Cargando…

Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma

OBJECTIVE: The objective of this study is to evaluate the performance and feasibility of surface-enhanced Raman spectroscopy coupled with a filter membrane and advanced multivariate data analysis on identifying and differentiating benign and malignant thyroid tumors from blood plasma. PATIENTS AND M...

Descripción completa

Detalles Bibliográficos
Autores principales: Liang, Xiaozhou, Miao, Xuchao, Xiao, Weijin, Ye, Qin, Wang, Sisi, Lin, Juqiang, Li, Chao, Huang, Zufang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132009/
https://www.ncbi.nlm.nih.gov/pubmed/32280222
http://dx.doi.org/10.2147/IJN.S233663
_version_ 1783517363555008512
author Liang, Xiaozhou
Miao, Xuchao
Xiao, Weijin
Ye, Qin
Wang, Sisi
Lin, Juqiang
Li, Chao
Huang, Zufang
author_facet Liang, Xiaozhou
Miao, Xuchao
Xiao, Weijin
Ye, Qin
Wang, Sisi
Lin, Juqiang
Li, Chao
Huang, Zufang
author_sort Liang, Xiaozhou
collection PubMed
description OBJECTIVE: The objective of this study is to evaluate the performance and feasibility of surface-enhanced Raman spectroscopy coupled with a filter membrane and advanced multivariate data analysis on identifying and differentiating benign and malignant thyroid tumors from blood plasma. PATIENTS AND METHODS: We proposed a membrane filter SERS technology for the differentiation between benign thyroid tumor and thyroid cancer. That is to say, by using filter membranes with optimal pore size, the blood plasma samples from thyroid tumor patients were pretreated with the macromolecular proteins being filtered out prior to SERS measurement. The SERS spectra of blood plasma ultrafiltrate obtained using filter membranes from 102 patients with thyroid tumors (70 thyroid cancers and 32 benign thyroid tumors) were then analyzed and compared. Two multivariate statistical analyses, principal component analysis-linear discriminate analysis (PCA-LDA) and Lasso-partial least squares-discriminant analysis (Lasso-PLS-DA), were performed on the SERS spectral data after background subtraction and normalization, as well as the first derivative processing, to analyze and compare the differential diagnosis of benign thyroid tumors and thyroid cancer. RESULTS: SERS measurements were performed in blood plasma acquired from a total of 102 thyroid tumor patients (benign thyroid tumor N=32; thyroid cancer N=70). By using filter membranes, the macromolecular proteins in blood plasma were effectively filtered out to yield high-quality SERS spectra. 84.3% discrimination accuracy between benign and malignant thyroid tumor was achieved using PCA-LDA method, while Lasso-PLS-DA yields a discrimination accuracy of 90.2%. CONCLUSION: Our results demonstrate that SERS spectroscopy, coupled with ultrafiltration and multivariate analysis has the potential of providing a non-invasive, rapid, and objective detection and differentiation of benign and malignant thyroid tumors.
format Online
Article
Text
id pubmed-7132009
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-71320092020-04-10 Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma Liang, Xiaozhou Miao, Xuchao Xiao, Weijin Ye, Qin Wang, Sisi Lin, Juqiang Li, Chao Huang, Zufang Int J Nanomedicine Original Research OBJECTIVE: The objective of this study is to evaluate the performance and feasibility of surface-enhanced Raman spectroscopy coupled with a filter membrane and advanced multivariate data analysis on identifying and differentiating benign and malignant thyroid tumors from blood plasma. PATIENTS AND METHODS: We proposed a membrane filter SERS technology for the differentiation between benign thyroid tumor and thyroid cancer. That is to say, by using filter membranes with optimal pore size, the blood plasma samples from thyroid tumor patients were pretreated with the macromolecular proteins being filtered out prior to SERS measurement. The SERS spectra of blood plasma ultrafiltrate obtained using filter membranes from 102 patients with thyroid tumors (70 thyroid cancers and 32 benign thyroid tumors) were then analyzed and compared. Two multivariate statistical analyses, principal component analysis-linear discriminate analysis (PCA-LDA) and Lasso-partial least squares-discriminant analysis (Lasso-PLS-DA), were performed on the SERS spectral data after background subtraction and normalization, as well as the first derivative processing, to analyze and compare the differential diagnosis of benign thyroid tumors and thyroid cancer. RESULTS: SERS measurements were performed in blood plasma acquired from a total of 102 thyroid tumor patients (benign thyroid tumor N=32; thyroid cancer N=70). By using filter membranes, the macromolecular proteins in blood plasma were effectively filtered out to yield high-quality SERS spectra. 84.3% discrimination accuracy between benign and malignant thyroid tumor was achieved using PCA-LDA method, while Lasso-PLS-DA yields a discrimination accuracy of 90.2%. CONCLUSION: Our results demonstrate that SERS spectroscopy, coupled with ultrafiltration and multivariate analysis has the potential of providing a non-invasive, rapid, and objective detection and differentiation of benign and malignant thyroid tumors. Dove 2020-04-01 /pmc/articles/PMC7132009/ /pubmed/32280222 http://dx.doi.org/10.2147/IJN.S233663 Text en © 2020 Liang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Liang, Xiaozhou
Miao, Xuchao
Xiao, Weijin
Ye, Qin
Wang, Sisi
Lin, Juqiang
Li, Chao
Huang, Zufang
Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma
title Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma
title_full Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma
title_fullStr Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma
title_full_unstemmed Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma
title_short Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma
title_sort filter-membrane-based ultrafiltration coupled with surface-enhanced raman spectroscopy for potential differentiation of benign and malignant thyroid tumors from blood plasma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132009/
https://www.ncbi.nlm.nih.gov/pubmed/32280222
http://dx.doi.org/10.2147/IJN.S233663
work_keys_str_mv AT liangxiaozhou filtermembranebasedultrafiltrationcoupledwithsurfaceenhancedramanspectroscopyforpotentialdifferentiationofbenignandmalignantthyroidtumorsfrombloodplasma
AT miaoxuchao filtermembranebasedultrafiltrationcoupledwithsurfaceenhancedramanspectroscopyforpotentialdifferentiationofbenignandmalignantthyroidtumorsfrombloodplasma
AT xiaoweijin filtermembranebasedultrafiltrationcoupledwithsurfaceenhancedramanspectroscopyforpotentialdifferentiationofbenignandmalignantthyroidtumorsfrombloodplasma
AT yeqin filtermembranebasedultrafiltrationcoupledwithsurfaceenhancedramanspectroscopyforpotentialdifferentiationofbenignandmalignantthyroidtumorsfrombloodplasma
AT wangsisi filtermembranebasedultrafiltrationcoupledwithsurfaceenhancedramanspectroscopyforpotentialdifferentiationofbenignandmalignantthyroidtumorsfrombloodplasma
AT linjuqiang filtermembranebasedultrafiltrationcoupledwithsurfaceenhancedramanspectroscopyforpotentialdifferentiationofbenignandmalignantthyroidtumorsfrombloodplasma
AT lichao filtermembranebasedultrafiltrationcoupledwithsurfaceenhancedramanspectroscopyforpotentialdifferentiationofbenignandmalignantthyroidtumorsfrombloodplasma
AT huangzufang filtermembranebasedultrafiltrationcoupledwithsurfaceenhancedramanspectroscopyforpotentialdifferentiationofbenignandmalignantthyroidtumorsfrombloodplasma