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Value of preoperative prediction of Ki-67 expression in breast cancer based on DCE-MRI intratumoral combined with peritumoral radiomics model
MING Jie  CHEN Ying  LIU Ying  ZHU Lina  LI Xing 

Cite this article as: Ming J, Chen Y, Liu Y, et al. Value of preoperative prediction of Ki-67 expression in breast cancer based on DCE-MRI intratumoral combined with peritumoral radiomics model[J]. Chin J Magn Reson Imaging, 2022, 13(10): 132-137, 149. DOI:10.12015/issn.1674-8034.2022.10.020.

[Abstract] Objective To explore the value of preoperative prediction of Ki-67 expression status in breast cancer based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and intratumoral combined peritumoral 3D radiomics model.Materials and Methods The data of 312 patients diagnosed with breast cancer in the Affiliated Tumors Hospital of Xinjiang Medical University from January 2019 to January 2022 were retrospectively collected and randomly divided them into training groups (n=250) and validation groups (n=62) according to the ratio of 8∶2. Firstly, doctors adopted 3D Slicer software to extract 3D imaging radiomics features from the 5 mm region in and around stage 2 of DCE-MRI images. Secondly, features were standardized with Z-score, and intra-class correlation coefficient (ICC), Spearman correlation coefficient and least absolute shrinkage and selection operator (LASSO) were used to screen the optimal radiomics features. Thirdly, modelintra, modelperi, modelintra+peri were established by support vector machine (SVM) algorithms to predict the expression status of Ki-67 in breast cancer and were verified by the validation groups. Fourthly, the performance models were assessed by the receiver operating characteristic (ROC) curve and area under the curve (AUC).Results The features of intratumor, peritumor, intratumor+peritumor were extracted 1906, 1906 and 3812 samples respectively, 322, 413 and 762 features were excluded by ICC, and 624, 732 and 1604 were eliminated by Spearman, after that 8, 19 and 16 features were selected by LASSO from the rest of 960, 761 and 1446 features. With comprehensive analysis, the modelintra+peri showed the best prognostic efficacy, with AUC of 0.949 and 0.862 in the training and validation groups respectively. The calibration curve nearly showed the best value of 45%, Hosmer-Lemeshow goodness-of-fit test suggested that the curve of the model fitted the data with high efficiency (P=0.082), decision curve analysis showed better results than other models and benefits in the clinic application.Conclusions The predicting model of Ki-67 was creatively established by DCE-MRI and intratumoral combined peritumoral 3D radiomics model, the research provides accurate personal treatment in the breast cancer.
[Keywords] breast cancer;intratumor;peritumor;Ki-67;prognosis;dynamic contrast-enhanced magnetic resonance imaging;radiomics;magnetic resonance imaging

MING Jie1   CHEN Ying1   LIU Ying2, 3   ZHU Lina1   LI Xing1*  

1 Medical Imaging Center, Affiliated Tumors Hospital of Xinjiang Medical University, Urumqi 830011, China

2 Special Needs Comprehensive Department, Cancer Hospital Affiliated to Xinjiang Medical University, Urumqi 830011, China

3 Oncology Department, People's Hospital of Bachu County, Bachu 843800, China

Li X, E-mail:

Conflicts of interest   None.

Received  2022-06-29
Accepted  2022-10-09
DOI: 10.12015/issn.1674-8034.2022.10.020
Cite this article as: Ming J, Chen Y, Liu Y, et al. Value of preoperative prediction of Ki-67 expression in breast cancer based on DCE-MRI intratumoral combined with peritumoral radiomics model[J]. Chin J Magn Reson Imaging, 2022, 13(10): 132-137, 149.DOI:10.12015/issn.1674-8034.2022.10.020

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