Fourier transform infrared (FTIR) spectral mapping of the cervical transformation zone, and dysplastic squamous epithelium
Fourier transform infrared (FTIR) spectral mapping of the cervical transformation zone, and dysplastic squamous epithelium
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DOI：
10.1016/j.ygyno.2003.12.028
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发表时间：
2004-04-01
影响因子：
4.7
通讯作者：
Diem, M
中科院分区：
文献类型：
--
作者：
Wood, BR;Chiriboga, L;Diem, M
目标。本文旨在建立宫颈鳞状上皮不同组织类型及疾病不同阶段的红外光谱图谱。讨论了对这些组织类型进行无监督区分的方法。傅立叶变换红外（FTIR）图的鳞状和腺状宫颈上皮，以及宫颈转化区，获得和分析多变量无监督分层聚类方法。所产生的簇与组织切片中相应的染色组织病理学特征相关。对组织切片收集的FTIR光谱进行多元统计分析，允许一种无监督的方法来区分组织类型，并区分正常和病变组织。通过分析不同的光谱窗口并将结果与组织学进行比较，我们发现酰胺I和II区域（1740- 1470 cm(-1)）在将组织的解剖和组织病理学特征与光谱簇关联方面非常重要。由于在这些工作中使用的是一种无监督的算法，而不是诊断算法，因此目前没有假阳性/假阴性结果的统计分析报告。FTIR显微光谱和多元光谱处理的结合提供了对单个细胞基本光谱特征的重要见解，因此显示出作为宫颈癌诊断工具的潜力。(C) 2004爱思唯尔公司版权所有。
Objective. This paper is aimed at establishing infrared spectral patterns for the different tissue types found in, and for different stages of disease of squamous cervical epithelium. Methods for the unsupervised distinction of these tissue types are discussed.Methods. Fourier transform infrared (FTIR) maps of the squamous and glandular cervical epithelium, and of the cervical transformation zone, were obtained and analyzed by multivariate unsupervised hierarchical cluster methods. The resulting clusters are correlated to the corresponding stained histopathological features in the tissue sections.Results. Multivariate statistical analysis of FTIR spectra collected for tissue sections permit an unsupervised method of distinguishing tissue types, and of differentiating between normal and diseased tissue. By analyzing different spectral windows and comparing the results with histology, we found the amide I and II region (1740- 1470 cm(-1)) to be very important in correlating anatomical and histopathological features in tissue to spectral clusters. Since an unsupervised, rather than a diagnostic, algorithm was used in these efforts, no statistical analysis of false-positive/false-negative results is reported at this time.Conclusions. The combination of FTIR micro-spectroscopy and multivariate spectral processing provides important insights into the fundamental spectral signatures of individual cells and consequently shows potential as a diagnostic tool for cervical cancer. (C) 2004 Elsevier Inc. All rights reserved.