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- Jin-Ming Cao, Jian-Qiong Yang, Zhi-Qiang Ming, Jia-Long Wu, Li-Qin Yang, Tian-Wu Chen, Rui Li, Jing Ou, Xiao-Ming Zhang, Qi-Wen Mu, Hong-Jun Li, and Jiani Hu.
- Sichuan Key Laboratory of Medical Imaging, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan, China; Department of Radiology, Nanchong Central Hospital/Second School of Clinical Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan, China.
- Eur J Radiol. 2020 Sep 1; 130: 109201.
PurposeTo build a radiomics model of liver contrast-enhanced computed tomography (CT) to predict hepatic encephalopathy secondary to Hepatitis B related cirrhosis.Materials And MethodsThis study consisted of 304 consecutive patients with first-diagnosed hepatitis B related cirrhosis. 212 and 92 patients were randomly computer-generated into training and testing cohorts, among which 38 and 21 patients endured HE, respectively. 356 radiomics features of liver were extracted from portal venous-phase CT data, and 3 clinical features were collected from medical record. After data were standardized by Z-score, we used least absolute shrinkage and selection operator to choose useful radiomics features. Ultimately, three predictive models including a radiomics model, a clinical model and an integrated model of radiomics and clinical features were built by analysis of R-software. Predictive performance was tested by multivariable logistic regression, and evaluated by area under receiver-operating characteristic curve (AUC), and accuracy.Results19 radiomics features of liver CT were selected. The selected radiomics features and 3 relevant clinical features were applied to develop a radiomics model, a clinical model, and an integrated model of both radiomics and clinical features. The integrated model showed better performance than the radiomics model or clinical model to predict HE (AUC = 0.94 vs. 0.91 or 0.76, and 0.87 vs. 0.86 or 0.73; accuracy = 0.93 vs. 0.89 or 0.83, and 0.83 vs. 0.84 or 0.77) in the training and testing cohorts, respectively.ConclusionThe integrated model of radiomics and clinical features could well predict HE secondary to hepatitis B related cirrhosis.Copyright © 2020 Elsevier B.V. All rights reserved.
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