Song Dongliang, Yu Fan, Chen Shilin, Chen Yishen, He Qingli, Zhang Zhe, Zhang Jingyuan, Wang Shuang
Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, 710069, China.
Department of physics, Northwest University, Xi'an, Shaanxi, 710069, China.
Biomed Opt Express. 2020 Jan 23;11(2):1061-1072. doi: 10.1364/BOE.383869. eCollection 2020 Feb 1.
Lung cancer is the leading cause of death in cancer patients, and microwave ablation (MWA) has been extensively used in clinical treatment. In this study, we characterized the spectra of MWA-treated and untreated lung squamous cell carcinoma (LSCC) tissues, as well as healthy lung tissue, and conducted a preliminary analysis of spectral variations associated with MWA treatment. The results of characteristic spectral analysis of different types of tissues indicated that MWA treatment induces an increase in the content of nucleic acids, proteins, and lipid components in lung cancer tissues. The discriminant model based on the principal component analysis - linear discriminant analysis (PCA-LDA) algorithm together with leave-one-out cross validation (LOOCV) method yield the sensitivities of 90%, 80%, and 96%, and specificities of 86.2%, 93.8%, and 100% among untreated and MWA-treated cancerous tissue, and healthy lung tissue, respectively. These results indicate that Raman spectroscopy combined with multivariate analysis techniques can be used to explore the biochemical response mechanism of cancerous tissue to MWA therapy.
肺癌是癌症患者死亡的主要原因，微波消融（MWA）已在临床治疗中广泛应用。在本研究中，我们对微波消融治疗和未治疗的肺鳞状细胞癌（LSCC）组织以及健康肺组织的光谱进行了表征，并对与微波消融治疗相关的光谱变化进行了初步分析。不同类型组织的特征光谱分析结果表明，微波消融治疗会导致肺癌组织中核酸、蛋白质和脂质成分含量增加。基于主成分分析-线性判别分析（PCA-LDA）算法并结合留一法交叉验证（LOOCV）方法的判别模型，在未治疗和微波消融治疗的癌组织以及健康肺组织中的灵敏度分别为90%、80%和96%，特异性分别为86.2%、93.8%和100%。这些结果表明，拉曼光谱结合多变量分析技术可用于探索癌组织对微波消融治疗的生化反应机制。
