Félix Maria M, Tavares Mariana V, Santos Inês P, Batista de Carvalho Ana L M, Batista de Carvalho Luís A E, Marques Maria Paula M
Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal.
Gynaecology Department, Portuguese Oncology Institute of Porto, 4200-072 Porto, Portugal.
Molecules. 2024 Feb 20;29(5):922. doi: 10.3390/molecules29050922.
Cervical cancer was considered the fourth most common cancer worldwide in 2020. In order to reduce mortality, an early diagnosis of the tumor is required. Currently, this type of cancer occurs mostly in developing countries due to the lack of vaccination and screening against the Human Papillomavirus. Thus, there is an urgent clinical need for new methods aiming at a reliable screening and an early diagnosis of precancerous and cancerous cervical lesions. Vibrational spectroscopy has provided very good results regarding the diagnosis of various tumors, particularly using Fourier transform infrared microspectroscopy, which has proved to be a promising complement to the currently used histopathological methods of cancer diagnosis. This spectroscopic technique was applied to the analysis of cryopreserved human cervical tissue samples, both squamous cell carcinoma (SCC) and non-cancer samples. A dedicated Support Vector Machine classification model was constructed in order to categorize the samples into either normal or malignant and was subsequently validated by cross-validation, with an accuracy higher than 90%.
2020年，宫颈癌被认为是全球第四大常见癌症。为了降低死亡率，需要对肿瘤进行早期诊断。目前，由于缺乏针对人乳头瘤病毒的疫苗接种和筛查，这种类型的癌症大多发生在发展中国家。因此，临床上迫切需要新的方法来可靠地筛查和早期诊断癌前和癌性宫颈病变。振动光谱在各种肿瘤的诊断方面取得了很好的结果，特别是使用傅里叶变换红外显微光谱，事实证明它是目前用于癌症诊断的组织病理学方法的一个有前景的补充。这种光谱技术被应用于分析冷冻保存的人类宫颈组织样本，包括鳞状细胞癌（SCC）样本和非癌样本。构建了一个专用的支持向量机分类模型，以便将样本分类为正常或恶性，随后通过交叉验证进行验证，准确率高于90%。
