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Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status
To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic co...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589282/ https://www.ncbi.nlm.nih.gov/pubmed/37864025 http://dx.doi.org/10.1038/s41598-023-45079-2 |
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author | Li, Xiaojun Fan, Zhichang Jiang, Hongnan Niu, Jinliang Bian, Wenjin Wang, Chen Wang, Ying Zhang, Runmei Zhang, Hui |
author_facet | Li, Xiaojun Fan, Zhichang Jiang, Hongnan Niu, Jinliang Bian, Wenjin Wang, Chen Wang, Ying Zhang, Runmei Zhang, Hui |
author_sort | Li, Xiaojun |
collection | PubMed |
description | To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values. |
format | Online Article Text |
id | pubmed-10589282 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105892822023-10-22 Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status Li, Xiaojun Fan, Zhichang Jiang, Hongnan Niu, Jinliang Bian, Wenjin Wang, Chen Wang, Ying Zhang, Runmei Zhang, Hui Sci Rep Article To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values. Nature Publishing Group UK 2023-10-20 /pmc/articles/PMC10589282/ /pubmed/37864025 http://dx.doi.org/10.1038/s41598-023-45079-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Li, Xiaojun Fan, Zhichang Jiang, Hongnan Niu, Jinliang Bian, Wenjin Wang, Chen Wang, Ying Zhang, Runmei Zhang, Hui Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status |
title | Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status |
title_full | Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status |
title_fullStr | Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status |
title_full_unstemmed | Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status |
title_short | Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status |
title_sort | synthetic mri in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589282/ https://www.ncbi.nlm.nih.gov/pubmed/37864025 http://dx.doi.org/10.1038/s41598-023-45079-2 |
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