Artificial Intelligence in digital pathology of breast cancer, new era of practice?

Journal: International journal of surgery (London, England)
Published Date: Jul 23, 2025

Abstract

Breast cancer is the most common cancers among women worldwide. Early diagnosis and personalized medicine are crucial for the treatment of breast cancer. With the development of computer science and the emergence of whole slide imaging technology (WSIs), artificial intelligence(AI) is having a surprisingly positive impact on the field of pathology, including breast pathology. The deployment of AI provides powerful tools for research in digital pathology and provides potential solutions in precision medicine in breast cancer. In this review, we systematically reviewed the applications of AI in digital pathology of breast cancer, including the identification of histological features, such as tumor-infiltrating lymphocytes (TILs), and the evaluation of classical biomarkers, such as human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), progesterone receptor (PR). We also introduce the combined use of AI with multi-omics data in outcome prediction and treatment in breast cancer, and outline the evolution of AI methods applied in digital pathology. Collectively, the robustly evolving AI technologies would profoundly impact the precision pathology and medicine in breast cancer.

Authors

  • Wenjing Li
    Department of Allergy, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
  • Sijing Ye
    Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.
  • Zimeng Jin
    Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.
  • Lin Chen
    College of Sports, Nanjing Tech University, Nanjing, China.
  • Yuqing Chao
    School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Guikang Wei
    Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.
  • Qinyi Huang
    School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Huakang Tu
    Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Qinchuan Wang
    Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. wangqinchuan@zju.edu.cn.

Keywords

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