ACLT models showed mild cartilage degeneration, MSX models moderate, and MIA severe cartilage degenerative changes both morphologically and histologically. Our result demonstrates that NIR spectroscopic information is capable of separating the cartilage samples into different groups relative to the severity of degeneration, with NIR correlating significantly with their Mankin score (R(2) = 88.85%). CONCLUSION: We conclude that NIR is a viable tool for evaluating articular cartilage health and physical properties such as change in thickness with degeneration.
Authors: Isaac O Afara; Rubina Shaikh; Ervin Nippolainen; William Querido; Jari Torniainen; Jaakko K Sarin; Shital Kandel; Nancy Pleshko; Juha Töyräs Journal: Nat Protoc Date: 2021-01-18 Impact factor: 13.491
Authors: Iman Kafian-Attari; Ervin Nippolainen; Dmitry Semenov; Markku Hauta-Kasari; Juha Töyräs; Isaac O Afara Journal: Biomed Opt Express Date: 2020-10-19 Impact factor: 3.732
Authors: Stephanie Tatjana Stumpfe; Julia Karin Pester; Susanne Steinert; Ivan Marintschev; Holger Plettenberg; Matthias Aurich; Gunther Olaf Hofmann Journal: Muscles Ligaments Tendons J Date: 2013-08-11