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Artificial intelligence empowers the second-observer strategy for colonoscopy: a randomized clinical trial.

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Artificial intelligence (AI) computer-aided detection (CADe) significantly improved adenoma and polyp detection during colonoscopy compared to a human observer. This AI assistance enhances colorectal cancer screening outcomes by increasing lesion detection rates.

Keywords:
adenomaartificial intelligencecolon cancer screeningcomputer-aided detectionearly detection

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Area of Science:

  • Gastroenterology
  • Medical Imaging
  • Artificial Intelligence in Medicine

Background:

  • Human vision limitations in colonoscopy can increase missed colorectal cancer lesions.
  • Artificial intelligence (AI) shows promise in improving polyp detection during colonoscopy.
  • Evidence comparing AI as a second observer to human observers for adenoma detection is limited.

Purpose of the Study:

  • To compare the effectiveness of AI-assisted colonoscopy versus human observer-assisted colonoscopy.
  • To evaluate AI's superiority as a second observer in increasing adenoma detection rates.

Main Methods:

  • Prospective multicenter randomized study involving 1,261 patients across four endoscopy centers in China.
  • Patients were randomized into computer-aided detection (CADe)-assisted or observer-assisted groups.
  • Primary outcome: adenoma per colonoscopy (APC); Secondary outcomes: polyp per colonoscopy (PPC), adenoma detection rate (ADR), polyp detection rate (PDR).

Main Results:

  • The CADe-assisted group showed significantly higher APC (0.42 vs 0.35), PPC (1.13 vs 0.81), and PDR (47.5% vs 37.4%) than the observer-assisted group.
  • Adenoma detection rate (ADR) was comparable between groups (25.8% vs 24.0%).
  • CADe significantly increased detection of sessile polyps and sessile adenomas, with fewer false detections compared to human observers.

Conclusions:

  • Computer-aided detection (CADe) systems can improve colonoscopy clinical outcomes compared to human observers.
  • AI assistance enhances lesion detection and may reduce the disturbance to routine endoscopy practices.
  • The study provides evidence for AI's effectiveness in improving adenoma detection during colonoscopy screening.