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• Clinical Article •
Preoperative predicting lymphov-ascular space invasion in endometrial carcinoma by nomogram based on mpMRI radiomics
PENG Yongjia  LIU Xiaowen  TANG Xue  LUO Yan  JIANG Changsi  GONG Jingshan 

Cite this article as: Peng YJ, Liu XW, Tang X, et al. Preoperative predicting lymphov-ascular space invasion in endometrial carcinoma by nomogram based on mpMRI radiomics[J]. Chin J Magn Reson Imaging, 2022, 13(7): 61-67. DOI:10.12015/issn.1674-8034.2022.07.011.


[Abstract] Objective To investigate the value of multiparametric magnetic resonance imaging (mpMRI) radiomics in predicting lymphatic vascular space invasion (LVSI) in endometrial cancer (EC).Materials and Methods The clinical data of 202 patients with EC confirmed by surgery and pathology were retrospectively collected. All patients underwent pelvic mpMRI before operation,and randomly divided into training set and testing set according to ratio of 7∶3. Using the open-source ITK-SNAP software draw the outline of region of interest (ROI). EC radiomics features were extracted by the Pyradiomics software from mpMRI images. The association of clinicopathological characteristics and radiomics features with LVSI were evaluated by univariate analysis. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the radiomics features and calculate rad-score. Multivariate logistic regression was used to screen for independent risk factors for LVSI. Using the R language for modeling and drawing the nomograms, and the prediction efficiency of the model was evaluated by C-index. To compare the prediction efficacy of the radiomics and the nomogram model for LVSI.Results Thirteen radiomics features were selected from 321 by LASSO regression, and calculated Rad-score. Univariate and multivariate logistic regression analyses found that the independent risk factors of LVSI were age, pathological grade, and Rad-score. The C-index of the nomogram that was constructed with the combined LVSI risk factors was 0.871 (95% CI: 0.803-0.940) and 0.810 (95% CI: 0.698-0.917) in the training set and the validation set, respectively. The C-index of the radiomics model in the training set and verification set was 0.854 (95% CI: 0.784-0.925) and 0.756 (95% CI: 0.619-0.892) respectively. Both the nomogram and the radiomics model had a good prediction efficiency for LVSI, and the nomogram was higher than the radiomics model.Conclusions The radiomics nomogram based on mpMRI can achieve a high diagnostic efficacy in preoperative evaluation of EC LVSI.
[Keywords] endometrial carcinoma；lymphatic vascular space invasion；multi-parameter magnetic resonance imaging；radiomics；nomogram

PENG Yongjia1   LIU Xiaowen1   TANG Xue2   LUO Yan2   JIANG Changsi2   GONG Jingshan2*  

1 The Second Clinical Medical College, Jinan University, Shenzhen 518020, China

2 Department of Radiology, Shenzhen People's Hospital, the Second Clinical Medical College of Jinan University, Shenzhen 518020, China

Gong JS, E-mail: jshgong@sina.com

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 82172026).
Received  2022-03-28
Accepted  2022-06-24
DOI: 10.12015/issn.1674-8034.2022.07.011
Cite this article as: Peng YJ, Liu XW, Tang X, et al. Preoperative predicting lymphov-ascular space invasion in endometrial carcinoma by nomogram based on mpMRI radiomics[J]. Chin J Magn Reson Imaging, 2022, 13(7): 61-67. DOI:10.12015/issn.1674-8034.2022.07.011.

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