SERS光谱对肾结石患者尿液的无标记检测

Label-free Detection of Urine from Patients with Kidney Stones by SERS spectroscopy

近年来,肾结石的发病率逐渐升高,严重影响了患者的生活质量。因此,有必要开发一种强大的肾结石患者筛查技术。本文采用表面增强拉曼散射(SERS)技术对24例肾结石患者尿液和16例正常志愿者尿液进行检测,并成功记录了其光谱。同时分析两组SERS光谱的差谱,表明两组尿液在SERS光谱上存在细微但不可忽略的差异。利用主成分分析(PCA)算法考察两组SERS光谱中多个变量的相关性从而降维,并结合线性判别分析(LDA)算法区分正常人尿液样本和肾结石患者尿液样本,结果表明灵敏度和特异性分别为88%和81%。最后,计算受试者工作特征(ROC)曲线的面积为0.94,进一步证明了基于PCA-LDA诊断算法的有效性.

In recent years,the incidence rate of renal calculi has gradually increased,which has a significant impact on the quality of life of patients.Therefore,it is necessary to develop a powerful technique for analysis.In this paper,we used a method of surface enhanced Raman scatting(SERS)to detect the 24 renal-calculi patients'urine and 16 normal human urine,and successfully recorded their spectra.Simultaneous analysis of the difference spectrum of the two sets of SERS spectra shows that there are subtle but not negligible differences in the SERS spectra of the two sets of urine.And use the principal component analysis(PCA)algorithm to investigate the correlation of multiple variables in the two sets of SERS spectra,thereby reducing the dimensionality,combined with the linear discriminant analysis(LDA)algorithm to differentiate normal samples and patients'samples,the sensitivity and specificity are 88%and 81%,respectively.Finally,the area under the receiver operating characteristic(ROC)curve is 0.94,which further proves the validity of based on the PCA-LDA diagnostic algorithm.