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An Artificial Intelligence-Guided Strategy to Reduce Poor Bowel Preparation: A Multicenter Randomized Controlled

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A new software application using artificial intelligence significantly improved colon cleansing quality for colonoscopies. This AI-driven approach enhances bowel preparation, leading to better outcomes in outpatient procedures.

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Area of Science:

  • Gastroenterology and Endoscopy
  • Artificial Intelligence in Medicine
  • Medical Imaging Analysis

Background:

  • High-quality bowel preparation is essential for accurate adenoma detection during colonoscopies.
  • Current standard methods for bowel preparation assessment can be subjective and inconsistent.
  • Novel technological solutions are needed to objectively improve colon cleansing quality.

Purpose of the Study:

  • To evaluate the efficacy of a software application utilizing a convolutional neural network (CNN) for improving colon cleansing quality.
  • To compare a software-driven bowel preparation approach with standard care in a multicenter randomized controlled trial.
  • To assess whether AI-based feedback on rectal effluent images enhances colonoscopy preparation.

Main Methods:

  • A multicenter randomized controlled trial involving 774 patients.
  • Patients were assigned to either standard care or an intervention group using a web application with CNN-based feedback.
  • The intervention group submitted images of rectal effluents for AI analysis and received guidance on preparation adequacy.

Main Results:

  • The intervention group showed statistically significant improvements in overall bowel cleansing quality (91% vs. 84.2%, P=0.005).
  • Superior cleansing was observed in both the right and left colon segments for the intervention group.
  • Per-protocol analysis confirmed significantly better bowel cleansing in the intervention group, including for achieving excellent preparation (BBPS >7).

Conclusions:

  • A software application leveraging CNN analysis of rectal effluent images significantly enhances colon cleansing quality in outpatients.
  • This AI-driven approach offers a promising tool for optimizing bowel preparation prior to colonoscopies.
  • The study demonstrates the clinical utility of integrating AI into patient-guided preparation protocols.