Application of multimodal fusion technology in early recurrence prediction and pathological analysis of hepatocellular carcinoma

doi:10.4251/wjgo.v17.i12.114037

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Dec 15, 2025 (publication date) through Dec 14, 2025

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World Journal of Gastrointestinal Oncology

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1948-5204

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Cohort Study

World J Gastrointest Oncol. Dec 15, 2025; 17(12): 114037
Published online Dec 15, 2025. doi: 10.4251/wjgo.v17.i12.114037

Application of multimodal fusion technology in early recurrence prediction and pathological analysis of hepatocellular carcinoma

Li-Hong Huang, Yi-Jing Fang, Xiao-Jun Zheng, Ce Huang, Chang-Lu Li, Bin Yu, Meng-Jie Huang, Shi-Ji Qin, De-You Huang, De-Wei Lu

Li-Hong Huang, Xiao-Jun Zheng, Bin Yu, Meng-Jie Huang, Shi-Ji Qin, De-You Huang, De-Wei Lu, Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China

Yi-Jing Fang, Department of Radiology, Beihai People's Hospital, Beihai 536000, Guangxi Zhuang Autonomous Region, China

Ce Huang, Department of Radiology, Tianlin County People's Hospital, Baise 533300, Guangxi Zhuang Autonomous Region, China

Chang-Lu Li, Department of Radiology, Qinzhou First People's Hospital, Qinzhou 535000, Guangxi Zhuang Autonomous Region, China

Co-first authors: Li-Hong Huang and Yi-Jing Fang.

Co-corresponding authors: De-You Huang and De-Wei Lu.

Author contributions: Huang LH and Fang YJ contribute equally to this study as co-first authors; Huang DY and Lu DW contribute equally to this study as co-corresponding authors; Huang LH, Fang YJ, Zheng XJ, Huang DY and Lu DW carried out the studies, participated in collecting data, and drafted the manuscript; Huang LH, Fang YJ, Zheng XJ, Huang DY and Lu DW performed the statistical analysis and participated in its design; Huang C, Li CL, Yu B, Huang MJ, Qin SJ helped to draft the manuscript; all authors read and approved the final manuscript.

Supported by the "Summit Plan (New Departure)" Project for the Development of Doctoral Degree Authorization Points and Professional Disciplines at the Affiliated Hospital of Youjiang Medical University for Nationalities, No. DF20244433; Self-funded Research Projects by the Guangxi Health and Wellness Committee, No. Z-L20240824; and the Project to Enhance the Research Foundations of Young and Mid-career Faculty in Guangxi Universities, No. 2024KY0562.

Institutional review board statement: Following the ethical principles of the Declaration of Helsinki, we conducted a retrospective analysis of 237 patients diagnosed with hepatocellular carcinoma at the Affiliated Hospital of Youjiang Medical University for Nationalities from January 2019 to May 2024. We obtained approval from the Institutional Review Board and received a waiver of informed consent for all patients from the institution (approval No. YYFY-LL-2024-038).

Informed consent statement: In accordance with the Helsinki Declaration and our institution’s ethical review guidelines, the ethics committee granted a waiver of informed consent due to the non-interventional nature of the study and the de-identification of patient information.

Conflict-of-interest statement: The authors declare that they have no conflict of interests.

STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.

Data sharing statement: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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: De-Wei Lu, BM, Associate Chief Physician, Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, No. 18 Zhongshan Second Road, Baise 533000, Guangxi Zhuang Autonomous Region, China. 45934710@qq.com

Received: September 10, 2025
Revised: October 2, 2025
Accepted: November 6, 2025
Published online: December 15, 2025
Processing time: 92 Days and 17.1 Hours

Abstract

BACKGROUND

Early recurrence is an important factor affecting the prognosis of hepatocellular carcinoma (HCC), but its preoperative prediction remains challenging.

AIM

To explore the value of a multimodal interpretable fusion model combining computed tomography (CT) habitat imaging (HI), radiomics, and clinical features in predicting early recurrence of HCC and analyze its correlation with pathological indicators.

METHODS

The 191 HCC patients were categorized into early recurrence and non-early recurrence groups based on postoperative follow-up outcomes, and randomly divided into training and testing sets in a 7:3 ratio. Based on CT arterial phase and clinical data, the habitat model, radiomics model, clinical model, and fusion model were constructed and compared for their predictive ability in early recurrence of HCC. For the optimal model, SHapley Additive exPlanations (SHAP) analysis was performed to evaluate the contribution of different features in the model, and the correlation between HI and radiomics features with tumor microvascular invasion (MVI), Ki67 expression, GPC-3 expression, and pathological grading was analyzed.

RESULTS

The fusion model demonstrated the best performance in predicting early recurrence of HCC, achieving the area under the curve of 0.933 on the validation set. The decision curve analysis curve indicated that the fusion model yielded the highest clinical net benefit. SHAP analysis provided valuable insights into explaining the fusion model's prediction of early HCC recurrence. Correlation analysis revealed significant associations between certain radiomics and Habitat features and pathological indicators such as MVI and Ki-67 expression in HCC.

CONCLUSION

An interpretable fusion model integrating clinical, radiomic, and habitat features can assist clinicians in identifying early postoperative recurrence of HCC, offering significant potential for prognosis prediction and clinical management.

Keywords: Hepatocellular carcinoma; Habitat imaging; Radiomics; Early recurrence; Fusion model

Core Tip: This study explores an interpretable fusion model that combines clinical, radiomics, and habitat features based on enhanced arterial-phase computed tomography images of the liver to predict early recurrence after hepatocellular carcinoma (HCC) surgery. The model outperforms traditional radiomics, clinical, and habitat models. It can help clinicians identify early recurrence of HCC after surgery.