Multi-algorithms analysis for pre-treatment prediction of response to transarterial chemoembolization in hepatocellular carcinoma on multiphase MRI

Multi-algorithms analysis for pre-treatment prediction of response to transarterial chemoembolization in hepatocellular carcinoma on multiphase MRI

Key points DNN and LASSO models performed better than other classifiers in TACE response prediction. CD model achieved an AUC of 0.974 in the training set, superior to other comprehensive models. CD model may serve as a potential tool for the selection of suitable TACE candidates.

Bibliographic Details
Main Authors: Mingzhen Chen, Chunli Kong, Enqi Qiao, Yaning Chen, Weiyue Chen, Xiaole Jiang, Shiji Fang, Dengke Zhang, Minjiang Chen, Weiqian Chen, Jiansong Ji
Format: Article
Language:English
Published: SpringerOpen 2023-02-01
Series:Insights into Imaging
Subjects:
Hepatocellular carcinoma
Transarterial chemoembolization
Deep learning
Radiomics
Online Access:https://doi.org/10.1186/s13244-023-01380-2

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