The yield of artificial intelligence (GI genius) in Lynch syndrome -A randomized tandem-colonoscopy trial.

Dig Liver DisSep 15, 2026 (epub)

Laish Ido, Ben-Horin Shomron, Levi Idan et al.

✦ AI-curated · Sources linked

In 30 seconds

This single-centre randomized tandem-colonoscopy trial assessed whether artificial intelligence (AI) added polyp detection beyond high-definition white-light endoscopy (HD-WLE) in patients with Lynch syndrome. Among 100 enrolled patients, the per-polyp incremental adenoma detection rate was 33.3% with AI and 11.1% with HD-WLE, but the difference was not statistically significant (OR 4.0, 95% CI 0.68-23.40; p=0.124). Per-patient increases in adenoma and polyp detection were also not significant. The authors concluded that AI did not significantly improve adenoma detection in this setting.

Key findings

  • Per-polyp incremental adenoma detection was 33.3% with AI versus 11.1% with HD-WLE (OR 4.0, 95% CI 0.68-23.40; p=0.124).
  • Per-patient incremental adenoma detection was 35.3% with AI versus 13.3% with HD-WLE (p=0.165).
  • Per-patient incremental polyp detection was 26.6% with AI versus 14.8% with HD-WLE (p=0.278).

Why it matters

Lynch syndrome is the population studied, and the trial addresses whether AI adds detection beyond careful high-definition colonoscopy. Although the observed incremental detection rates were numerically higher with AI, the comparisons were not statistically significant. These results help frame the uncertainty about AI’s added value in this specific colonoscopy setting.

What to keep in mind

The trial was single-centre, and the reported comparisons were not statistically significant, with a wide confidence interval for the per-polyp estimate.

Source

Published in Dig Liver Dis. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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