Dublin Institute of Technology (DIT), Focas Research Institute, DIT Centre for Radiation and Environ, Ireland.
Coombe Women and Infants University Hospital, Department of Pathology, Dublin, Ireland.
J Biomed Opt. 2018 May;23(5):1-8. doi: 10.1117/1.JBO.23.5.055001.
There is an unmet need for methods to help in the early detection of cervical precancer. Optical spectroscopy-based techniques, such as Raman spectroscopy, have shown great potential for diagnosis of different cancers, including cervical cancer. However, relatively few studies have been carried out on liquid-based cytology (LBC) pap test specimens and confounding factors, such as blood contamination, have been identified. Previous work reported a method to remove blood contamination before Raman spectroscopy by pretreatment of the slides with hydrogen peroxide. The aim of the present study was to extend this work to excessively bloody samples to see if these could be rendered suitable for Raman spectroscopy. LBC ThinPrep specimens were treated by adding hydrogen peroxide directly to the vial before slide preparation. Good quality Raman spectra were recorded from negative and high grade (HG) cytology samples with no blood contamination and with heavy blood contamination. Good classification between negative and HG cytology could be achieved for samples with no blood contamination (sensitivity 92%, specificity 93%) and heavy blood contamination (sensitivity 89%, specificity 88%) with poorer classification when samples were combined (sensitivity 82%, specificity 87%). This study demonstrates for the first time the improved potential of Raman spectroscopy for analysis of ThinPrep specimens regardless of blood contamination.
目前，人们迫切需要一些方法来帮助早期检测宫颈癌前病变。基于光谱学的技术，如拉曼光谱学，已显示出在诊断不同癌症（包括宫颈癌）方面的巨大潜力。然而，针对液基细胞学（LBC）巴氏涂片标本的研究相对较少，并且已经确定了一些混杂因素，如血液污染。先前的工作报道了一种在进行拉曼光谱分析之前通过用双氧水预处理载玻片来去除血液污染的方法。本研究旨在将该方法扩展到血液过多的样本，以观察是否可以使这些样本适用于拉曼光谱分析。在准备载玻片之前，直接将双氧水添加到 LBC ThinPrep 小瓶中处理。从没有血液污染和有大量血液污染的阴性和高级别（HG）细胞学样本中记录到了高质量的拉曼光谱。对于没有血液污染的样本（敏感性 92%，特异性 93%）和大量血液污染的样本（敏感性 89%，特异性 88%），可以实现阴性和 HG 细胞学之间的良好分类，而当将样本合并时，分类效果较差（敏感性 82%，特异性 87%）。这项研究首次证明了，无论是否存在血液污染，拉曼光谱分析 ThinPrep 标本的潜力都得到了改善。
