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

Journal: Bioscience trends
PMID: 40240167

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.

Authors

  • Runze Huang
    Department of Animal and Food Sciences, University of Delaware, Newark, DE 19716-2150, USA.
  • Xin Jin
    Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, 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.
  • 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.
  • Lu Wang
    Department of Laboratory, Akesu Center of Disease Control and Prevention, Akesu, China.
  • Weiping Zhu
    State Key Laboratory of Bioreactor Engineering, Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, PR China.

Keywords

External Resources

Popular Topics
Recent Journals