Early Diagnosis of Colon Cancer Using Raman Spectroscopy and Multivariate Statistical Analysis Techniques

LUO Shu-wen; CHEN Chang-shui; CHEN Wei-dong

doi:10.3788/fgxb20133411.1544

您当前的位置：

首页 >

文章列表页 >

Early Diagnosis of Colon Cancer Using Raman Spectroscopy and Multivariate Statistical Analysis Techniques

更新时间：2020-08-12

- Early Diagnosis of Colon Cancer Using Raman Spectroscopy and Multivariate Statistical Analysis Techniques
- Chinese Journal of Luminescence Vol. 34, Issue 11, Pages: 1544-1549(2013)
- 作者机构：
  
  1. 华南师范大学广东省微纳光子功能材料与器件重点实验室,广东广州,510006
  2. Universit&eacute re
  3. du Littoral C&ocirc
  4. te d'Opale, Dunkerque,France
  5. Laboratoire de Physicochimie de l'Atmosph&egrave
- 作者简介：
- 基金信息：
- DOI：10.3788/fgxb20133411.1544
  CLC： Q631
- Received：30 May 2013，
  
  Revised：29 August 2013，
  
  Published：10 November 2013
- 稿件说明：
移动端阅览
罗舒文, 陈长水, CHEN Wei-dong. 基于拉曼光谱和多元统计分析技术的结肠癌早期诊断[J]. 发光学报, 2013,34(11): 1544-1549

LUO Shu-wen, CHEN Chang-shui, CHEN Wei-dong. Early Diagnosis of Colon Cancer Using Raman Spectroscopy and Multivariate Statistical Analysis Techniques[J]. Chinese Journal of Luminescence, 2013,34(11): 1544-1549
罗舒文, 陈长水, CHEN Wei-dong. 基于拉曼光谱和多元统计分析技术的结肠癌早期诊断[J]. 发光学报, 2013,34(11): 1544-1549 DOI： 10.3788/fgxb20133411.1544.

LUO Shu-wen, CHEN Chang-shui, CHEN Wei-dong. Early Diagnosis of Colon Cancer Using Raman Spectroscopy and Multivariate Statistical Analysis Techniques[J]. Chinese Journal of Luminescence, 2013,34(11): 1544-1549 DOI： 10.3788/fgxb20133411.1544.

摘要

为了寻找结肠癌的病理发展规律在拉曼光谱属性上的体现

采用共聚焦显微拉曼光谱仪对60例离体的正常结肠组织、腺瘤性息肉和腺癌组织的近红外拉曼光谱进行对比检测

初步探讨了三类组织的拉曼光谱特征及其改变的规律。结果表明:三类组织拉曼光谱的差异明显存在于830

855

1 032

1 210

1 323

1 335

1 445

1 450

1 655 cm

-1

处

腺瘤性息肉的光谱大体位于正常组织与腺癌组织之间。以组织病理诊断为金标准

主成分分析结合线性判别分析技术建立的诊断算法区分3类组织的灵敏度分别为96.9%、85.7%和97.3%

特异性分别为82.8%、90%和92.3%。因此

拉曼光谱有潜力在分子水平上区分正常结肠组织、腺瘤性息肉和腺癌组织

有望成为结肠癌早期诊断的一种有效方法。

Abstract

By using confocal Raman microspectrometer

near-infrared (NIR) Raman spectra from 60 cases of

ex vivo

normal

adenomatous polyp and adenocarcinoma colon tissues were obtained. To find the embodiment of the regularity of pathological development of colon cancer on Raman spectral characteristic

we analyzed and compared the Raman spectral properties of the three tissue types

and researched the regularity of spectra-related changes. The results show that significant differences in Raman spectra were observed among the three tissue types at around 830

855

1 032

1 210

1 323

1 335

1 445

1 450 and 1 655 cm

-1

. Overall

the spectra of adenomatous polyp was in the middle of the spectra of normal and adenocarcinoma colon tissues

which might illustrate that adenomatous polyp was in the transitional state. Principal component analysis (PCA) and linear discriminant analysis (LDA) were employed to develop diagnostic algorithms for classifying the Raman spectra of different types of colon tissues. Based on the gold standards of histopathologic diagnosis

sensitivities of 96.9%

85.7% and 97.3%

and specificities of 82.8%

90%

and 92.3%

respectively were achieved by using PCA-LDA algorithms to discriminate the normal

adenomatous polyp and adenocarcinoma colon tissues. Therefore

near-infrared Raman spectroscopy can not only be utilized to differentiate colon cancer tissues from normal tissues

but also be used for discriminating colon premalignant lesions in molecular level. It is a potential effective method for early diagnosis of colon cancer.

关键词

Keywords

references

Jemal A, Bray F, Center M M, et al. Global cancer statistics [J]. CA Cancer J. Clin., 2011, 61(2):69-90.[2] American Cancer Society. Colorectal Cancer Facts & Figures 2008~2010 [R]. Atlanta: American Cancer Society, 2008:1-32.[3] Lopes P C, Moreira J A, Almeida A, et al. Discriminating adenocarcinoma from normal colonic mucosa through deconvolution of Raman spectra [J]. J. Biomed. Opt., 2011, 16(12):127001-1-13.[4] Beljebbar A, Bouche O, Diebold M D, et al. Identification of Raman spectroscopic markers for the characterization of normal and adenocarcinomatous colonic tissues [J]. Crit. Rev. Oncol. Hematol., 2009, 72(3):255-264.[5] Teh S K, Zheng W, Ho K Y, et al. Near-infrared Raman spectroscopy for optical diagnosis in the stomach: Identification of Helicobacter-pylori infection and intestinal metaplasia [J]. Int. J. Cancer, 2010, 126(8):1920-1927.[6] Teh S K, Zheng W, Ho K Y, et al. Near-infrared Raman spectroscopy for early diagnosis and typing of adenocarcinoma in the stomach [J]. Br. J. Surg., 2010, 97(4):550-557.[7] Molckovsky A, Song L M, Shim M G, et al. Diagnostic potential of near-infrared Raman spectroscopy in the colon:Diffe-rentiating adenomatous from hyperplastic polyps [J]. Gastrointest. Endosc., 2003, 57(3):396-402.[8] Huang Z, Zheng W, Widjaja E, et al. Classification of colonic tissues using Raman spectroscopy and multivariate techniques [J]. Biomed. Vib. Spectrosc. Ⅲ, 2006, 6093:60930Q-1-4.[9] Widjaja E, Zheng W, Huang Z. Classification of colonic tissues using near-infrared Raman spectroscopy and support vector machines [J]. Int. J. Oncol., 2008, 32(3):653-662.[10] Chowdary M V, Kumar K K, Thakur K, et al. Discrimination of normal and malignant mucosal tissues of the colon by Raman spectroscopy [J]. Photomed. Laser Surg., 2007, 25(4):269-274.[11] Zhang Z M, Chen S, Liang Y Z, et al. An intelligent background-correction algorithm for highly fluorescent samples in Raman spectroscopy [J]. J. Raman Spectrosc., 2009, 41(6):659-669.[12] Zhang Z M, Chen S, Liang Y Z. Baseline correction using adaptive iteratively reweighted penalized least squares [J]. Analyst., 2010, 135(5):1138-1146.[13] Krafft C, Steiner G, Beleites C, et al. Disease recognition by infrared and Raman spectroscopy [J]. J. Biophoton., 2009, 2(1-2):13-28.[14] Sattlecker M, Stone N, Smith J, et al. Assessment of robustness and transferability of classification models built for cancer diagnostics using Raman spectroscopy [J]. J. Raman Spectrosc., 2011, 42(5):897-903.[15] Bergholt M S, Zheng W, Lin K, et al. Characterizing variability in in vivo Raman spectra of different anatomical locations in the upper gastrointestinal tract toward cancer detection [J]. J. Biomed. Opt., 2011, 16(3):037003-1-11.[16] Bender R, Lange S. Adjusting for multiple testing－when and how? [J]. J. Clin. Epidemiol., 2001, 54(4):343-349.[17] Bergholt M S, Zheng W, Lin K, et al. Raman endoscopy for in vivo differentiation between benign and malignant ulcers in the stomach [J]. Analyst., 2010, 135(12):3162-3168.[18] Kast R E, Serhatkulu G K, Cao A, et al. Raman spectroscopy can differentiate malignant tumors from normal breast tissue and detect early neoplastic changes in a mouse model [J]. Biopolymers, 2008, 89(3):235-241.[19] Yan X L, Dong R X, Zhang L, et al. Raman spectra of single cell from gastrointestinal cancer patients [J]. World J. Gastroenterol., 2005, 11(21):3290-3292.[20] Hughes J H, Leigh C J, Raab S S, et al. Cytologic criteria for the brush diagnosis of gastric adenocarcinoma [J]. Cancer, 1998, 84(5):289-294.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Recent Advances in Optical Microcavity Enhanced Fluorescence and Raman Spectroscopy

Effect of Low Growth Pressure of HT-AlN Buffer on GaN Epilayer Grown on Si(111)

Raman Spectra Enhancement of Dioxin-like Polychlorinated Biphenyls (PCBs) Based on Molecular Docking

Controllable Synthesis of High Quality Monolayer WS₂ with Large Size on Sapphire Substrate by Chemical Vapor Deposition

Microstructure and Photoluminescence Characteristics of Solution Controlled ZnO Crystals

Related Author

JIANG Yijian

YAN Yinzhou

YAO Yao

YANG Tao-tao

HAN Jun

ZHAO Jia-hao

XING Yan-hui

SHI Feng-feng

Related Institution

School of Physics and Optoelectronic Engineering， Beijing University of Technology

Key Laboratory of Opto-electronics Technology, Ministry of Education, College of Microelectronics, Beijing University of Technology

Key Laboratory of Nano Devices and Applications, Suzhou Institute of Nano-technology and Nano-bionics, Chinese Academy of Sciences

College of Environmental Science and Engineering, North China Electric Power University

The Moe Key Laboratory of Resources and Environmental Systems Optimization, North China Electric Power University

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176862 Email：fgxbt@126.com
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰