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World J Radiol. Feb 28, 2026; 18(2): 116486
Published online Feb 28, 2026. doi: 10.4329/wjr.v18.i2.116486
Published online Feb 28, 2026. doi: 10.4329/wjr.v18.i2.116486
Interpretable radiomics model based on magnetic resonance imaging to predict responses to transarterial chemoembolization for hepatocellular carcinoma
Qi Mao, Peng Zhang, Mao-Ting Zhou, Yue Shi, Xu-Li Min, Hao Xu, Lin Yang, Xiao-Ming Zhang, Center of Interventional Medical, Department of Radiology, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
Qi Mao, Department of Radiology, The People’s Hospital of Yuechi County, Yuechi County 610041, Sichuan Province, China
Co-first authors: Qi Mao and Peng Zhang.
Author contributions: Mao Q, Zhang P, Zhou MT, Shi Y, Min XL, and Xu H performed the research; Yang L and Zhang XM designed the research study; Mao Q and Zhang P contributed equally to this manuscript and are co-first authors. All the authors contributed to the article and approved the submitted version.
Supported by the Project of City-University Science and Technology Strategic Cooperation of Nanchong City, No. 20SXQT0324 and No. 20SXQT0246.
Institutional review board statement: This study was approved by the Ethics Committee of the Affiliated Hospital of North Sichuan Medical College (Approval No. 2025ER8-1) and was performed in accordance with the Declaration of Helsinki.
Informed consent statement: Because this study was a retrospective study with anonymous data collection, the requirement for informed consent was waived.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.
Corresponding author: Lin Yang, MD, Center of Interventional Medical, Department of Radiology, The Affiliated Hospital of North Sichuan Medical College, No. 63 Wenhua Road, Nanchong 637000, Sichuan Province, China. linyangmd@163.com
Received: November 13, 2025
Revised: January 11, 2026
Accepted: January 19, 2026
Published online: February 28, 2026
Processing time: 105 Days and 1.9 Hours
Revised: January 11, 2026
Accepted: January 19, 2026
Published online: February 28, 2026
Processing time: 105 Days and 1.9 Hours
Core Tip
Core Tip: Transarterial chemoembolization (TACE) plays an important role in the treatment of unresectable hepatocellular carcinoma (HCC). However, owing to the heterogeneity of HCC tumors, TACE efficacy varies among individual HCC patients. Accurate preoperative prediction of responses to TACE among HCC patients could guide the development of individualized treatment strategies and improve patient outcomes. This study aimed to investigate the predictive value of multiple-sequence magnetic resonance imaging radiomic features combined with clinical indices for the response to TACE among HCC patients and to develop an interpretable machine learning model.