Imaging of colorectal adenocarcinoma using FT-IR microspectroscopy and cluster analysis

被引:341
作者
Lasch, P
Haensch, W
Naumann, D
Diem, M
机构
[1] Robert Koch Inst, D-13353 Berlin, Germany
[2] Humboldt Univ, Robert Rossle Klin, Max Delbruck Ctr Mol Med, Dept Pathol,Charite Med Fac, D-13125 Berlin, Germany
[3] CUNY Hunter Coll, Dept Chem & Biochem, New York, NY 10021 USA
来源
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE | 2004年 / 1688卷 / 02期
基金
美国国家卫生研究院;
关键词
cluster analysis; IR imaging; biomedical spectroscopy; FT-IR microspectroscopy; colorectal adenocarcinoma; patternr ecognition; tissue classification;
D O I
10.1016/j.bbadis.2003.12.006
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In this paper, three different clustering algorithms were applied to assemble infrared (IR) spectral maps from IR microspectra of tissues. Using spectra from a colorectal adenocarcinoma section, we show how IR images can be assembled by agglomerative hierarchical (AH) clustering (Ward's technique), fuzzy C-means (FCM) clustering, and k-means (KM) clustering. We discuss practical problems of IR imaging on tissues such as the influence of spectral quality and data pretreatment on image quality. Furthermore, the applicability of cluster algorithms to the spatially resolved microspectroscopic data and the degree of correlation between distinct cluster images and histopathology are compared. The use of any of the clustering algorithms dramatically increased the information content of the IR images, as compared to univariate methods of IR imaging (functional group mapping). Among the cluster imaging methods, AH clustering (Ward's algorithm) proved to be the best method in terms of tissue structure differentiation. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:176 / 186
页数:11
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