Radiomics Integrated with Deep Learning Based on Contrast-Enhanced MRI for Predicting Short-Term Efficacy of Drug-Eluting Beads Transarterial Chemoembolization in Hepatocellular Carcinoma from Multicenter Retrospective Study.

Zihan Xi¹, Yuchi Tian², Lulu Liu³, Haiyan Chen³, Xinru Wu³, Temitope Emmanuel Komolafe⁴, Xiaoyun Liang², Jinwu Ren⁵, Yongbo Yang⁶

¹Radiology Department 3, Baoding No.1 Central Hospital, Baoding, Hebei Province, 071000, China.

²Institute of Research and Clinical Innovations, Neusoft Medical Systems Co., Ltd, Shanghai, China.

³Department of Radiology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang , 310022, China.

⁴Collaborative Research Center, Shanghai University of Medicine & Health Sciences, Shanghai, China.

⁵Radiology Department 3, Baoding No.1 Central Hospital, Baoding, Hebei Province, 071000, China. rjwzhanglihong@163.com.

⁶Department of Radiology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang , 310022, China. dryangyb@163.com.

PubMed DOI

Abstract

We aimed to develop and validate a predictive model combining radiomics, deep learning, and clinical features for the preoperative prediction of the short-term efficacy of initial drug-eluting bead transarterial chemoembolization (DEB-TACE) treatment in patients with hepatocellular carcinoma (HCC). This retrospective cohort study included 113 internal and 32 external patients from three centers wi…

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