Clinical Trials Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Aug 16, 2025; 13(23): 101742
Published online Aug 16, 2025. doi: 10.12998/wjcc.v13.i23.101742
Prediction of the efficacy of first transarterial chemoembolization for advanced hepatocellular carcinoma via a clinical-radiomics model
Kai-Fei Zhao, Chao-Bang Xie, Yang Wu
Kai-Fei Zhao, Department of Radiology, The Affiliated Hospital of Zunyi Medical University, Zunyi 563000, Guizhou Province, China
Chao-Bang Xie, Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang 563000, Guizhou Province, China
Yang Wu, Department of Intervention, The Second Affiliated Hospital of Zunyi Medical University, Zunyi 563000, Guizhou Province, China
Author contributions: Zhao KF and Xie CB contributed to conceptualization, methodology, data curation, writing, original draft; Wu Y contributed to visualization, validation, writing–review and editing. All authors approved the final manuscript and agreed to be accountable for all aspects of the work.
Institutional review board statement: This study was approved by the Ethics Committee of the Affiliated Hospital of Zunyi Medical University.
Informed consent statement: Since it was a single-center, retrospective, observational cohort study, informed consent was waived.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
CONSORT 2010 statement: The authors have read the CONSORT 2010 statement, and the manuscript was prepared and revised according to the CONSORT 2010 statement.
Data sharing statement: No additional data are available.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yang Wu, Doctor, Department of Intervention, The Second Affiliated Hospital of Zunyi Medical University, Intersection of Xinlong Avenue and Xinpu Avenue, Xinpu New District, Zunyi 563000, Guizhou Province, China. 1096945853@qq.com
Received: September 26, 2024
Revised: March 9, 2025
Accepted: April 25, 2025
Published online: August 16, 2025
Processing time: 250 Days and 18.9 Hours
Abstract
BACKGROUND

Hepatocellular carcinoma (HCC) is a common tumor with a poor prognosis. Early intervention is essential; thus, good prognostic markers to identify patients who benefit from first transarterial chemoembolization (TACE) are needed.

AIM

To investigate the efficacy of computed tomography (CT) radiomics in predicting the success of the first TACE in patients with advanced HCC and to develop an early prediction model based on clinical radiomics features.

METHODS

Data from 122 patients with advanced HCC treated with TACE were analyzed. Intratumoral and peritumoral areas on arterial and venous CT images were selected to extract radiomic features, which were screened in the training cohort using the minimum redundancy maximum correlation. Then, support vector machines were used to construct the model. To construct a receiver operating characteristic curve, the predictive efficacy of each model was evaluated on the basis of the area under the curve (AUC).

RESULTS

Among the 122 patients, 72 patients were effectively treated via TACE, and in 50 patients, this treatment was ineffective. In the radiomics model, the areas under the curve of the venous phase model were 0.867 (95%CI: 0.790-0.940) in the training cohort and 0.755 (0.600-0.910) in the validation cohort, indicating good predictive efficacy. The multivariate logistic regression results indicated that preoperative alpha-fetoprotein levels (P = 0.01) were a risk factor for TACE. The screened clinical features were combined with the radiomic features to construct a combined model. This combined model had an AUC of 0.92 (0.87-0.95) in the training cohort and 0.815 (0.67-0.95) in the validation cohort.

CONCLUSION

CT radiomics has good value in predicting the efficacy of the first TACE treatment in patients with HCC. The combined model was a better tool for predicting the first TACE efficacy in patients with advanced HCC and could provide an efficient predictive tool to help with the selection of patients for TACE.

Keywords: Hepatocellular carcinoma; Transarterial chemoembolization; Radiomics; Computed tomography; Prognosis; Treatment response

Core Tip: Hepatocellular carcinoma (HCC) is often diagnosed at advanced stages, where transarterial chemoembolization (TACE) serves as a key therapy. However, nearly 50% of patients show poor TACE response due to tumor heterogeneity. This study integrates preoperative computed tomography radiomics and clinical factors to build a predictive model for TACE efficacy. Radiomics noninvasively extracts quantitative imaging features reflecting tumor pathophysiology, enabling precise assessment of treatment response. The combined model stratifies patients by predicted risk, guiding timely transition to alternative therapies (e.g., targeted drugs or immunotherapy) for non-responders. This approach enhances personalized HCC management, optimizes resource allocation, and improves survival outcomes through data-driven clinical decision-making.