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Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”

Alexandra Sala Orcid Logo, Katie E. Spalding, Katherine M. Ashton, Ruth Board, Holly J. Butler, Timothy P. Dawson, Dean A. Harris, Caryn S. Hughes, Cerys A. Jenkins, Michael D. Jenkinson, David S. Palmer, Benjamin R. Smith, Cathy Thornton Orcid Logo, Matthew J. Baker

Journal of Biophotonics, Volume: 13, Issue: 9

Swansea University Author: Cathy Thornton Orcid Logo

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DOI (Published version): 10.1002/jbio.202000118

Abstract

In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR-FTIR o...

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Published in: Journal of Biophotonics
ISSN: 1864-063X 1864-0648
Published: Wiley 2020
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URI: https://cronfa.swan.ac.uk/Record/cronfa54465
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spelling 2022-12-06T15:10:28.1838124 v2 54465 2020-06-12 Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying” c71a7a4be7361094d046d312202bce0c 0000-0002-5153-573X Cathy Thornton Cathy Thornton true false 2020-06-12 BMS In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR-FTIR on both liquid and air-dried samples to investigate “digital drying” as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least-squares method, have demonstrated a greater random forest (RF) classification performance than the air-dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.0% and specificity values higher than 83.0%. Moreover, quantum cascade laser infrared (QCL-IR) based spectroscopic imaging is utilized on liquid samples to assess the implications of a deep-penetration light source on disease classification. The RF classification of QCL-IR data has provided sensitivity and specificity amounting to 85.1% and 75.3% respectively. Journal Article Journal of Biophotonics 13 9 Wiley 1864-063X 1864-0648 1 9 2020 2020-09-01 10.1002/jbio.202000118 COLLEGE NANME Biomedical Sciences COLLEGE CODE BMS Swansea University Engineering and Physical Sciences Research Council. Grant Number: EP/L505080/1 2022-12-06T15:10:28.1838124 2020-06-12T13:49:46.3612714 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Alexandra Sala 0000-0001-6417-9706 1 Katie E. Spalding 2 Katherine M. Ashton 3 Ruth Board 4 Holly J. Butler 5 Timothy P. Dawson 6 Dean A. Harris 7 Caryn S. Hughes 8 Cerys A. Jenkins 9 Michael D. Jenkinson 10 David S. Palmer 11 Benjamin R. Smith 12 Cathy Thornton 0000-0002-5153-573X 13 Matthew J. Baker 14 54465__17747__bd6f872f04974e909980f906b45503cb.pdf jbio.202000118.pdf 2020-07-22T13:14:17.4524374 Output 2878109 application/pdf Version of Record true This is an open access article under the terms of the Creative Commons Attribution License true eng https://creativecommons.org/licenses/by/4.0/
title Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”
spellingShingle Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”
Cathy Thornton
title_short Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”
title_full Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”
title_fullStr Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”
title_full_unstemmed Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”
title_sort Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”
author_id_str_mv c71a7a4be7361094d046d312202bce0c
author_id_fullname_str_mv c71a7a4be7361094d046d312202bce0c_***_Cathy Thornton
author Cathy Thornton
author2 Alexandra Sala
Katie E. Spalding
Katherine M. Ashton
Ruth Board
Holly J. Butler
Timothy P. Dawson
Dean A. Harris
Caryn S. Hughes
Cerys A. Jenkins
Michael D. Jenkinson
David S. Palmer
Benjamin R. Smith
Cathy Thornton
Matthew J. Baker
format Journal article
container_title Journal of Biophotonics
container_volume 13
container_issue 9
publishDate 2020
institution Swansea University
issn 1864-063X
1864-0648
doi_str_mv 10.1002/jbio.202000118
publisher Wiley
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
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description In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR-FTIR on both liquid and air-dried samples to investigate “digital drying” as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least-squares method, have demonstrated a greater random forest (RF) classification performance than the air-dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.0% and specificity values higher than 83.0%. Moreover, quantum cascade laser infrared (QCL-IR) based spectroscopic imaging is utilized on liquid samples to assess the implications of a deep-penetration light source on disease classification. The RF classification of QCL-IR data has provided sensitivity and specificity amounting to 85.1% and 75.3% respectively.
published_date 2020-09-01T04:08:01Z
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