Classification of human colonic tissues using FTIR spectra and advanced statistical techniques

One of the major public health hazards is colon cancer. There is a great necessity to develop new methods for early detection of cancer. If colon cancer is detected and treated early, cure rate of more than 90% can be achieved. In this study we used FTIR microscopy (MSP), which has shown a good potential in the last 20 years in the fields of medical diagnostic and early detection of abnormal tissues. Large database of FTIR microscopic spectra was acquired from 230 human colonic biopsies. Five different subgroups were included in our database, normal and cancer tissues as well as three stages of benign colonic polyps, namely, mild, moderate and severe polyps which are precursors of carcinoma. In this study we applied advanced mathematical and statistical techniques including principal component analysis (PCA) and linear discriminant analysis (LDA), on human colonic FTIR spectra in order to differentiate among the mentioned subgroups' tissues. Good classification accuracy between normal, polyps and cancer groups was achieved with approximately 85% success rate. Our results showed that there is a great potential of developing FTIR-micro spectroscopy as a simple, reagent-free viable tool for early detection of colon cancer in particular the early stages of premalignancy among the benign colonic polyps.

[1]  Frank R. Burden,et al.  An Investigation into FTIR Spectroscopy as a Biodiagnostic Tool for Cervical Cancer , 1998 .

[2]  S. Argov,et al.  PROOF COPY 012202JBO Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients , 2002 .

[3]  Peter Lasch,et al.  Biomedical Vibrational Spectroscopy , 2008 .

[4]  Natalia I. Afanasyeva,et al.  Diagnostics of cancer tissues by fiber optic evanescent wave Fourier transform IR (FEW-FTIR) spectroscopy , 1997, Photonics West - Biomedical Optics.

[5]  F. Mauro,et al.  A New Approach to the Study of Human Solid Tumor Cells by Means of FT-IR Microspectroscopy , 1990 .

[6]  Reinhard F. Bruch,et al.  Diagnostics of breast cancer tissues by fiber optic evanescent wave Fourier transform IR (FEW-FTIR) spectroscopy : Innovations in Breast Cancer Diagnosis and Minimally Invasive Therapy , 1999 .

[7]  Max Diem,et al.  Infrared Spectroscopy of Cells and Tissues: Shining Light onto a Novel Subject , 1999 .

[8]  L. Murphy,et al.  A comparative infrared spectroscopic study of human breast tumors and breast tumor cell xenografts , 1995 .

[9]  S. Mordechai,et al.  Fourier transform infrared spectroscopy in cancer detection. , 2005, Future oncology.

[10]  Max Diem,et al.  Vibrational Spectroscopy for Medical Diagnosis , 2008 .

[11]  P. Nabet,et al.  Applications of infrared spectroscopy to medical biology. , 1998, Cellular and molecular biology.

[12]  N. Polissar,et al.  Models of DNA structure achieve almost perfect discrimination between normal prostate, benign prostatic hyperplasia (BPH), and adenocarcinoma and have a high potential for predicting BPH and prostate cancer. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Natalia I. Afanasyeva,et al.  Minimally invasive and ex-vivo diagnostics of breast cancer tissues by fiber optic evanescent-wave Fourier transform IR (FEW-FTIR) spectroscopy , 1998, Photonics West - Biomedical Optics.

[14]  Markus Ritter,et al.  Altered cell volume regulation in ras oncogene expressing NIH fibroblasts , 1992, Pflügers Archiv.