Artificial intelligence in colorectal cancer liver metastases: From classification to precision medicine

Runze Huang; Xin Jin; Qinyu Liu; Xuanci Bai; Kenji Karako; Wei Tang; Lu Wang; Weiping Zhu

doi:10.5582/bst.2025.01045

Runze Huang, Xin Jin, Qinyu Liu, Xuanci Bai, Kenji Karako, Wei Tang, Lu Wang, Weiping Zhu

Author information

Runze Huang
Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
Department of Oncology, Shanghai Medical College Fudan University, Shanghai, China.
Xin Jin
Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
Department of Oncology, Shanghai Medical College Fudan University, Shanghai, China.
Qinyu Liu
Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
Department of Oncology, Shanghai Medical College Fudan University, Shanghai, China.
Xuanci Bai
Department of Clinical Medicine, Shanghai Medical College, Fudan University, Shanghai, China.
Kenji Karako
Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Wei Tang
Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
National Center for Global Health and Medicine, Japan Institute for Health Security, Tokyo, Japan.
Lu Wang
Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
Department of Oncology, Shanghai Medical College Fudan University, Shanghai, China.
Weiping Zhu
Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
Department of Oncology, Shanghai Medical College Fudan University, Shanghai, China.

Keywords: colorectal cancer liver metastasis, artificial intelligence, classification, precision medicine

JOURNAL FREE ACCESS Advance online publication

Article ID: 2025.01045

DOI https://doi.org/10.5582/bst.2025.01045

Details

Abstract

Colorectal cancer liver metastasis (CRLM) remains the leading cause of mortality among colorectal cancer (CRC) patients, with more than half eventually developing hepatic metastases. Achieving long-term survival in CRLM necessitates early detection, robust stratification, and precision treatment tailored to individual classifications. These processes encompass critical aspects such as tumor staging, predictive modeling of therapeutic responses, and risk stratification for survival outcomes. The rapid evolution of artificial intelligence (AI) has ushered in unprecedented opportunities to address these challenges, offering transformative potential for clinical oncology. This review summarizes the current methodologies for CRLM grading and classification, alongside a detailed discussion of the machine learning models commonly used in oncology and AI-driven applications. It also highlights recent advances in using AI to refine CRLM subtyping and precision medicine approaches, underscoring the indispensable role of interdisciplinary collaboration between clinical oncology and the computational sciences in driving innovation and improving patient outcomes in metastatic colorectal cancer.

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