State Key Laboratory of PPTHIDCA/Department of Gynecology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China.
College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China.
Lasers Med Sci. 2021 Dec;36(9):1855-1864. doi: 10.1007/s10103-020-03218-5. Epub 2021 Jan 6.
Early detection of cervical lesions, accurate diagnosis of cervical lesions, and timely and effective therapy can effectively avoid the occurrence of cervical cancer or improve the survival rate of patients. In this paper, the spectra of tissue sections of cervical inflammation (n = 60), CIN (cervical intraepithelial neoplasia) I (n = 30), CIN II (n = 30), CIN III (n = 30), cervical squamous cell carcinoma (n = 30), and cervical adenocarcinoma (n = 30) were collected by a confocal Raman micro-spectrometer (LabRAM HR Evolution, Horiba France SAS, Villeneuve d'Ascq, France). The Raman spectra of six kinds of cervical tissues were analyzed, the dominant Raman peaks of different kinds of tissues were summarized, and the differences in chemical composition between the six tissue samples were compared. An independent sample t test (p ≤ 0.05) was used to analyze the difference of average relative intensity of Raman spectra of six types of cervical tissues. The difference of relative intensity of Raman spectra of six kinds of tissues can reflect the difference of biochemical components in six kinds of tissues and the characteristic of biochemical components in different kinds of tissues. The classification models of cervical inflammation, CIN I, CIN II, CIN III, cervical squamous cell carcinoma, and cervical adenocarcinoma were established by using a support vector machine (SVM) algorithm. Six types of cervical tissues were classified and identified with an overall diagnostic accuracy of 85.7%. This study laid a foundation for the application of Raman spectroscopy in the clinical diagnosis of cervical precancerous lesions and cervical cancer.
早期发现宫颈病变、准确诊断宫颈病变、及时有效治疗，可以有效避免宫颈癌的发生，或提高患者的生存率。本文采用共聚焦激光拉曼光谱仪（LabRAM HR Evolution，Horiba France SAS，Villeneuve d'Ascq，France）采集宫颈炎症组织切片（n=60）、CIN I（宫颈上皮内瘤变 I，n=30）、CIN II（n=30）、CIN III（n=30）、宫颈鳞状细胞癌（n=30）、宫颈腺癌（n=30）的光谱。分析 6 种宫颈组织的拉曼光谱，总结不同组织的特征拉曼峰，比较 6 种组织样本的化学成分差异。采用独立样本 t 检验（p≤0.05）分析 6 种宫颈组织的平均相对强度拉曼光谱差异。6 种组织的相对强度拉曼光谱差异可以反映 6 种组织生化成分的差异及不同组织生化成分的特征。利用支持向量机（SVM）算法建立宫颈炎症、CIN I、CIN II、CIN III、宫颈鳞状细胞癌、宫颈腺癌的分类模型。6 种宫颈组织分类识别的总诊断准确率为 85.7%。本研究为拉曼光谱在宫颈癌前病变及宫颈癌的临床诊断中的应用奠定了基础。
