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| Prediction of early recurrence of hepatocellular carcinoma after liver transplantation based on CT radiomics model |
| ZHAO Jingwei1,2, CHEN Xiaoxia2, GUO Xiaodong3, HE Xucheng2, HAN Wenjuan2, YAO Dingming2, LIU Ting2, WANG Guisheng2 |
1. Postgraduate Training Base, The Third Medical Center of Chinese PLA General Hospital, Jinzhou Medical University, Beijing 100039, China;
2. Department of CT, The Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China;
3. The Fifth Medical Center of Chinese PLA General Hospital,Beijing 100039,China |
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Abstract Objective To explore the value of CT radiomics model in predicting early recurrence in patients with hepatocellular carcinoma (HCC) after liver transplantation.Methods A retrospective review of 131 patients with HCC who underwent liver transplantation was performed. And the whole dataset were randomly split into two datasets,a training dataset(92 cases) and a validation dataset(39 cases). Early recurrence was confirmed by postoperative regular follow-up. Three-dimensional tumor segmentation is completed by delineating the tumor margins slice by slice and 1218 features were gengerated. To select features with potential predictive value,The LASSO algorithm was applied. By applying logistic regression,the model for predicting early recurrence after liver transplantation were developed based on the selected features. The performance of the model to predict whether the patients would experience early recurrence was evaluated by the area under the curve (AUC).Results The selected features with potential predictive value were 8.The prediction model showed AUC=0.828 , sensitivity=82.4% , specificity=74.7% in training dataset and AUC=0.856, sensitivity=77.8%, specificity=86.7% in validation dataset.Conclusions The radiomic model based on preoperative enhanced CT images has predictive value for early recurrence of HCC patients after liver transplantation.
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Received: 20 November 2020
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2021, Vol. 32 
