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Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis
PURPOSE: This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis. MATERIALS AND METHODS: Approval from the institutional revie...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5768409/ https://www.ncbi.nlm.nih.gov/pubmed/29371992 http://dx.doi.org/10.18632/oncotarget.22267 |
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author | Xu, Tingting Zhang, Lin Xu, Hong Kang, Sifeng Xu, Yali Luo, Xiaoyu Hua, Ting Tang, Guangyu |
author_facet | Xu, Tingting Zhang, Lin Xu, Hong Kang, Sifeng Xu, Yali Luo, Xiaoyu Hua, Ting Tang, Guangyu |
author_sort | Xu, Tingting |
collection | PubMed |
description | PURPOSE: This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis. MATERIALS AND METHODS: Approval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis. RESULTS: Low-risk tumors showed significantly lower K(trans) and K(ep) values (t = 2.065, P = 0.043 and t = 3.548, P = 0.001, respectively) and higher ADC value (t = 4.713, P = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression (P = 0.000), lower MMP-9 expression (P = 0.001), and lower microvessel density (MVD) values (P = 0.008) compared with non-low-risk breast cancers. K(trans) and K(ep) values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers. CONCLUSIONS: The prediction parameter using K(trans), K(ep), and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis. |
format | Online Article Text |
id | pubmed-5768409 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-57684092018-01-25 Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis Xu, Tingting Zhang, Lin Xu, Hong Kang, Sifeng Xu, Yali Luo, Xiaoyu Hua, Ting Tang, Guangyu Oncotarget Clinical Research Paper PURPOSE: This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis. MATERIALS AND METHODS: Approval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis. RESULTS: Low-risk tumors showed significantly lower K(trans) and K(ep) values (t = 2.065, P = 0.043 and t = 3.548, P = 0.001, respectively) and higher ADC value (t = 4.713, P = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression (P = 0.000), lower MMP-9 expression (P = 0.001), and lower microvessel density (MVD) values (P = 0.008) compared with non-low-risk breast cancers. K(trans) and K(ep) values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers. CONCLUSIONS: The prediction parameter using K(trans), K(ep), and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis. Impact Journals LLC 2017-11-01 /pmc/articles/PMC5768409/ /pubmed/29371992 http://dx.doi.org/10.18632/oncotarget.22267 Text en Copyright: © 2017 Xu et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Clinical Research Paper Xu, Tingting Zhang, Lin Xu, Hong Kang, Sifeng Xu, Yali Luo, Xiaoyu Hua, Ting Tang, Guangyu Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis |
title | Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis |
title_full | Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis |
title_fullStr | Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis |
title_full_unstemmed | Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis |
title_short | Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis |
title_sort | prediction of low-risk breast cancer using quantitative dce-mri and its pathological basis |
topic | Clinical Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5768409/ https://www.ncbi.nlm.nih.gov/pubmed/29371992 http://dx.doi.org/10.18632/oncotarget.22267 |
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