McGoverin Cushla M, Lewis Karl, Yang Xu, Bostrom Mathias P G, Pleshko Nancy
Temple University, Department of Bioengineering, College of Engineering, 1947 North 12th Street, Philadelphia, PA 19122 USA.
Appl Spectrosc. 2014;68(10):1168-75. doi: 10.1366/13-07327. Epub 2014 Oct 1.
Near-infrared (NIR) spectroscopy has been used to assess hyaline cartilage quality in human and animal osteochondral tissues. However, due to the lack of NIR signal from bone phosphate and the relatively deep penetration depth of the radiation, the separate contributions of cartilage and bone to the spectral signatures have not been well defined. The objectives of the current study were (1) to improve the understanding of the contributions of bone and cartilage to NIR spectra acquired from osteochondral tissue and (2) to assess the ability of this nondestructive method to predict cartilage thickness and modified Mankin grade of human tibial plateau articular cartilage. Near-infrared spectra were acquired from samples of bovine bone and cartilage with varying thicknesses and from 22 tibial plateaus harvested from patients undergoing knee replacement surgery. The spectra were recorded from regions of the tibial plateaus with varying degrees of degradation, and the cartilage thickness and modified Mankin grade of these regions were assessed histologically. The spectra from bone and cartilage samples of known thicknesses were investigated to identify spectral regions that were distinct for these two tissues. Univariate and multivariate linear regression methods were used to correlate modified Mankin grade and cartilage thickness with NIR spectral changes. The ratio of the NIR absorbances associated with water at 5270 and 7085 cm(-1) was the best differentiator of cartilage and bone spectra. The NIR prediction models for thickness and Mankin grade calculated using partial least squares regression were more accurate than were univariate-based prediction models, with a root mean square errors of cross-validation of 0.42 mm (for thickness) and 1.3 (for modified Mankin grade). We conclude that NIR spectroscopy may be used to simultaneously assess articular cartilage thickness and modified Mankin grade, based in part on differences in spectral contributions from bone and cartilage.
近红外(NIR)光谱已被用于评估人类和动物骨软骨组织中的透明软骨质量。然而,由于骨磷酸盐缺乏近红外信号以及辐射相对较深的穿透深度,软骨和骨对光谱特征的单独贡献尚未得到很好的界定。本研究的目的是:(1)增进对骨和软骨对从骨软骨组织获取的近红外光谱贡献的理解;(2)评估这种无损方法预测人类胫骨平台关节软骨厚度和改良曼金分级的能力。从不同厚度的牛骨和软骨样本以及从接受膝关节置换手术患者身上获取的22个胫骨平台采集近红外光谱。从胫骨平台不同程度退变的区域记录光谱,并通过组织学评估这些区域的软骨厚度和改良曼金分级。研究已知厚度的骨和软骨样本的光谱,以确定这两种组织不同的光谱区域。使用单变量和多变量线性回归方法将改良曼金分级和软骨厚度与近红外光谱变化相关联。在5270和7085 cm⁻¹处与水相关的近红外吸光度之比是软骨和骨光谱的最佳区分指标。使用偏最小二乘法回归计算的厚度和曼金分级的近红外预测模型比基于单变量的预测模型更准确,交叉验证的均方根误差分别为0.42 mm(厚度)和1.3(改良曼金分级)。我们得出结论,近红外光谱可用于同时评估关节软骨厚度和改良曼金分级,部分基于骨和软骨光谱贡献的差异。