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CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery

OBJECTIVE: To investigate the diagnostic value of computed tomography (CT) combined with multiparametric magnetic resonance imaging (mpMRI) for preoperative differentiation of non-small-cell lung cancer (NSCLC). METHODS: CT and MRI imaging data were collected from all patients with squamous lung can...

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Autores principales: Li, Xinwen, Wang, Xiaoyan, Li, Qing, Bai, Lijie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129958/
https://www.ncbi.nlm.nih.gov/pubmed/35655730
http://dx.doi.org/10.1155/2022/8207301
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author Li, Xinwen
Wang, Xiaoyan
Li, Qing
Bai, Lijie
author_facet Li, Xinwen
Wang, Xiaoyan
Li, Qing
Bai, Lijie
author_sort Li, Xinwen
collection PubMed
description OBJECTIVE: To investigate the diagnostic value of computed tomography (CT) combined with multiparametric magnetic resonance imaging (mpMRI) for preoperative differentiation of non-small-cell lung cancer (NSCLC). METHODS: CT and MRI imaging data were collected from all patients with squamous lung cancer and adenocarcinoma admitted to our hospital from June 2019 to December 2020 (286 cases). ROC curves were plotted to evaluate the performance of CT, mpMRI, and CT combined with mpMRI to differentiate pathological subtypes of NSCLC. Univariate and multivariate regression were used to be independent predictors of pathological subtypes of NSCLC. RESULTS: ROC curves showed that CT combined with mpMRI had the largest area under the curve, followed by mpMRI and CT successively. Univariate regression analysis showed that gender, smoking, tumor size, morphology, marginal lobulation, marginal burr, bronchial truncation sign, and vascular convergence sign were factors influencing the pathological subtype of NSCLC. Multivariate regression analysis suggested the fact that gender, tumor size, morphology, marginal lobulation, bronchial truncation, and vascular convergence sign are likely the independent predictors of NSCLC pathological subtypes. CONCLUSIONS: CT combined with mpMRI can effectively distinguish NSCLC pathological subtypes, which is worthy of clinical application.
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spelling pubmed-91299582022-06-01 CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery Li, Xinwen Wang, Xiaoyan Li, Qing Bai, Lijie Contrast Media Mol Imaging Research Article OBJECTIVE: To investigate the diagnostic value of computed tomography (CT) combined with multiparametric magnetic resonance imaging (mpMRI) for preoperative differentiation of non-small-cell lung cancer (NSCLC). METHODS: CT and MRI imaging data were collected from all patients with squamous lung cancer and adenocarcinoma admitted to our hospital from June 2019 to December 2020 (286 cases). ROC curves were plotted to evaluate the performance of CT, mpMRI, and CT combined with mpMRI to differentiate pathological subtypes of NSCLC. Univariate and multivariate regression were used to be independent predictors of pathological subtypes of NSCLC. RESULTS: ROC curves showed that CT combined with mpMRI had the largest area under the curve, followed by mpMRI and CT successively. Univariate regression analysis showed that gender, smoking, tumor size, morphology, marginal lobulation, marginal burr, bronchial truncation sign, and vascular convergence sign were factors influencing the pathological subtype of NSCLC. Multivariate regression analysis suggested the fact that gender, tumor size, morphology, marginal lobulation, bronchial truncation, and vascular convergence sign are likely the independent predictors of NSCLC pathological subtypes. CONCLUSIONS: CT combined with mpMRI can effectively distinguish NSCLC pathological subtypes, which is worthy of clinical application. Hindawi 2022-05-17 /pmc/articles/PMC9129958/ /pubmed/35655730 http://dx.doi.org/10.1155/2022/8207301 Text en Copyright © 2022 Xinwen Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Xinwen
Wang, Xiaoyan
Li, Qing
Bai, Lijie
CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery
title CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery
title_full CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery
title_fullStr CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery
title_full_unstemmed CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery
title_short CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery
title_sort ct combined with multiparameter mri in differentiating pathological subtypes of non-small-cell lung cancer before surgery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129958/
https://www.ncbi.nlm.nih.gov/pubmed/35655730
http://dx.doi.org/10.1155/2022/8207301
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