{
  "id": 6779812,
  "title": "AI-enabled analysis of pathology slides may help assess risk of pancreatic cancer recurrence",
  "url": "https://urgent.news/2026/09/11/ai-enabled-analysis-of-pathology-slides-may-help-assess-risk-of",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-11T17:00:02.000Z",
  "source": {
    "name": "Medical Xpress",
    "slug": "medical-xpress",
    "url": "https://medicalxpress.com/news/2026-09-ai-enabled-analysis-pathology-pancreatic.html"
  },
  "original_language": "en",
  "account": "Artificial intelligence (AI) analysis of pathology slides may help identify patients with pancreatic cancer who are at higher risk of recurrence after treatment and surgery. Mayo Clinic researchers used AI to examine patterns in routine pathology slides, finding that the organization of residual cancer, rather than just the amount remaining, could indicate recurrence risk. Patients with a fragmented and intermixed pattern of cancer and surrounding tissue were more likely to experience earlier recurrence. The spatial patterns, measured through AI, independently predicted disease-free survival, even when accounting for other factors like the stage of cancer and lymph node involvement. High-risk spatial patterns also showed reduced infiltration of immune cells within the cancer itself. These findings, published in Clinical Cancer Research, suggest that AI-enabled analysis could provide additional information to inform recurrence risk assessments, potentially without the need for additional tissue tests. The study's lead author, Dr. Ryan Carr, emphasizes that the valuable information is already present in existing pathology slides, and AI can help measure features difficult to detect by the human eye. However, further prospective studies are needed to confirm these results before they can be used to guide clinical decision-making.",
  "summary": "Mayo Clinic researchers have found that artificial intelligence (AI)-enabled spatial analysis can identify patterns in routine pathology slides that may help clinicians identify which patients with pancreatic cancer are at greater risk of recurrence after treatment and surgery.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}