1 Experimental Rheumatology Unit, Department of Orthopedics, Jena University Hospital, Waldkrankenhaus "Rudolf Elle", Eisenberg, Germany.
2 fzmb GmbH, Research Centre for Medical Technology and Biotechnology, Bad Langensalza, Germany.
Cartilage. 2019 Apr;10(2):173-185. doi: 10.1177/1947603517731851. Epub 2017 Oct 5.
The suitability of near-infrared spectroscopy (NIRS) for non-destructive measurement of cartilage thickness was compared with the gold standard needle indentation. A combination of NIRS and biomechanical indentation (NIRS-B) was used to address the influence of varying loads routinely applied for hand-guided NIRS during real-life surgery on the accuracy of NIRS-based thickness prediction. NIRS-B was performed under three different loading conditions in 40 osteochondral cylinders from the load-bearing area of the medial and lateral femur condyle of 20 cadaver joints (left stifle joints; female Merino sheep; 6.1 ± 0.6 years, mean ± standard error of the mean). The cartilage thickness measured by needle indentation within the region analyzed by NIRS-B was then compared with cartilage thickness prediction based on NIRS spectral data using partial least squares regression. NIRS-B repeat measurements yielded highly reproducible values concerning force and absorbance. Separate or combined models for the three loading conditions (the latter simulating load-independent measurements) resulted in models with optimized quality parameters (e.g., coefficients of determination R between 92.3 and 94.7) and a prediction accuracy of < 0.1 mm. NIRS appears well suited to determine cartilage thickness (possibly in a hand-guided, load-independent fashion), as shown by high reproducibility in repeat measurements and excellent reliability compared with tissue-destructive needle indentation. This may provide the basis for non-destructive, intra-operative assessment of cartilage status quo and fine-tuning of repair procedures.
近红外光谱(NIRS)在非破坏性测量软骨厚度方面的适用性与金标准针压痕进行了比较。使用 NIRS 和生物力学压痕的组合(NIRS-B)来解决在实际手术中进行手引导 NIRS 时经常施加的不同负荷对基于 NIRS 的厚度预测准确性的影响。NIRS-B 在 20 个尸体关节(左侧膝关节;雌性美利奴羊;6.1±0.6 岁,平均值±平均值的标准误差)的内侧和外侧股骨髁负重区的 40 个骨软骨圆柱体在三种不同的加载条件下进行。然后,将通过 NIRS-B 分析区域内的针压痕测量的软骨厚度与基于 NIRS 光谱数据的软骨厚度预测进行比较,使用偏最小二乘回归。NIRS-B 的重复测量在力和吸收率方面产生了高度可重复的值。三种加载条件的单独或组合模型(后者模拟独立于负载的测量)产生了具有优化质量参数的模型(例如,决定系数 R 在 92.3 和 94.7 之间),并且预测精度<0.1 毫米。NIRS 似乎非常适合确定软骨厚度(可能以手引导、独立于负载的方式),这从重复测量的高可重复性和与组织破坏性针压痕相比的出色可靠性中得到证明。这可能为非破坏性、术中评估软骨现状和修复程序的微调提供基础。