Literature DB >> 20384240

Advanced statistical techniques applied to comprehensive FTIR spectra on human colonic tissues.

A Zwielly1, S Mordechai, I Sinielnikov, A Salman, E Bogomolny, S Argov.   

Abstract

PURPOSE: Colon cancer is a major public health problem due to its high disease rate and death toll worldwide. The use of FTIR microscopy in the field of cancer diagnosis has become attractive over the past 20 years. In the present study, the authors investigated the potential of FTIR microscopy to define spectral changes among normal, polyp, and cancer human colonic biopsied tissues.
METHODS: A large database of FTIR microscopic spectra was compiled from 230 human colonic biopsies. The database was divided into five subgroups: Normal, cancerous tissues, and three stages of benign colonic polyps, namely, mild, moderate, and severe polyps, which are precursors of carcinoma. All biopsied tissue sections were classified concurrently by an expert pathologist. The authors applied the principal components analysis (PCA) model to reduce the dimension of the original data size to 13 principal components.
RESULTS: While PCA analysis shows only partial success in distinguishing among cancer, polyp, and the normal tissues, multivariate analysis (e.g., LDA) shows a promising distinction even within the polyp subgroups.
CONCLUSIONS: Good classification accuracy among normal, polyp, and cancer groups was achieved with a success rate of approximately 85%. These results strongly support the potential of developing FTIR microscopy as a simple, reagent-free tool for early detection of colon cancer and, in particular, for discriminating among the benign premalignant colonic polyps having increasing degrees of dysplasia severity (mild, moderate, and severe).

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Year:  2010        PMID: 20384240     DOI: 10.1118/1.3298013

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  5 in total

1.  Renal Graft Fibrosis and Inflammation Quantification by an Automated Fourier-Transform Infrared Imaging Technique.

Authors:  Vincent Vuiblet; Michael Fere; Cyril Gobinet; Philippe Birembaut; Olivier Piot; Philippe Rieu
Journal:  J Am Soc Nephrol       Date:  2015-12-18       Impact factor: 10.121

2.  Selecting optimal features from Fourier transform infrared spectroscopy for discrete-frequency imaging.

Authors:  Rupali Mankar; Michael J Walsh; Rohit Bhargava; Saurabh Prasad; David Mayerich
Journal:  Analyst       Date:  2018-02-26       Impact factor: 4.616

3.  Chemometrics of differentially expressed proteins from colorectal cancer patients.

Authors:  Lay-Chin Yeoh; Saravanan Dharmaraj; Boon-Hui Gooi; Manjit Singh; Lay-Harn Gam
Journal:  World J Gastroenterol       Date:  2011-04-28       Impact factor: 5.742

4.  Grading of intrinsic and acquired cisplatin-resistant human melanoma cell lines: an infrared ATR study.

Authors:  A Zwielly; S Mordechai; G Brkic; E Bogomolny; I Z Pelly; R Moreh; J Gopas
Journal:  Eur Biophys J       Date:  2011-04-07       Impact factor: 1.733

5.  Potential of infrared microscopy to differentiate between dementia with Lewy bodies and Alzheimer's diseases using peripheral blood samples and machine learning algorithms.

Authors:  Ahmad Salman; Itshak Lapidot; Elad Shufan; Adam H Agbaria; Bat-Sheva Porat Katz; Shaul Mordechai
Journal:  J Biomed Opt       Date:  2020-04       Impact factor: 3.170

  5 in total

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