Literature DB >> 25649324

Rapid identification of goblet cells in unstained colon thin sections by means of quantum cascade laser-based infrared microspectroscopy.

N Kröger-Lui1, N Gretz, K Haase, B Kränzlin, S Neudecker, A Pucci, A Regenscheit, A Schönhals, W Petrich.   

Abstract

Changes in the volume covered by mucin-secreting goblet cell regions within colon thin sections may serve as a means to differentiate between ulcerative colitis and infectious colitis. Here we show that rapid, quantum cascade laser-based mid-infrared microspectroscopy might be able to contribute to the differential diagnosis of colitis ulcerosa, an inflammatory bowel disease. Infrared hyperspectral images of mouse colon thin sections were obtained within 7.5 minutes per section with a pixel size of 3.65 × 3.65 μm(2) and a field of view of 2.8 × 3.1 mm(2). The spectra were processed by training a random decision forest classifier on the basis of k-means clustering on one thin section. The trained algorithm was then applied to 5 further thin sections for a blinded validation and it was able to identify goblet cells in all sections. The rapid identification of goblet cells within these unstained, paraffinized thin sections of colon tissue was enabled by the high content of glycopeptides within the goblet cells as revealed by the pronounced spectral signatures in the 7.6 μm-8.6 μm and the 9.2 μm-9.7 μm wavelength ranges of the electromagnetic spectrum. More so, the simple calculation of the ratio between the absorbance values at 9.29 μm and 8.47 μm provides the potential to further shorten the time for measurement and analysis of a thin section down to well below 1 minute.

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Year:  2015        PMID: 25649324     DOI: 10.1039/c4an02001d

Source DB:  PubMed          Journal:  Analyst        ISSN: 0003-2654            Impact factor:   4.616


  7 in total

Review 1.  Infrared Spectroscopic Imaging Advances as an Analytical Technology for Biomedical Sciences.

Authors:  Tomasz P Wrobel; Rohit Bhargava
Journal:  Anal Chem       Date:  2018-02-06       Impact factor: 6.986

Review 2.  Advances in Digital Pathology: From Artificial Intelligence to Label-Free Imaging.

Authors:  Frederik Großerueschkamp; Hendrik Jütte; Klaus Gerwert; Andrea Tannapfel
Journal:  Visc Med       Date:  2021-08-24

3.  Development of a practical spatial-spectral analysis protocol for breast histopathology using Fourier transform infrared spectroscopic imaging.

Authors:  F Nell Pounder; Rohith K Reddy; Rohit Bhargava
Journal:  Faraday Discuss       Date:  2016-06-23       Impact factor: 4.008

4.  Rapid brain structure and tumour margin detection on whole frozen tissue sections by fast multiphotometric mid-infrared scanning.

Authors:  Tim Kümmel; Björn van Marwick; Miriam Rittel; Carina Ramallo Guevara; Felix Wühler; Tobias Teumer; Björn Wängler; Carsten Hopf; Matthias Rädle
Journal:  Sci Rep       Date:  2021-05-28       Impact factor: 4.379

5.  Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging.

Authors:  Angela Kallenbach-Thieltges; Frederik Großerueschkamp; Hendrik Jütte; Claus Kuepper; Anke Reinacher-Schick; Andrea Tannapfel; Klaus Gerwert
Journal:  Sci Rep       Date:  2020-06-23       Impact factor: 4.379

6.  Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections.

Authors:  Claus Kuepper; Angela Kallenbach-Thieltges; Hendrik Juette; Andrea Tannapfel; Frederik Großerueschkamp; Klaus Gerwert
Journal:  Sci Rep       Date:  2018-05-16       Impact factor: 4.379

7.  Simultaneous cancer and tumor microenvironment subtyping using confocal infrared microscopy for all-digital molecular histopathology.

Authors:  Shachi Mittal; Kevin Yeh; L Suzanne Leslie; Seth Kenkel; Andre Kajdacsy-Balla; Rohit Bhargava
Journal:  Proc Natl Acad Sci U S A       Date:  2018-06-04       Impact factor: 11.205

  7 in total

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