Non-contrast CT radiomics for predicting recurrence of acute pancreatitis
10.13929/j.issn.1003-3289.2025.05.012
- VernacularTitle:基于平扫CT影像组学预测急性胰腺炎复发
- Author:
Bingbing LIN
1
;
Ping YIN
1
;
Fei ZHENG
1
;
Nan HONG
1
Author Information
1. 北京大学人民医院放射科,北京 100044
- Publication Type:Journal Article
- Keywords:
pancreatitis;
recurrence;
tomography,X-ray computed;
radiomics
- From:
Chinese Journal of Medical Imaging Technology
2025;41(5):749-752
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of non-contrast CT radiomics for predicting recurrence of acute pancreatitis(AP).Methods Totally 356 patients with first-episode AP were retrospectively enrolled.The patients were categorized into recurrence group(n=78)and non-recurrence group(n=278)based on whether recurrence after 3 months of complete/near disappearance of symptoms,also divided into training set(n=213)and test set(n=143)at the ratio of 6∶4.For 116 cases who underwent contrast-enhanced CT,taken portal venous phase images as references,ROI of pancreatic parenchyma was manually delineated on non-contrast CT,while SegResNet segmentation model was used for automatic segmentation on non-contrast CT images for the rest 240 cases.The optimal radiomics features were extracted and selected to construct a radiomics model based on YeoJohnson transformer and Bagging decision tree.The receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated to evaluate the efficacy of the obtained model for predicting AP recurrence.Results Totally 2 264 radiomics features were extracted from ROI of pancreatic parenchyma,and finally 4 optimal features were screened.The AUC of radiomics model for predicting recurrence was 0.887 and 0.889 in training set and test set,respectively.Conclusion Non-contrast CT radiomics could be used to effectively predict recurrence of AP.
