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• Clinical Article •
The value of multi-parametric MRI radiomics model in predicting lymph node metastasis of pancreatic ductal adenocarcinoma
ZENG Piao'e  QU Chao  CUI Jingjing  XIU Dianrong  LIU Jianyu  YUAN Huishu 

Cite this article as: ZENG P E, QU C, CUI J J, et al. The value of multi-parametric MRI radiomics model in predicting lymph node metastasis of pancreatic ductal adenocarcinoma[J]. Chin J Magn Reson Imaging, 2024, 15(3): 114-121. DOI:10.12015/issn.1674-8034.2024.03.019.


[Abstract] Objective A multi-parametric MRI radiomics model was constructed by combining the radiomics features of conventional MRI and apparent diffusion coefficient (ADC) map to predict lymph node metastasis (LNM) in pancreatic ductal adenocarcinoma (PDAC), and the prediction performance was compared with the established conventional MRI radiomics model and clinical model, to explore the added value of ADC map radiomics.Methods and Materials A total of 218 patients with PDAC were randomly divided into a training cohort and a validation cohort at a ratio of 7∶3. Clinical and conventional imaging features were used to construct the clinical imaging model. Then the radiomics features were extracted based on conventional MRI images (T1WI, T2WI, arterial phase images and portal venous phase images) and ADC maps. Least absolute shrinkage and selection operator was used to select the most relevant features of LNM in the training cohort for model construction. Radiomics models based on conventional MRI images (represented as radiomics model 1) and radiomics models combined with conventional MRI images and ADC maps (represented as radiomics model 2) were constructed. The area under the curve (AUC) of receiver operator characteristic was used to evaluate the prediction performance of the models. DeLong validation was used to compare the difference of AUC values between models. The calibration curve was used to evaluate the accuracy of the model. The clinical value of the model was evaluated by decision curve analysis.Results The AUC values of clinical and radiographic model, radiomics model 1 and radiomics model 2 for preoperative prediction of LNM in the training and validation cohorts were 0.741 and 0.674, 0.818 and 0.702, 0.854 and 0.839, respectively. The AUC value of radiomics model 2 for preoperative prediction of LNM was significantly higher than that of the clinical and radiographic model (P=0.009 in the training cohort; P=0.023 in the validation cohort) and radiomics model 1 (P=0.044 in the training cohort; P=0.041 in the validation cohort). The prediction performance of radiomics model 1 was not significantly different from that of the clinical radiographic model (P=0.095 in the training cohort; P=0.759 in the validation cohort). The calibration curves of the three models showed good agreement between the predicted values and the actual values. Decision curve analysis curve showed that radiomics model 2 had a higher net benefit than radiomics model 1 and clinical imaging model.Conclusions The multi-parametric MRI radiomics model by combining conventional MRI and ADC map radiomics can improve the diagnostic efficiency of predicting LNM of PDAC, which is significantly better than the conventional MRI radiomics model and clinical-radiographic model.
[Keywords] pancreatic ductal adenocarcinoma；lymph node metastasis；radiomics；magnetic resonance imaging；apparent diffusion coefficient

ZENG Piao'e1   QU Chao2   CUI Jingjing3   XIU Dianrong2   LIU Jianyu1   YUAN Huishu1*  

1 Department of Radiology, Peking University Third Hospital, Beijing 100191, China

2 Department of General Surgery, Peking University Third Hospital, Beijing 100191, China

3 Department of Research and Development, United Imaging Intelligence (Beijing), Beijing 100094, China

Corresponding author: YUAN H S, E-mail: huishuy@bjmu.edu.cn

Conflicts of interest   None.

Received  2023-10-27
Accepted  2024-02-23
DOI: 10.12015/issn.1674-8034.2024.03.019
Cite this article as: ZENG P E, QU C, CUI J J, et al. The value of multi-parametric MRI radiomics model in predicting lymph node metastasis of pancreatic ductal adenocarcinoma[J]. Chin J Magn Reson Imaging, 2024, 15(3): 114-121. DOI:10.12015/issn.1674-8034.2024.03.019.

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