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<p>Prostate cancer is a leading cause of male cancer mortality, and early, accurate diagnosis is critical. Artificial intelligence (AI), including machine learning, deep learning, and radiomics, enhances detection, characterization, and treatment assessment across TRUS, mp-MRI, and PSMA PET/CT. AI models achieve high accuracy, often matching experts, improving small-lesion detection, and supporting risk stratification. Challenges remain in data quality, generalization, clinical integration, and ethics, with future prospects in multi-omics, explainable AI, and workflow-embedded decision support.</p>

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Application and prospect of artificial intelligence in diagnostic imaging of prostate cancer

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月5日

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  • Xiaoxiao Wang,
  • Shan Zhong,
  • Kun Fang,
  • Yangchun Du,
  • Jianlin Huang

摘要

Prostate cancer is a leading cause of male cancer mortality, and early, accurate diagnosis is critical. Artificial intelligence (AI), including machine learning, deep learning, and radiomics, enhances detection, characterization, and treatment assessment across TRUS, mp-MRI, and PSMA PET/CT. AI models achieve high accuracy, often matching experts, improving small-lesion detection, and supporting risk stratification. Challenges remain in data quality, generalization, clinical integration, and ethics, with future prospects in multi-omics, explainable AI, and workflow-embedded decision support.