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• Clinical Article •
Value of MRI radiomics in predicting molecular subtypes of invasive breast carcinoma of no special type
ZHANG Dingyi  HUANG Xiaohua  SHEN Mengyi  ZHANG Li  HE Xin 

Cite this article as: ZHANG D Y, HUANG X H, SHEN M Y, et al. Value of MRI radiomics in predicting molecular subtypes of invasive breast carcinoma of no special type[J]. Chin J Magn Reson Imaging, 2024, 15(3): 100-106. DOI:10.12015/issn.1674-8034.2024.03.017.


[Abstract] Objective To investigate the clinical value of MRI radiomics in predicting Luminal and non-Luminal subtypes of invasive breast carcinoma of no special type.Materials and Methods A total of 149 cases with pathologically confirmed invasive breast carcinoma of no special type from April 2021 to December 2022 were retrospectively collected according to the inclusion and exclusion criteria, and all of them underwent non-contrast MRI scanning and contrast-enhanced scanning before treatment. Clinical and pathological data of all enrolled patients were collected. Patients were classified into Luminal subtype (n=90) and non-luminal subtype (n=59) based on the expression of estrogen receptor (ER) and progesterone receptor (PR). They were divided into training group (n=104) and test group (n=45) in a ratio of 7∶3,randomly. Screened the optimal features of radiomics from the extracted data, and three prediction models were established based on the random forest method, namely DWI model, DCE model, and DWI combining DCE model. The prediction performance of the models was evaluated by receiver operating characteristic (ROC) curve and the area under the curve (AUC). The DeLong test was used to compare the prediction performance of different models.Results There were no significant differences in the clinicopathological features (age, ER status, PR status, menopausal status, lymph node metastasis) between Luminal and non-Luminal groups, training group and test group (P>0.05). The AUCs of DWI model, DCE model and joint model were 0.859, 0.839 and 0.903 in the training group. In the test group, the AUCs were 0.722, 0.798 and 0.821 respectively. The DeLong test showed that the prediction efficacy of the DCE model and the joint model in the training group were statistically significant (P=0.03), but there was no statistically significant difference in the prediction efficacy among the three models (P>0.05).Conclusions The model constructed based on MRI radiomics can better predict the luminal and non-luminal subtypes of invasive breast carcinoma of no special type, and can help the decision-making of clinical treatment options for invasive breast carcinoma of no special type.
[Keywords] breast cancer；magnetic resonance imaging；molecular subtype；radiomics；joint model

ZHANG Dingyi   HUANG Xiaohua*   SHEN Mengyi   ZHANG Li   HE Xin  

Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China

Corresponding author: HUANG X H, E-mail: 15082797553@163.com

Conflicts of interest   None.

Received  2023-09-07
Accepted  2024-02-23
DOI: 10.12015/issn.1674-8034.2024.03.017
Cite this article as: ZHANG D Y, HUANG X H, SHEN M Y, et al. Value of MRI radiomics in predicting molecular subtypes of invasive breast carcinoma of no special type[J]. Chin J Magn Reson Imaging, 2024, 15(3): 100-106. DOI:10.12015/issn.1674-8034.2024.03.017.

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