A Radiomics-based Approach for Predicting Early Recurrence in Intrahepatic Cholangiocarcinoma after Surgical Resection: A Multicenter Study.

Abstract

This work aimed to develop a noninvasive and reliable computed tomography (CT)-based imaging biomarker to predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICC) via radiomics analysis. In this retrospective study, a total of 177 ICC patients were enrolled from three independent hospitals. Radiomic features were extracted on CT images, then 11 feature selection algorithms and 4 classifiers were to conduct a multi-strategy radiomics modeling. Six established radiomics models were selected as stable ones by robustness-based rule. Among those models, Max-Relevance Min-Redundancy (MRMR) combined with Gradient Boosting Machine (GBM) yielded the highest areas under the receiver operating characteristics curve (AUCs) of 0.802 (95% confidence interval [CI]: 0.727-0.876) and 0.781 (95% CI: 0.655-0.907) in the training and test cohorts, respectively. To evaluate the generalization of the developed radiomics model, stratification analysis was performed regarding different centers. The MRMR-GBM-based model manifested good generalization with comparable AUCs in each hospital (p > 0.05 for paired comparison). Thus, the MRMR-GBM-based model could offer a potential imaging biomarker to assist the prediction of ER in ICC in a noninvasive manner.Clinical Relevance-The proposed radiomics model achieved satisfactory accuracy and good generalization ability in predicting ER in ICC, which might assist personalized surveillance and clinical treatment strategy making.

• Authors: Xiaohan Hao, Bing Liu, Xiaofei Hu, Jingwei Wei, Yuqi Han, Xianchuang Liu, Zhiyu Chen, Jiaping Li, Jie Bai, Yongliang Chen, Jian Wang, Meng Niu, Jie Tian
• Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Annu Int Conf IEEE Eng Med Biol Soc) Vol. 2021 Pg. 3659-3662 (11 2021) ISSN: 2694-0604 [Electronic] United States
• PMID: 34892030 (Publication Type: Journal Article, Multicenter Study, Research Support, Non-U.S. Gov't)

Topics

• Bile Duct Neoplasms (diagnostic imaging, surgery)
• Bile Ducts, Intrahepatic (diagnostic imaging, surgery)
• Cholangiocarcinoma (diagnostic imaging, surgery)
• Humans
• Retrospective Studies
• Tomography, X-Ray Computed