Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Distinguishing tumor from healthy tissue in human liver ex vivo using machine learning and multivariate analysis of diffuse reflectance spectra

Reistad, Nina LU orcid and Sturesson, Christian (2022) In Journal of Biophotonics 15(10).
Abstract
The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues, and to determine whether an extended wavelength range (450–1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100%, and a Matthews correlation coefficient of 100% using the... (More)
The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues, and to determine whether an extended wavelength range (450–1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100%, and a Matthews correlation coefficient of 100% using the extended wavelength range and a combination of principal component analysis and support vector techniques. The results indicate that this technology may be useful in clinical applications for real-time tissue diagnostics of tumor margins where rapid classification is important. (Less)
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
diffuse reflectance spectroscopy, extended wavelength region, human liver tissues, multivariate analysis, discriminant analysis, linear discriminant analysis, support vector machine, machine learning
in
Journal of Biophotonics
volume
15
issue
10
publisher
John Wiley & Sons Inc.
external identifiers
  • scopus:85135516750
  • pmid:35860880
ISSN
1864-0648
DOI
10.1002/jbio.202200140
language
English
LU publication?
yes
id
0d54a986-1115-46eb-a2ab-e26daddc1ac5
date added to LUP
2022-07-22 11:39:34
date last changed
2024-02-16 07:10:05
@article{0d54a986-1115-46eb-a2ab-e26daddc1ac5,
  abstract     = {{The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues, and to determine whether an extended wavelength range (450–1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100%, and a Matthews correlation coefficient of 100% using the extended wavelength range and a combination of principal component analysis and support vector techniques. The results indicate that this technology may be useful in clinical applications for real-time tissue diagnostics of tumor margins where rapid classification is important.}},
  author       = {{Reistad, Nina and Sturesson, Christian}},
  issn         = {{1864-0648}},
  keywords     = {{diffuse reflectance spectroscopy; extended wavelength region; human liver tissues; multivariate analysis; discriminant analysis; linear discriminant analysis; support vector machine; machine learning}},
  language     = {{eng}},
  month        = {{07}},
  number       = {{10}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Journal of Biophotonics}},
  title        = {{Distinguishing tumor from healthy tissue in human liver ex vivo using machine learning and multivariate analysis of diffuse reflectance spectra}},
  url          = {{http://dx.doi.org/10.1002/jbio.202200140}},
  doi          = {{10.1002/jbio.202200140}},
  volume       = {{15}},
  year         = {{2022}},
}