Literature DB >> 27064063

Label-free classification of colon cancer grading using infrared spectral histopathology.

C Kuepper1, F Großerueschkamp1, A Kallenbach-Thieltges1, A Mosig1, A Tannapfel2, K Gerwert1.   

Abstract

In recent years spectral histopathology (SHP) has been established as a label-free method to identify cancer within tissue. Herein, this approach is extended. It is not only used to identify tumour tissue with a sensitivity of 94% and a specificity of 100%, but in addition the tumour grading is determined. Grading is a measure of how much the tumour cells differ from the healthy cells. The grading ranges from G1 (well-differentiated), to G2 (moderately differentiated), G3 (poorly differentiated) and in rare cases to G4 (anaplastic). The grading is prognostic and is needed for the therapeutic decision of the clinician. The presented results show good agreement between the annotation by SHP and by pathologists. A correlation matrix is presented, and the results show that SHP provides prognostic values in colon cancer, which are obtained in a label-free and automated manner. It might become an important automated diagnostic tool at the bedside in precision medicine.

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Year:  2016        PMID: 27064063     DOI: 10.1039/c5fd00157a

Source DB:  PubMed          Journal:  Faraday Discuss        ISSN: 1359-6640            Impact factor:   4.008


  11 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.  Colon Cancer Grading Using Infrared Spectroscopic Imaging-Based Deep Learning.

Authors:  Saumya Tiwari; Kianoush Falahkheirkhah; Georgina Cheng; Rohit Bhargava
Journal:  Appl Spectrosc       Date:  2022-03-25       Impact factor: 3.588

4.  Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics.

Authors:  Frederik Großerueschkamp; Thilo Bracht; Hanna C Diehl; Claus Kuepper; Maike Ahrens; Angela Kallenbach-Thieltges; Axel Mosig; Martin Eisenacher; Katrin Marcus; Thomas Behrens; Thomas Brüning; Dirk Theegarten; Barbara Sitek; Klaus Gerwert
Journal:  Sci Rep       Date:  2017-03-30       Impact factor: 4.379

5.  A convenient protein library for spectroscopic calibrations.

Authors:  Joëlle De Meutter; Erik Goormaghtigh
Journal:  Comput Struct Biotechnol J       Date:  2020-07-10       Impact factor: 7.271

6.  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

7.  Fourier transform infrared spectroscopic imaging of colon tissues: evaluating the significance of amide I and C-H stretching bands in diagnostic applications with machine learning.

Authors:  Cai Li Song; Martha Z Vardaki; Robert D Goldin; Sergei G Kazarian
Journal:  Anal Bioanal Chem       Date:  2019-08-16       Impact factor: 4.142

8.  A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework.

Authors:  Mehedi Masud; Niloy Sikder; Abdullah-Al Nahid; Anupam Kumar Bairagi; Mohammed A AlZain
Journal:  Sensors (Basel)       Date:  2021-01-22       Impact factor: 3.576

9.  Serum levels of zinc, copper, selenium and glutathione peroxidase in the different groups of colorectal cancer patients.

Authors:  Raghad F Al-Ansari; Abdulnasser M Al-Gebori; Ghassan M Sulaiman
Journal:  Caspian J Intern Med       Date:  2020

10.  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

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