AUTHOR=Xue Beihui , Wu Sunjie , Zheng Minghua , Jiang Huanchang , Chen Jun , Jiang Zhenghao , Tian Tian , Tu Yifan , Zhao Huanhu , Shen Xian , Ramen Kuvaneshan , Wu Xiuling , Zhang Qiyu , Zeng Qiqiang , Zheng Xiangwu 

TITLE=Development and Validation of a Radiomic-Based Model for Prediction of Intrahepatic Cholangiocarcinoma in Patients With Intrahepatic Lithiasis Complicated by Imagologically Diagnosed Mass

JOURNAL=Frontiers in Oncology

VOLUME=Volume 10 - 2020

YEAR=2021

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2020.598253

DOI=10.3389/fonc.2020.598253

ISSN=2234-943X

ABSTRACT=Background: This study was conducted in order to develop and validate a radiomics model for predicting intrahepatic cholangiocarcinoma (ICC) in patients with intrahepatic lithiasis (IHL) complicated by imagologically-diagnosed mass (IM).
Methods: A radiomics model was developed in a training cohort of 96 patients with IHL-IM between January 2005 and July 2019. Radiomics features were extracted from arterial phase computed tomography (CT) scans. The radiomics score (rad-score) based on radiomics features, was built by logistic regression after using the least absolute shrinkage and selection operator (LASSO) method. The rad-score and other independent predictors were incorporated into a novel comprehensive model. The performance of the Model was determined by its discrimination, calibration, and clinical usefulness. The model was externally validated in 35 consecutive patients.
Results: The rad-score was able to discriminate ICC from IHL in both the training group (AUC 0.829, sensitivity 0.868, specificity 0.635, and accuracy 0.723) and the validation group (AUC 0.879, sensitivity 0.824, specificity 0.778, and accuracy 0.800). Furthermore, the comprehensive model that combined rad-score and clinical features was great in predicting IHL-ICC (AUC 0.902, sensitivity 0.771, specificity 0.923, and accuracy 0.862).
Conclusions: The radiomics-based model holds promise as a novel and accurate tool for predicting IHL-ICC, which can identify lesions in IHL timely for hepatectomy or avoid unnecessary surgical resection.