%0 Journal Article
%T CT-Based Radiomics Nomogram: A Potential Tool for Differentiating Hepatocellular Adenoma From Hepatocellular Carcinoma in the Noncirrhotic Liver.
%A Nie P
%A Wang N
%A Pang J
%A Yang G
%A Duan S
%A Chen J
%A Xu W
%J Acad Radiol
%V 28
%N 6
%D 06 2021
%M 32386828
%F 5.482
%R 10.1016/j.acra.2020.04.027
%X To evaluate the value of a radiomics nomogram for preoperative differentiating hepatocellular adenoma (HCA) from hepatocellular carcinoma (HCC) in the noncirrhotic liver.<BR>One hundred and thirty-one patients with HCA (n = 46) and HCC (n = 85) were divided into a training set (n = 93) and a test set (n = 38). Clinical data and CT findings were analyzed. Radiomics features were extracted from the triphasic contrast CT images. A radiomics signature was constructed with the least absolute shrinkage and selection operator algorithm and a radiomics score was calculated. Combined with the radiomics score and independent clinical factors, a radiomics nomogram was developed by multivariate logistic regression analysis. The performance of the radiomics nomogram was assessed by calibration, discrimination and clinical usefulness.<BR>Gender, age, and enhancement pattern were the independent clinical factors. Three thousand seven hundred and sixty-eight features were extracted and reduced to 7 features as the optimal discriminators to build the radiomics signature. The radiomics nomogram (area under the curve [AUC], 0.96; 95% confidence interval [CI], 0.93-0.99) and the clinical factors model (AUC, 0.93; 95%CI, 0.88-0.99) showed better discrimination capability (p = 0.001 and 0.047) than the radiomics signature (AUC, 0.83; 95%CI, 0.74-0.92) in the training set. In the test set, the radiomics nomogram (AUC, 0.94; 95%CI, 0.87-1.00) performed better (p = 0.013) than the radiomics signature (AUC, 0.75; 95%CI, 0.59-0.91). Decision curve analysis showed the radiomics nomogram outperformed the clinical factors model and the radiomics signature in terms of clinical usefulness.<BR>The CT-based radiomics nomogram has the potential to accurately differentiate HCA from HCC in the noncirrhotic liver.