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<p>Diagnostic needle biopsies that miss clinically significant prostate cancer (PCa) often sample benign tissue near hidden cancers. Such benign samples might still display subtle morphological signs of cancer elsewhere in the prostate. This study examined if artificial intelligence (AI) could detect these morphological clues in benign biopsies from men with elevated prostate-specific antigen (PSA) levels to predict subsequent diagnosis of clinically significant PCa within 30 months. We analysed biopsies from 232 men initially diagnosed as benign, matched for age, diagnosis year, and PSA levels-half were later diagnosed with PCa, while the rest remained cancer-free for at least eight years. The AI model accurately predicted future PCa diagnosis from initial benign biopsies (AUC = 0.82), highlighting patterns such as changes in stromal collagen and altered glandular epithelial cells. This demonstrates that AI analysis of routine haematoxylin-eosin biopsy sections can detect subtle signs indicating clinically significant PCa before it becomes histologically apparent. Such morphological patterns shed light on the broader tissue alterations induced by prostate cancer, even in benign tissue, potentially enhancing early detection and clinical decision-making.</p>

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Discovery of tumour indicating morphological changes in benign prostate biopsies through AI

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月21日

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  • Eduard Chelebian,
  • Christophe Avenel,
  • Helena Järemo,
  • Pernilla Andersson,
  • Anders Bergh,
  • Carolina Wählby

摘要

Diagnostic needle biopsies that miss clinically significant prostate cancer (PCa) often sample benign tissue near hidden cancers. Such benign samples might still display subtle morphological signs of cancer elsewhere in the prostate. This study examined if artificial intelligence (AI) could detect these morphological clues in benign biopsies from men with elevated prostate-specific antigen (PSA) levels to predict subsequent diagnosis of clinically significant PCa within 30 months. We analysed biopsies from 232 men initially diagnosed as benign, matched for age, diagnosis year, and PSA levels-half were later diagnosed with PCa, while the rest remained cancer-free for at least eight years. The AI model accurately predicted future PCa diagnosis from initial benign biopsies (AUC = 0.82), highlighting patterns such as changes in stromal collagen and altered glandular epithelial cells. This demonstrates that AI analysis of routine haematoxylin-eosin biopsy sections can detect subtle signs indicating clinically significant PCa before it becomes histologically apparent. Such morphological patterns shed light on the broader tissue alterations induced by prostate cancer, even in benign tissue, potentially enhancing early detection and clinical decision-making.