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. 2023 Oct 20;13(1):17978.
doi: 10.1038/s41598-023-45079-2.

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status

Xiaojun Li #  1   2 , Zhichang Fan #  1 , Hongnan Jiang  3 , Jinliang Niu  4 , Wenjin Bian  1 , Chen Wang  5 , Ying Wang  5 , Runmei Zhang  4 , Hui Zhang  6
Affiliations

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status

Xiaojun Li et al. Sci Rep. .

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Flowchart showing the patient selection process to form the study sample.
Figure 2
Figure 2
ROC curves based on SyMRI and ADC values for differentiating between benign and malignant breast lesions.
Figure 3
Figure 3
Images before and after enhancement of a patient who was confirmed to have intraductal papilloma. The DCE curve showed a plateau, and the average ADC value was 1.153 × 10−3 mm2/s. The lesion was classified as BI-RADS 4 preoperatively. The lesion’s SD of PD-Pre, T2-Gd, and SD of T1-Gd were 4.5 ms, 80 ms, and 1444 ms, respectively, and the lesion was diagnosed as benign by the model combining SyMRI and ADC values.
Figure 4
Figure 4
Images before and after enhancement of a patient who was confirmed to have invasive ductal carcinoma. The DCE curve showed a plateau, and the average ADC value was 1.119 × 10−3 mm2/s; the lesion was classified as BI-RADS 4 preoperatively. The lesion’s SD of PD-Pre, T2-Gd, and SD of T1-Gd were 1.8 ms, 109 ms, and 2579 ms, respectively, and the lesion was diagnosed as malignant by the model combining SyMRI and ADC.
Figure 5
Figure 5
ROC curves based on SyMRI for predicting the expression of IHC markers including AR, ER, PR, Her-2, P53, and Ki-67.
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