The use of machine learning in transarterial chemoembolisation/transarterial embolisation for patients with intermediate-stage hepatocellular carcinoma: a systematic review
File(s)
Published online version
Author(s)
Type
Journal Article
Abstract
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Intermediate-stage HCC is often treated with either transcatheter arterial chemoembolisation (TACE) or transcatheter arterial embolisation (TAE). Integrating machine learning (ML) offers the possibility of improving treatment outcomes through enhanced patient selection. This systematic review evaluates the effectiveness of ML models in improving the precision and efficacy of both TACE and TAE for intermediate-stage HCC. A comprehensive search of PubMed, EMBASE, Web of Science, and Cochrane Library databases was conducted for studies applying ML models to TACE and TAE in patients with intermediate-stage HCC. Seven studies involving 4,017 patients were included. All included studies were from China. Various ML models, including deep learning and radiomics, were used to predict treatment response, yielding a high predictive accuracy (AUC 0.90). However, study heterogeneity limited comparisons. While ML shows potential in predicting treatment outcomes, further research with standardised protocols and larger, multi-centre trials is needed for clinical integration.
Date Issued
2025-05-03
Date Acceptance
2025-03-25
Citation
La Radiologia Medica, 2025
ISSN
1826-6983
Publisher
Springer
Journal / Book Title
La Radiologia Medica
Copyright Statement
© The Author(s) 2025 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
10.1007/s11547-025-02013-y
Subjects
Carcinoma, Hepatocellular
Chemoembolization, Therapeutic
Machine Learning
Image Interpretation, Computer-Assisted
Interventional Radiology
Publication Status
Published online
Date Publish Online
2025-05-03