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采用多直径单光纤反射光谱技术提高 Barrett 食管患者的内镜监测效果。

Toward improved endoscopic surveillance with multidiameter single fiber reflectance spectroscopy in patients with Barrett's esophagus.

机构信息

Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Department of Surgery, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

出版信息

J Biophotonics. 2021 Apr;14(4):e202000351. doi: 10.1002/jbio.202000351. Epub 2021 Jan 31.

DOI:10.1002/jbio.202000351
PMID:33410602
Abstract

Patients with Barrett's esophagus are at an increased risk to develop esophageal cancer and, therefore, undergo regular endoscopic surveillance. Early detection of neoplasia enables endoscopic treatment, which improves outcomes. However, early Barrett's neoplasia is easily missed during endoscopic surveillance. This study investigates multidiameter single fiber reflectance spectroscopy (MDSFR) to improve Barrett's surveillance. Based on the concept of field cancerization, it may be possible to identify the presence of a neoplastic lesion from measurements elsewhere in the esophagus or even the oral cavity. In this study, MDSFR measurements are performed on non-dysplastic Barrett's mucosa, squamous mucosa, oral mucosa, and the neoplastic lesion (if present). Based on logistic regression analysis on the scattering parameters measured by MDSFR, a classifier is developed that can predict the presence of neoplasia elsewhere in the Barrett's segment from measurements on the non-dysplastic Barrett's mucosa (sensitivity 91%, specificity 71%, AUC = 0.77). Classifiers obtained from logistic regression analysis for the squamous and oral mucosa do not result in an AUC significantly different from 0.5.

摘要

巴雷特食管患者发生食管癌的风险增加,因此需要进行定期的内镜监测。早期发现肿瘤可以进行内镜治疗,从而改善预后。然而,在内镜监测中,早期的巴雷特肿瘤很容易被忽视。本研究探讨了多直径单光纤反射光谱(MDSFR)以改善巴雷特的监测。基于肿瘤发生的概念,有可能从食管或口腔的其他部位的测量中识别出肿瘤病变的存在。在这项研究中,对非异型增生的巴雷特黏膜、鳞状黏膜、口腔黏膜和肿瘤病变(如果存在)进行 MDSFR 测量。基于 MDSFR 测量的散射参数的逻辑回归分析,开发了一个分类器,可以从非异型增生的巴雷特黏膜的测量中预测巴雷特段的其他部位是否存在肿瘤(敏感性 91%,特异性 71%,AUC=0.77)。从鳞状和口腔黏膜的逻辑回归分析获得的分类器没有导致 AUC 显著不同于 0.5。

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