关节滑液傅里叶变换红外光谱在颞下颌关节疾病诊断中的应用

Application of synovial fluid-based Fourier transform infrared spectroscopy for a diagnosis of temporomandibular joint disease

摘要:

目的： 利用傅里叶变换红外光谱（Fourier transform infrared spectroscopy，FTIR）技术对人颞下颌关节液（synovial fluid，SF）样本进行分析，以探究FTIR技术在颞下颌关节疾病诊断及鉴别诊断中的应用价值。方法： 共收集115例颞下颌关节滑液样本：正常组15例，不可复性关节盘移位（anterior disc displacement without renaturation，ADDWR）32例，颞下颌关节骨关节病（temporomandibular joint osteoarthritis，TMJOA）41例，特发性髁突吸收（idiopathic condyle absorption，ICR）27例。采集SF样本红外光谱数据。采用主成分分析（principal component analysis，PCA）对各组样本进行区分，偏最小二乘法判别（partial least squares-discriminate analysis，PLS-DA）建立预测模型并对预测效力进行评估。结果： 通过PCA，TMJOA、ICR均能与正常关节液显著区分，而ADDWR和正常关节液成分非常相似。组间差异主要体现在PC1载荷中3 386 cm^-1、2 943 cm^-1、2 912 cm^-1、1 682 cm^-1、1 537 cm^-1、1 468 cm^-1等附近吸收峰上；通过PLS-DA，得到较为满意的预测结果：内部交叉验证正确率为90%，外部验证正确率为97%。结论： FTIR光谱技术结合化学计量方法对辅助颞下颌关节疾病临床诊断及鉴别诊断具有较大的潜力。

Abstract:

Objective: To analysis the temporomandibular joint synovial fluid (SF) sample by using Fourier transform infrared spectroscopy (FTIR) method, so as to investigate its application value in diagnosis and differential diagnosis among temporomandibular joint diseases. Methods: A total of 115 temporomandibular joint SF samples were collected, with 15 cases in the normal group, 32 cases of anterior disc displacement without renaturation (ADDWR), 41 cases of temporomandibular joint osteoarthritis (TMJOA), and 27 cases of idiopathic condyle absorption (ICR). Dry films were made from SF samples and principal component analysis (PCA) was used to separate samples from groups. A partial least squares-discriminate analysis (PLS-DA) was used to establish predictive model and evaluate predictive ability. Results: Based on the PCA results, TMJOA and ICR was able to be significantly distinguished from ADDWR and normal SF samples. Components in ADDWR and normal SF samples were similar. In PC1 loading, the main differentiated absorption peaks sited around 3 386 cm^-1, 2 943 cm^-1, 2 912 cm^-1, 1 682 cm^-1, 1 537 cm^-1and 1 468 cm^-1. Through partial least squares-discriminant analysis, a satisfactory prediction result was obtained. The internal cross-validation accuracy was 90%, and the external validation classification accuracy was 97%. Conclusion: FTIR spectroscopy combined with appropriate stoichiometry has great potential for assisting the clinical diagnosis and differential diagnosis of temporomandibular joint disease.