Suppr超能文献

智能刀(iKnife)及其在治疗宫颈疾病中的术中诊断优势。

The intelligent knife (iKnife) and its intraoperative diagnostic advantage for the treatment of cervical disease.

机构信息

Department of Gut, Metabolism and Reproduction, Institute of Reproductive and Developmental Biology, Faculty of Medicine, Imperial College London, London SW7 2DD, United Kingdom.

Department of Surgery and Cancer, Institute of Reproductive and Developmental Biology, Faculty of Medicine, Imperial College London, London SW7 2DD, United Kingdom.

出版信息

Proc Natl Acad Sci U S A. 2020 Mar 31;117(13):7338-7346. doi: 10.1073/pnas.1916960117. Epub 2020 Mar 16.

Abstract

Clearance of surgical margins in cervical cancer prevents the need for adjuvant chemoradiation and allows fertility preservation. In this study, we determined the capacity of the rapid evaporative ionization mass spectrometry (REIMS), also known as intelligent knife (iKnife), to discriminate between healthy, preinvasive, and invasive cervical tissue. Cervical tissue samples were collected from women with healthy, human papilloma virus (HPV) ± cervical intraepithelial neoplasia (CIN), or cervical cancer. A handheld diathermy device generated surgical aerosol, which was transferred into a mass spectrometer for subsequent chemical analysis. Combination of principal component and linear discriminant analysis and least absolute shrinkage and selection operator was employed to study the spectral differences between groups. Significance of discriminatory features was tested using univariate statistics and tandem MS performed to elucidate the structure of the significant peaks allowing separation of the two classes. We analyzed 87 samples (normal = 16, HPV ± CIN = 50, cancer = 21 patients). The iKnife discriminated with 100% accuracy normal (100%) vs. HPV ± CIN (100%) vs. cancer (100%) when compared to histology as the gold standard. When comparing normal vs. cancer samples, the accuracy was 100% with a sensitivity of 100% (95% CI 83.9 to 100) and specificity 100% (79.4 to 100). Univariate analysis revealed significant MS peaks in the cancer-to-normal separation belonging to various classes of complex lipids. The iKnife discriminates healthy from premalignant and invasive cervical lesions with high accuracy and can improve oncological outcomes and fertility preservation of women treated surgically for cervical cancer. Larger in vivo research cohorts are required to validate these findings.

摘要

宫颈癌的手术切缘清除可避免辅助放化疗的需要,并允许保留生育能力。在这项研究中,我们确定了快速蒸发电离质谱(REIMS),也称为智能刀(iKnife),区分健康、癌前和浸润性宫颈组织的能力。从患有健康、人乳头瘤病毒(HPV)±宫颈上皮内瘤变(CIN)或宫颈癌的女性中采集宫颈组织样本。手持电烙设备产生手术气溶胶,然后将其转移到质谱仪进行后续化学分析。我们采用主成分和线性判别分析以及最小绝对收缩和选择算子组合来研究组间光谱差异。使用单变量统计检验来检验有区别的特征的显著性,并进行串联 MS 以阐明显著峰的结构,从而允许两类的分离。我们分析了 87 个样本(正常=16,HPV±CIN=50,癌症=21 例)。与组织学作为金标准相比,iKnife 的准确率为 100%,可准确区分正常(100%)与 HPV±CIN(100%)与癌症(100%)。当比较正常与癌症样本时,准确率为 100%,灵敏度为 100%(95%CI83.9 至 100),特异性为 100%(79.4 至 100)。单变量分析显示,癌症与正常分离中存在各种复杂脂质类别的显著 MS 峰。iKnife 以高准确率区分健康与癌前和浸润性宫颈病变,可改善因宫颈癌接受手术治疗的女性的肿瘤学结局和生育能力保留。需要更大的体内研究队列来验证这些发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3cc/7132269/5a1884b3f7c1/pnas.1916960117fig01.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验