The Contribution of Bone and Cartilage to the Near-Infrared Spectrum of Osteochondral Tissue
The Contribution of Bone and Cartilage to the Near-Infrared Spectrum of Osteochondral Tissue
复制标题
DOI：
10.1366/13-07327
复制
发表时间：
2014-10-01
影响因子：
3.5
通讯作者：
Pleshko, Nancy
中科院分区：
文献类型：
--
作者：
McGoverin, Cushla M.;Lewis, Karl;Pleshko, Nancy
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，由于缺乏来自骨磷酸盐的NIR信号和辐射的相对深的穿透深度，软骨和骨对光谱特征的单独贡献尚未被很好地定义。本研究的目的是（1）提高对骨和软骨对从骨软骨组织获得的近红外光谱的贡献的理解和（2）评估这种非破坏性方法预测软骨厚度和人类胫骨平台关节软骨的改良Mankin等级的能力。近红外光谱是从不同厚度的牛骨和软骨样品以及从接受膝关节置换手术的患者中采集的22个胫骨平台获得的。从具有不同程度降解的胫骨平台区域记录光谱，并从组织学上评估这些区域的软骨厚度和改良的Mankin分级。研究了已知厚度的骨和软骨样品的光谱，以确定这两种组织不同的光谱区域。采用单变量和多变量线性回归方法将改良Mankin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光谱的比值是软骨和骨光谱的最佳区分因子。使用偏最小二乘回归计算的厚度和Mankin等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为0.42 mm（厚度）和1.3（修改后的Mankin等级）。我们的结论是，近红外光谱可用于同时评估关节软骨厚度和修改的Mankin等级，部分基于骨和软骨的光谱贡献的差异。
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.