Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status
Abstract 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 d...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-10-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-45079-2 |
| _version_ | 1797452997147492352 |
|---|---|
| author | Xiaojun Li Zhichang Fan Hongnan Jiang Jinliang Niu Wenjin Bian Chen Wang Ying Wang Runmei Zhang Hui Zhang |
| author_facet | Xiaojun Li Zhichang Fan Hongnan Jiang Jinliang Niu Wenjin Bian Chen Wang Ying Wang Runmei Zhang Hui Zhang |
| author_sort | Xiaojun Li |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-09T15:16:28Z |
| format | Article |
| id | doaj.art-51b49d849878463095f76560374db710 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:16:28Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-51b49d849878463095f76560374db7102023-11-26T13:03:59ZengNature PortfolioScientific Reports2045-23222023-10-0113111010.1038/s41598-023-45079-2Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression statusXiaojun Li0Zhichang Fan1Hongnan Jiang2Jinliang Niu3Wenjin Bian4Chen Wang5Ying Wang6Runmei Zhang7Hui Zhang8Department of Medical Imaging, Shanxi Medical UniversityDepartment of Medical Imaging, Shanxi Medical UniversityDepartment of Breast Surgery, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen CenterDepartment of Radiology, The 2nd Affiliated Hospital of Shanxi Medical UniversityDepartment of Medical Imaging, Shanxi Medical UniversityDepartment of Pathology, The 2nd Affiliated Hospital of Shanxi Medical UniversityDepartment of Pathology, The 2nd Affiliated Hospital of Shanxi Medical UniversityDepartment of Radiology, The 2nd Affiliated Hospital of Shanxi Medical UniversityDepartment of Radiology, First Hospital of Shanxi Medical UniversityAbstract 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.https://doi.org/10.1038/s41598-023-45079-2 |
| spellingShingle | Xiaojun Li Zhichang Fan Hongnan Jiang Jinliang Niu Wenjin Bian Chen Wang Ying Wang Runmei Zhang Hui Zhang Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status Scientific Reports |
| 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 |
| url | https://doi.org/10.1038/s41598-023-45079-2 |
| work_keys_str_mv | AT xiaojunli syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus AT zhichangfan syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus AT hongnanjiang syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus AT jinliangniu syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus AT wenjinbian syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus AT chenwang syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus AT yingwang syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus AT runmeizhang syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus AT huizhang syntheticmriinbreastcancerdifferentiatingbenignfrommalignantlesionsandpredictingimmunohistochemicalexpressionstatus |