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Artificial intelligence computer-aided detection (CADe) increases adenoma detection rates and reduces miss rates during colonoscopy. However, CADe also leads to more removal of nonneoplastic polyps, indicating potential overdiagnosis.

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Area of Science:

  • Gastroenterology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Artificial intelligence computer-aided detection (CADe) may improve adenoma detection rates (ADRs) and reduce miss rates during colonoscopy.
  • However, concerns exist regarding CADe's potential for overdiagnosis and overtreatment of nonneoplastic polyps.

Approach:

  • A systematic review and meta-analysis was conducted to quantify the benefits and harms of CADe in randomized controlled trials.
  • Data were extracted from Medline, Embase, and Scopus databases, including randomized trials comparing CADe-assisted with standard colonoscopy.
  • Outcomes assessed included adenoma detection, miss rates, advanced adenoma detection, serrated lesion detection, polypectomies for nonneoplastic lesions, and withdrawal time, with certainty of evidence evaluated using the GRADE framework.

Key Points:

  • CADe significantly increased the adenoma detection rate (ADR) compared to standard colonoscopy (44.0% vs. 35.9%), with low-certainty evidence.
  • CADe demonstrated a moderate-certainty moderate-certainty relative reduction in adenoma miss rate (45%).
  • The use of CADe resulted in a low-certainty increase in polypectomies for nonneoplastic lesions (0.52 vs. 0.34 per colonoscopy).
  • Mean inspection time increased marginally with CADe (0.47 minutes), with moderate-certainty evidence.

Conclusions:

  • CADe enhances polyp detection during colonoscopy, leading to higher adenoma detection rates.
  • Despite increased adenoma detection, CADe did not show improved detection of advanced adenomas.
  • CADe use is associated with a higher rate of unnecessary removal of nonneoplastic polyps.