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Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer
BACKGROUND: To investigate the correlation between quantitative pharmacokinetic parameters and clinicopathological prognostic biomarkers including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and MiB1 (Ki-67) in patients with breast cancer, the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798285/ https://www.ncbi.nlm.nih.gov/pubmed/35117155 http://dx.doi.org/10.21037/tcr.2019.11.10 |
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author | Yang, Guocai Yang, Jing Xu, Hui Zhang, Qingxin Qi, Yonghong Zhang, Aiju |
author_facet | Yang, Guocai Yang, Jing Xu, Hui Zhang, Qingxin Qi, Yonghong Zhang, Aiju |
author_sort | Yang, Guocai |
collection | PubMed |
description | BACKGROUND: To investigate the correlation between quantitative pharmacokinetic parameters and clinicopathological prognostic biomarkers including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and MiB1 (Ki-67) in patients with breast cancer, the image histogram analysis was performed on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: The reference region model (RRM) was used to calculate the quantitative permeability parameters, including reference region volume transfer constant (K(trans,RR)), the rate constant of tissue of interest (K(ep,TOI)), and the rate constant of reference region (K(ep,RR)). Histogram analysis was performed to compare these parameters between ER/PR/HER2/Ki-67 positive and negative groups. The performance of the histogram parameters K(trans,RR), K(ep,TOI) and K(ep,RR) in differential diagnosis of immunohistochemistry results was conducted by receiver operating characteristic (ROC) curve analysis. RESULTS: All the histogram metrics of K(ep,TOI) significantly differed between ER/PR positive and negative groups (P<0.05). However, K(trans,RR) and K(ep,RR) did not significantly differ between ER/PR positive and negative groups (P>0.05). The 10(th) percentile, energy, entropy and variance of K(trans,RR), and almost all the histogram parameters of K(ep,TOI) except for variance significantly differed between HER2 positive and negative groups (all P<0.05). The energy of K(trans,RR) significantly differed between Ki-67 positive and negative groups (P<0.05). The skewness and energy of K(ep,TOI) showed the highest AUC of 0.977 and 0.879 in differentiating ER/PR status. The energy of K(trans,RR) presented the highest AUC in the differentiation of HER2 and Ki-67. CONCLUSIONS: Histogram analysis on quantitative pharmacokinetic breast parameters using DCE-MRI improves the performance in differentiation of histological phenotypes of breast cancer. |
format | Online Article Text |
id | pubmed-8798285 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-87982852022-02-02 Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer Yang, Guocai Yang, Jing Xu, Hui Zhang, Qingxin Qi, Yonghong Zhang, Aiju Transl Cancer Res Original Article BACKGROUND: To investigate the correlation between quantitative pharmacokinetic parameters and clinicopathological prognostic biomarkers including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and MiB1 (Ki-67) in patients with breast cancer, the image histogram analysis was performed on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: The reference region model (RRM) was used to calculate the quantitative permeability parameters, including reference region volume transfer constant (K(trans,RR)), the rate constant of tissue of interest (K(ep,TOI)), and the rate constant of reference region (K(ep,RR)). Histogram analysis was performed to compare these parameters between ER/PR/HER2/Ki-67 positive and negative groups. The performance of the histogram parameters K(trans,RR), K(ep,TOI) and K(ep,RR) in differential diagnosis of immunohistochemistry results was conducted by receiver operating characteristic (ROC) curve analysis. RESULTS: All the histogram metrics of K(ep,TOI) significantly differed between ER/PR positive and negative groups (P<0.05). However, K(trans,RR) and K(ep,RR) did not significantly differ between ER/PR positive and negative groups (P>0.05). The 10(th) percentile, energy, entropy and variance of K(trans,RR), and almost all the histogram parameters of K(ep,TOI) except for variance significantly differed between HER2 positive and negative groups (all P<0.05). The energy of K(trans,RR) significantly differed between Ki-67 positive and negative groups (P<0.05). The skewness and energy of K(ep,TOI) showed the highest AUC of 0.977 and 0.879 in differentiating ER/PR status. The energy of K(trans,RR) presented the highest AUC in the differentiation of HER2 and Ki-67. CONCLUSIONS: Histogram analysis on quantitative pharmacokinetic breast parameters using DCE-MRI improves the performance in differentiation of histological phenotypes of breast cancer. AME Publishing Company 2020-01 /pmc/articles/PMC8798285/ /pubmed/35117155 http://dx.doi.org/10.21037/tcr.2019.11.10 Text en 2020 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/. |
spellingShingle | Original Article Yang, Guocai Yang, Jing Xu, Hui Zhang, Qingxin Qi, Yonghong Zhang, Aiju Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer |
title | Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer |
title_full | Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer |
title_fullStr | Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer |
title_full_unstemmed | Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer |
title_short | Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer |
title_sort | relationship between histogram metrics of pharmacokinetic parameters of dce-mri and histological phenotype in breast cancer |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798285/ https://www.ncbi.nlm.nih.gov/pubmed/35117155 http://dx.doi.org/10.21037/tcr.2019.11.10 |
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