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Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes
OBJECTIVES: To assess breast cancer receptor status and molecular subtypes by using the CAIPIRINHA-Dixon-TWIST-VIBE and readout-segmented echo-planar diffusion weighted imaging techniques. METHODS: A total of 165 breast cancer patients were retrospectively recruited. Patient age, estrogen receptor,...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481692/ https://www.ncbi.nlm.nih.gov/pubmed/34604024 http://dx.doi.org/10.3389/fonc.2021.628824 |
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author | Yang, Zhiqi Chen, Xiaofeng Zhang, Tianhui Cheng, Fengyan Liao, Yuting Chen, Xiangguan Dai, Zhuozhi Fan, Weixiong |
author_facet | Yang, Zhiqi Chen, Xiaofeng Zhang, Tianhui Cheng, Fengyan Liao, Yuting Chen, Xiangguan Dai, Zhuozhi Fan, Weixiong |
author_sort | Yang, Zhiqi |
collection | PubMed |
description | OBJECTIVES: To assess breast cancer receptor status and molecular subtypes by using the CAIPIRINHA-Dixon-TWIST-VIBE and readout-segmented echo-planar diffusion weighted imaging techniques. METHODS: A total of 165 breast cancer patients were retrospectively recruited. Patient age, estrogen receptor, progesterone receptor, human epidermal growth factorreceptor-2 (HER-2) status, and the Ki-67 proliferation index were collected for analysis. Quantitative parameters (K(trans), V(e), K(ep)), semiquantitative parameters (W(-in), W(-out), TTP), and apparent diffusion coefficient (ADC) values were compared in relation to breast cancer receptor status and molecular subtypes. Statistical analysis were performed to compare the parameters in the receptor status and molecular subtype groups.Multivariate analysis was performed to explore confounder-adjusted associations, and receiver operating characteristic curve analysis was used to assess the classification performance and calculate thresholds. RESULTS: Younger age (<49.5 years, odds ratio (OR) =0.95, P=0.004), lower K(ep) (<0.704,OR=0.14, P=0.044),and higher TTP (>0.629 min, OR=24.65, P=0.011) were independently associated with progesterone receptor positivity. A higher TTP (>0.585 min, OR=28.19, P=0.01) was independently associated with estrogen receptor positivity. Higher K(ep) (>0.892, OR=11.6, P=0.047), lower TTP (<0.582 min, OR<0.001, P=0.004), and lower ADC (<0.719 ×10(-3) mm(2)/s, OR<0.001, P=0.048) had stronger independent associations with triple-negative breast cancer (TNBC) compared to luminal A, and those parameters could differentiate TNBC from luminal A with the highest AUC of 0.811. CONCLUSIONS: K(ep) and TTP were independently associated with hormone receptor status. In addition, the K(ep), TTP, and ADC values had stronger independent associations with TNBC than with luminal A and could be used as imaging biomarkers for differentiate TNBC from Luminal A. |
format | Online Article Text |
id | pubmed-8481692 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84816922021-10-01 Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes Yang, Zhiqi Chen, Xiaofeng Zhang, Tianhui Cheng, Fengyan Liao, Yuting Chen, Xiangguan Dai, Zhuozhi Fan, Weixiong Front Oncol Oncology OBJECTIVES: To assess breast cancer receptor status and molecular subtypes by using the CAIPIRINHA-Dixon-TWIST-VIBE and readout-segmented echo-planar diffusion weighted imaging techniques. METHODS: A total of 165 breast cancer patients were retrospectively recruited. Patient age, estrogen receptor, progesterone receptor, human epidermal growth factorreceptor-2 (HER-2) status, and the Ki-67 proliferation index were collected for analysis. Quantitative parameters (K(trans), V(e), K(ep)), semiquantitative parameters (W(-in), W(-out), TTP), and apparent diffusion coefficient (ADC) values were compared in relation to breast cancer receptor status and molecular subtypes. Statistical analysis were performed to compare the parameters in the receptor status and molecular subtype groups.Multivariate analysis was performed to explore confounder-adjusted associations, and receiver operating characteristic curve analysis was used to assess the classification performance and calculate thresholds. RESULTS: Younger age (<49.5 years, odds ratio (OR) =0.95, P=0.004), lower K(ep) (<0.704,OR=0.14, P=0.044),and higher TTP (>0.629 min, OR=24.65, P=0.011) were independently associated with progesterone receptor positivity. A higher TTP (>0.585 min, OR=28.19, P=0.01) was independently associated with estrogen receptor positivity. Higher K(ep) (>0.892, OR=11.6, P=0.047), lower TTP (<0.582 min, OR<0.001, P=0.004), and lower ADC (<0.719 ×10(-3) mm(2)/s, OR<0.001, P=0.048) had stronger independent associations with triple-negative breast cancer (TNBC) compared to luminal A, and those parameters could differentiate TNBC from luminal A with the highest AUC of 0.811. CONCLUSIONS: K(ep) and TTP were independently associated with hormone receptor status. In addition, the K(ep), TTP, and ADC values had stronger independent associations with TNBC than with luminal A and could be used as imaging biomarkers for differentiate TNBC from Luminal A. Frontiers Media S.A. 2021-09-16 /pmc/articles/PMC8481692/ /pubmed/34604024 http://dx.doi.org/10.3389/fonc.2021.628824 Text en Copyright © 2021 Yang, Chen, Zhang, Cheng, Liao, Chen, Dai and Fan https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Yang, Zhiqi Chen, Xiaofeng Zhang, Tianhui Cheng, Fengyan Liao, Yuting Chen, Xiangguan Dai, Zhuozhi Fan, Weixiong Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes |
title | Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes |
title_full | Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes |
title_fullStr | Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes |
title_full_unstemmed | Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes |
title_short | Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes |
title_sort | quantitative multiparametric mri as an imaging biomarker for the prediction of breast cancer receptor status and molecular subtypes |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481692/ https://www.ncbi.nlm.nih.gov/pubmed/34604024 http://dx.doi.org/10.3389/fonc.2021.628824 |
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