Wang Jing, Li Liang, Yang Ping, Chen Ying, Zhu Yining, Tong Ming, Hao Zhongqi, Li Xiangyou
Wuhan General Hospital of Guangzhou Military Command, Wuhan, 430074, Hubei, People's Republic of China.
Wuhan National Laboratory for Optoelectronics(WNLO), Huazhong University of Science and Technology(HUST), Wuhan, 430074, Hubei, People's Republic of China.
Lasers Med Sci. 2018 Aug;33(6):1381-1386. doi: 10.1007/s10103-018-2500-2. Epub 2018 Jun 26.
Cervical cancer is one of the most widespread diseases in women. Traditional cancer diagnosis is extremely complicated and relies on subjective interpretation of biopsy material. In this work, laser-induced breakdown spectroscopy (LIBS) was used in cervical cancer recognition. In order to improve identification accuracy of cervical cancer by LIBS, the chemometric methods of principal component analysis (PCA) and support vector machine (SVM) were combined. The results show that the content of trace elements in normal tissues and cervical cancer tissues was significantly different. Normalized peak intensities of Na, Mg, and K in the cervical cancer tissues were significantly higher than normal tissues, and the normalized peak intensities of Ca in the normal tissues were higher than cervical cancer tissues. The identification accuracies of PCA-SVM are better than SVM, with the achieved accuracies of 94.44% and 93.06%, respectively. It can be concluded that LIBS techniques coupled with chemometric method is a potential in cancer tissue identification, which provides a preliminary research basis for real-time diagnosis of cancer tissues using LIBS.
宫颈癌是女性中最普遍的疾病之一。传统的癌症诊断极其复杂，且依赖于对活检材料的主观解读。在这项工作中，激光诱导击穿光谱技术（LIBS）被用于宫颈癌识别。为了提高LIBS对宫颈癌的识别准确率，主成分分析（PCA）和支持向量机（SVM）这两种化学计量学方法被结合使用。结果表明，正常组织和宫颈癌组织中的微量元素含量存在显著差异。宫颈癌组织中Na、Mg和K的归一化峰值强度显著高于正常组织，而正常组织中Ca的归一化峰值强度高于宫颈癌组织。PCA-SVM的识别准确率优于SVM，分别达到了94.44%和93.06%。可以得出结论，LIBS技术与化学计量学方法相结合在癌症组织识别方面具有潜力，这为使用LIBS进行癌症组织的实时诊断提供了初步的研究基础。
