The state of the art in artificial intelligence and digital pathology in prostate cancer.

Journal: Nature reviews. Urology
Published Date: Aug 4, 2025

Abstract

Prostate cancer is among the most common cancers worldwide, with ~1.5 million new diagnoses globally every year. The sheer mass of data becoming available on prostate cancer, as well as other types of cancer, is increasing exponentially. The growth of digital pathology has particularly sparked interest in developing artificial intelligence (AI) approaches to data synthesis to predict cancer grade and outcomes in men with prostate cancer. Progress has been made in this field, particularly in applications for diagnosis, prognosis and inferring molecular alterations, but several challenges remain. Variability in tissue processing and scanning contribute to dataset heterogeneity. The absence of well-annotated, multi-institutional databases hinders AI model development and generalization of model performances across clinical settings. Regulatory frameworks for AI-driven diagnostics remain nascent. Moreover, bias in training datasets skewing against under-represented demographic groups poses a fundamental challenge to developing equitable models. By mapping contemporary evidence around each of these hurdles and identifying tangible interventions, we can advance AI-augmented digital pathology towards reliable and generalizable tools to improve prostate cancer care.

Authors

  • Heyuan Michael Ni
    Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Ramez Kouzy
    Department of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Ali Sabbagh
    Department of Radiation Oncology, University of California-San Francisco, San Francisco, CA, USA.
  • Michael K Rooney
    MD Anderson Cancer Center, Houston, TX, USA.
  • Jean Feng
    Department of Biostatistics, University of Washington, Seattle, WA.
  • Simon P Castillo
    Centre for Evolution and Cancer and Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom.
  • Sherif M Gadoue
    MD Anderson Cancer Center, Houston, TX, USA.
  • Zakaria El Kouzi
    MD Anderson Cancer Center, Houston, TX, USA.
  • Karen Hoffman
    The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Yinyin Yuan
    Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK; Division of Molecular Pathology, The Institute of Cancer Research, London, UK. Electronic address: yyuan6@mdanderson.org.
  • Anant Madabhushi
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.
  • Osama Mohamad
    Department of Radiation Oncology, University of California, San Francisco, San Francisco.

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