Traynor Damien, Duraipandian Shiyamala, Bhatia Ramya, Cuschieri Kate, Tewari Prerna, Kearney Padraig, D'Arcy Tom, O'Leary John J, Martin Cara M, Lyng Fiona M
Centre for Radiation and Environmental Science, FOCAS Research Institute, Technological University Dublin, D02 HW71 Dublin, Ireland.
School of Physics & Clinical & Optometric Sciences, Technological University Dublin, Grangegorman, D07 XT95 Dublin, Ireland.
Cancers (Basel). 2022 Apr 6;14(7):1836. doi: 10.3390/cancers14071836.
The mortality associated with cervical cancer can be reduced if detected at the precancer stage, but current methods are limited in terms of subjectivity, cost and time. Optical spectroscopic methods such as Raman spectroscopy can provide a rapid, label-free and nondestructive measurement of the biochemical fingerprint of a cell, tissue or biofluid. Previous studies have shown the potential of Raman spectroscopy for cervical cancer diagnosis, but most were pilot studies with small sample sizes. The aim of this study is to show the clinical utility of Raman spectroscopy for identifying cervical precancer in a large sample set with validation in an independent test set. Liquid-based cervical cytology samples ( = 662) (326 negative, 200 cervical intraepithelial neoplasia (CIN)1 and 136 CIN2+) were obtained as a training set. Raman spectra were recorded from single-cell nuclei and subjected to a partial least squares discriminant analysis (PLSDA). In addition, the PLSDA classification model was validated using a blinded independent test set ( = 69). A classification accuracy of 91.3% was achieved with only six of the blinded samples misclassified. This study showed the potential clinical utility of Raman spectroscopy with a good classification of negative, CIN1 and CIN2+ achieved in an independent test set.
如果在癌前阶段检测到宫颈癌，与之相关的死亡率可以降低，但目前的方法在主观性、成本和时间方面存在局限性。诸如拉曼光谱等光学光谱方法可以对细胞、组织或生物流体的生化指纹进行快速、无标记且无损的测量。先前的研究已显示拉曼光谱在宫颈癌诊断方面的潜力，但大多数是小样本量的初步研究。本研究的目的是在一个大样本集中展示拉曼光谱在识别宫颈上皮内瘤变方面的临床实用性，并在一个独立测试集中进行验证。获取了液基宫颈细胞学样本（n = 662）（326例阴性、200例宫颈上皮内瘤变（CIN）1级和136例CIN2 +级）作为训练集。从单个细胞核记录拉曼光谱，并进行偏最小二乘判别分析（PLSDA）。此外，使用一个盲法独立测试集（n = 69）对PLSDA分类模型进行验证。仅6个盲法样本被误分类，分类准确率达到了91.3%。本研究显示了拉曼光谱的潜在临床实用性，在一个独立测试集中对阴性、CIN1级和CIN2 +级实现了良好的分类。
