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Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue

机译:胃中近红外拉曼光谱的诊断潜能:将发育异常与正常组织区分开

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Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with diseased transformation. The purpose of this study was to explore near-infrared (NIR) Raman spectroscopy for identifying dysplasia from normal gastric mucosa tissue. A rapid-acquisition dispersive-type NIR Raman system was utilised for tissue Raman spectroscopic measurements at 785?nm laser excitation. A total of 76 gastric tissue samples obtained from 44 patients who underwent endoscopy investigation or gastrectomy operation were used in this study. The histopathological examinations showed that 55 tissue specimens were normal and 21 were dysplasia. Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues. High-quality Raman spectra in the range of 800–1800?cm?1 can be acquired from gastric tissue within 5?s. There are specific spectral differences in Raman spectra between normal and dysplasia tissue, particularly in the spectral ranges of 1200–1500?cm?1 and 1600–1800?cm?1, which contained signals related to amide III and amide I of proteins, CH3CH2 twisting of proteinsucleic acids, and the C=C stretching mode of phospholipids, respectively. The empirical diagnostic algorithm based on the ratio of the Raman peak intensity at 875?cm?1 to the peak intensity at 1450?cm?1 gave the diagnostic sensitivity of 85.7% and specificity of 80.0%, whereas the diagnostic algorithms based on PCA-LDA yielded the diagnostic sensitivity of 95.2% and specificity 90.9% for separating dysplasia from normal gastric tissue. Receiver operating characteristic (ROC) curves further confirmed that the most effective diagnostic algorithm can be derived from the PCA-LDA technique. Therefore, NIR Raman spectroscopy in conjunction with multivariate statistical technique has potential for rapid diagnosis of dysplasia in the stomach based on the optical evaluation of spectral features of biomolecules.
机译:拉曼光谱是一种分子振动光谱技术,能够光学探测与病变转化相关的生物分子变化。这项研究的目的是探索近红外(NIR)拉曼光谱,以鉴定正常胃粘膜组织的异常增生。快速采集的分散型近红外拉曼系统用于在785?nm激光激发下的组织拉曼光谱测量。从44例接受内窥镜检查或胃切除术的患者中获得的总共76份胃组织样本用于本研究。组织病理学检查显示55例组织标本正常,21例为不典型增生。经验方法和多元统计技术,包括主成分分析(PCA)和线性判别分析(LDA),以及留一样本交叉验证方法,均被用于开发有效的诊断算法,用于分类正常胃和增生胃组织之间的拉曼光谱。可以在5?s内从胃组织获取800-1800?cm?1范围内的高质量拉曼光谱。正常组织和不典型增生组织之间的拉曼光谱存在特定的光谱差异,特别是在1200–1500?cm?1和1600–1800?cm?1的光谱范围内,其中包含与蛋白质CH3CH2的酰胺III和酰胺I有关的信号蛋白质/核酸的扭曲,以及磷脂的C = C拉伸模式。基于875?cm?1的拉曼峰强度与1450?cm?1的峰强度之比的经验诊断算法给出的诊断灵敏度为85.7%,特异性为80.0%,而基于PCA-LDA对将异常增生与正常胃组织分离的诊断灵敏度为95.2%,特异性为90.9%。接收器工作特性(ROC)曲线进一步证实,最有效的诊断算法可以从PCA-LDA技术中得出。因此,基于生物分子光谱特征的光学评估,结合多变量统计技术的近红外拉曼光谱技术具有快速诊断胃异型增生的潜力。

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