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Raman spectroscopic study and identification of multi-period osteoarthritis of canine knee joint
Applied Physics B ( IF 2.1 ) Pub Date : 2020-11-25 , DOI: 10.1007/s00340-020-07549-7
Lin-Wei Shang , Juan-Juan Fu , Dan-Ying Ma , Yuan Zhao , Bao-Kun Huang , Jian-Hua Yin

A home-made small-sized Raman spectrometer combined with machine learning algorithms was used to study and identify healthy and multi-period osteoarthritis (OA) canine knee joints. Nine canines were equally divided into three groups according to the post-operative (OA modeling) time of 2-month, 3-month and 7-month. Other two normal canines were used as control. It was found that the degeneration degree of cartilage was positively correlated with post-operative time by doing anatomical analysis. The mixed Raman spectra of cartilage and subchondral bone were collected and analyzed, which reveals subchondral bone demineralization and carbonate ion substituting into the apatite mineral during OA. Raman spectra combined with principal component analysis (PCA) further disclosed that collagen matrix became unordered, both content ratios of amide I/matrix and phenylalanine/matrix in OA cartilage and subchondral bone increased. Based on the PCA getting five principal components, all groups were effectively discriminated by Fisher discriminant analysis (FDA) with high accuracy of 91.07% for the validation set, as well as 95.45% for the test set. It suggests that Raman spectroscopy combined with machine learning is capable to become an effective tool to achieve in situ identification of multi-period OA with high accuracy and preclinical significance.

中文翻译:

犬膝关节多期骨关节炎的拉曼光谱研究与鉴定

使用自制的小型拉曼光谱仪结合机器学习算法对健康多期骨关节炎(OA)犬膝关节进行研究和鉴定。9只犬根据术后2个月、3个月和7个月的时间(OA建模)平均分为三组。其他两只正常犬用作对照。通过解剖分析发现,软骨退变程度与术后时间呈正相关。收集并分析软骨和软骨下骨的混合拉曼光谱,揭示了 OA 过程中软骨下骨脱矿和碳酸根离子取代磷灰石矿物。拉曼光谱结合主成分分析(PCA)进一步揭示胶原基质变得无序,OA软骨和软骨下骨中酰胺I/基质和苯丙氨酸/基质的含量比均增加。基于得到五个主成分的 PCA,所有组都被 Fisher 判别分析 (FDA) 有效区分,验证集的准确率为 91.07%,测试集的准确率为 95.45%。这表明拉曼光谱结合机器学习能够成为实现多周期OA原位识别的有效工具,具有高精度和临床前意义。
更新日期:2020-11-25
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