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首页> 外文期刊>Osteoarthritis and cartilage >Near-infrared spectroscopy enables quantitative evaluation of human cartilage biomechanical properties during arthroscopy
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Near-infrared spectroscopy enables quantitative evaluation of human cartilage biomechanical properties during arthroscopy

机译：近红外光谱能够在关节镜检查中进行人体软骨生物力学特性的定量评估

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Objective: To investigate the feasibility of near-infrared (NIR) spectroscopy (NIRS) for evaluation of human articular cartilage biomechanical properties during arthroscopy. Design: A novel arthroscopic NIRS probe designed in our research group was utilized by an experienced orthopedic surgeon to measure NIR spectra from articular cartilage of human cadaver knee joints (ex vivo, n = 18) at several measurement locations during an arthroscopic surgery. Osteochondral samples (n = 265) were extracted from the measurement sites for reference analysis. NIR spectra were remeasured in a controlled laboratory environment (in vitro), after which the corresponding cartilage thickness and biomechanical properties were determined. Hybrid multivariate regression models based on principal component analysis and linear mixed effects modeling (PCA-LME) were utilized to relate cartilage in vitro spectra and biomechanical properties, as well as to account for the spatial dependency. Additionally, a k-nearest neighbors (kNN) classifier was employed to reject outlying ex vivo NIR spectra resulting from a non-optimal probe-cartilage contact. Model performance was evaluated for both in vitro and ex vivo NIR spectra via Spearman's rank correlation (ρ) and the ratio of performance to interquartile range (RPIQ). Results: Regression models accurately predicted cartilage thickness and biomechanical properties from in vitro NIR spectra (Model: 0.77 < =ρ< = 0.87, 2.03 < RPIQ< =3.0; Validation: 0.74 < = ρ < =0.84,1.87 < =RPIQ < 2.90). When predicting cartilage properties from ex vivo NIR spectra (0.33 < =ρ < =0.57 and 1.02 < =RPIQ < =2.14), a kNN classifier enhanced the accuracy of predictions (0.52 < = ρ< =0.87 and 1.06 < =RPIQ < =1.88). Conclusion: Arthroscopic NIRS could substantially enhance identification of damaged cartilage by enabling quantitative evaluation of cartilage biomechanical properties. The results demonstrate the capacity of NIRS in clinical applications.
机译：目的：探讨近红外（NIR）光谱（NIRS）对关节镜检查人关节软骨生物力学性质评价的可行性。设计：在我们的研究组中设计的一种新型关节镜NIRS探针，经历了经验丰富的整形外科医生，以在关节镜手术期间在几个测量位置测量人们尸体软骨（例如人尸体膝关节（离体N = 18）的关节软骨。从测量部位提取骨色素样品（n = 265）以进行参考分析。在受控实验室环境（体外）中测量NIR光谱，之后测定相应的软骨厚度和生物力学性质。利用基于主成分分析和线性混合效应建模（PCA-LME）的混合多变量回归模型（PCA-LME），以涉及软骨体外谱和生物力学特性，以及对空间依赖性的算法。另外，采用K最近邻居（KNN）分类器来拒绝由非最佳探针 - 软骨接触引起的偏远导致的离体NIR光谱。通过Spearman的等级相关性（ρ）和术语比例对体外和前体内NIR光谱进行评估模型性能，以及对整形范围（RPIQ）的性能之比。结果：回归模型精确预测来自体外NIR光谱的软骨厚度和生物力学性质（型号：0.77 <ρ<= 0.87，2.03

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