Multivariate analysis of laryngeal fluorescence spectra recorded in vivo
(2001) In Lasers in Surgery and Medicine 28(3). p.259-266- Abstract
- Background and Objective: The potential of using various multivariate analysis methods for classification of fluorescence spectra acquired in vivo from laryngeal tissues in Patients was investigated. Study Design/Materials and Methods: Autofluorescence spectra were measured on 29 normal tissue sites and 25 laryngeal lesions using 337-nm excitation. Four different multivariate analysis schemes were applied. Laryngeal fluorescence spectra from patients who had been administered F-aminolevulinic acid (ALA) were obtained using 405-nm excitation and were classified using partial least squares discriminant analysis (PLS-DA). Results: For autofluorescence spectra, logistic regression based on principal component analysis (PCA) or PLS, or PLS-DA... (More)
- Background and Objective: The potential of using various multivariate analysis methods for classification of fluorescence spectra acquired in vivo from laryngeal tissues in Patients was investigated. Study Design/Materials and Methods: Autofluorescence spectra were measured on 29 normal tissue sites and 25 laryngeal lesions using 337-nm excitation. Four different multivariate analysis schemes were applied. Laryngeal fluorescence spectra from patients who had been administered F-aminolevulinic acid (ALA) were obtained using 405-nm excitation and were classified using partial least squares discriminant analysis (PLS-DA). Results: For autofluorescence spectra, logistic regression based on principal component analysis (PCA) or PLS, or PLS-DA all resulted in sensitivities and specificities around 90% for lesion vs. normal. Using ALA and 405-nm excitation gave a sensitivity of 100% and a specificity of 69%. Conclusion: Multivariate analysis of fluorescence spectra could allow classification of laryngeal lesions in vivo with high sensitivity and specificity. PLS performs at least as well as PCA, and PLS-DA performs as well as logistic regression techniques on these data. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1119318
- author
- Eker, Charlotta ; Rydell, Roland LU ; Svanberg, Katarina LU and Andersson-Engels, Stefan LU
- organization
- publishing date
- 2001
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- in vivo diagnosis, larynx, laser-induced fluorescence, partial least squares (PLS), spectroscopy, tissue characterization, multivariate analysis
- in
- Lasers in Surgery and Medicine
- volume
- 28
- issue
- 3
- pages
- 259 - 266
- publisher
- Wiley-Liss Inc.
- external identifiers
-
- wos:000167953500011
- scopus:0035066557
- pmid:11295762
- ISSN
- 0196-8092
- DOI
- 10.1002/lsm.1048
- language
- English
- LU publication?
- yes
- id
- 6612df9d-d80e-488d-a4eb-d584143580ba (old id 1119318)
- date added to LUP
- 2016-04-01 16:55:35
- date last changed
- 2025-04-04 15:16:24
@article{6612df9d-d80e-488d-a4eb-d584143580ba, abstract = {{Background and Objective: The potential of using various multivariate analysis methods for classification of fluorescence spectra acquired in vivo from laryngeal tissues in Patients was investigated. Study Design/Materials and Methods: Autofluorescence spectra were measured on 29 normal tissue sites and 25 laryngeal lesions using 337-nm excitation. Four different multivariate analysis schemes were applied. Laryngeal fluorescence spectra from patients who had been administered F-aminolevulinic acid (ALA) were obtained using 405-nm excitation and were classified using partial least squares discriminant analysis (PLS-DA). Results: For autofluorescence spectra, logistic regression based on principal component analysis (PCA) or PLS, or PLS-DA all resulted in sensitivities and specificities around 90% for lesion vs. normal. Using ALA and 405-nm excitation gave a sensitivity of 100% and a specificity of 69%. Conclusion: Multivariate analysis of fluorescence spectra could allow classification of laryngeal lesions in vivo with high sensitivity and specificity. PLS performs at least as well as PCA, and PLS-DA performs as well as logistic regression techniques on these data.}}, author = {{Eker, Charlotta and Rydell, Roland and Svanberg, Katarina and Andersson-Engels, Stefan}}, issn = {{0196-8092}}, keywords = {{in vivo diagnosis; larynx; laser-induced fluorescence; partial least squares (PLS); spectroscopy; tissue characterization; multivariate analysis}}, language = {{eng}}, number = {{3}}, pages = {{259--266}}, publisher = {{Wiley-Liss Inc.}}, series = {{Lasers in Surgery and Medicine}}, title = {{Multivariate analysis of laryngeal fluorescence spectra recorded in vivo}}, url = {{https://lup.lub.lu.se/search/files/4820692/2370210.pdf}}, doi = {{10.1002/lsm.1048}}, volume = {{28}}, year = {{2001}}, }