Radiomics for Predicting the Efficacy of Immunotherapy in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment

CT/MRI-based radiomics uses routine imaging to non-invasively quantify whole-tumor phenotype and heterogeneity, enabling repeatable, longitudinal assessment in hepatocellular carcinoma. Evidence suggests that it can help to identify patients likely to benefit from immunotherapy before treatment. However, clinical implementation requires standardized imaging and analysis protocols, external validation, and transparent reporting.

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Publication Details

Journal
Cancers
Published
2026-01-06
DOI
https://doi.org/10.3390/cancers18020186
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00

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article

Radiomics for Predicting the Efficacy of Immunotherapy in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment

Anhong Zhang, Chengjie Zhang, Yi Liu, RuiXin Zhang et al.
Cancers
Radiomics and Machine Learning in Medical Imaging
article

Radiomics for Predicting the Efficacy of Immunotherapy in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment

Anhong Zhang, Chengjie Zhang, Yi Liu, RuiXin Zhang, Zhiguo Gui
article en

Abstract

CT/MRI-based radiomics uses routine imaging to non-invasively quantify whole-tumor phenotype and heterogeneity, enabling repeatable, longitudinal assessment in hepatocellular carcinoma. Evidence suggests that it can help to identify patients likely to benefit from immunotherapy before treatment. However, clinical implementation requires standardized imaging and analysis protocols, external validation, and transparent reporting.

CancersVol. 18(2)
North University of China (CN), Shanxi Medical University (CN), First Hospital of Shanxi Medical University (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 95%
Radiomics and Machine Learning in Medical Imaging
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