Persistent high-risk human papillomavirus (HR-HPV) infection is leading cause for the occurrence of cervical cancer, and timely detection and early treatment of HR-HPV infection can effectively reduce incidence of cervical cancer. In this study, a rapid and non-invasive method for detecting HR-HPV was proposed by using Fourier transform infrared (FT-IR) spectra of cervical exfoliated cells combined with multivariate analysis. A total of 100 spectra were recorded from 50 HR-HPV positive patients and 50 normal subjects. The obvious difference in infrared spectrum between the two groups was mainly shown at 1042 cm⁻¹ (mucin), 1246 cm⁻¹ (amide III), 1396 cm^-1 (proteins), 1543 cm⁻¹ (amide II), 1651 cm⁻¹ (amide I), 2361 cm⁻¹ (CO₂), 2928 cm⁻¹ (lipids), and 3294 cm⁻¹ (amide A). Then, a principal component analysis-linear discriminant analysis (PCA-LDA) diagnostic model was developed and applied on the FT-IR spectra of normal samples as well as HR-HPV positive patients, and satisfactory classification results were obtained. The diagnostic accuracy, specificity, and sensitivity were 98 %, 98 %, and 98 %, respectively. Furthermore, the area under the receiver operating characteristic (ROC) curve (AUC) was 0.997, which could further demonstrate the feasibility of the PCA-LDA model. Therefore, our exploratory work shows that the combination of FT-IR spectroscopy and PCA-LDA model has great potential for HR-HPV screening.

持续存在的高危人乳头瘤病毒（HR-HPV）感染是宫颈癌发生的主要原因，及时发现和早期治疗HR-HPV感染可以有效降低宫颈癌的发生率。在这项研究中，通过使用宫颈脱落细胞的傅立叶变换红外光谱（FT-IR）结合多变量分析，提出了一种快速，无创的​​HR-HPV检测方法。从50例HR-HPV阳性患者和50例正常受试者中记录了总共100张光谱。两组之间红外光谱的明显差异主要表现在1042 cm ^-1（粘蛋白），1246 cm ^-1（酰胺III），1396 cm ^-1（蛋白质），1543 cm ^-1（酰胺II），1651 cm ^-1（酰胺I），2361 cm ^-1（CO ₂），2928 cm ^-1（脂质）和3294 cm ^-1（酰胺A）。然后，建立了主成分分析-线性判别分析（PCA-LDA）诊断模型，并将其应用于正常样品以及HR-HPV阳性患者的FT-IR光谱，并获得了令人满意的分类结果。诊断准确性，特异性和敏感性分别为98％，98％和98％。此外，接收器工作特性（ROC）曲线（AUC）下的面积为0.997，这可以进一步证明PCA-LDA模型的可行性。因此，我们的探索性工作表明，将FT-IR光谱学和PCA-LDA模型相结合具有进行HR-HPV筛查的巨大潜力。