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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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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. |
format | Online Article Text |
id | pubmed-9129958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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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