Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial

Am J Gastroenterol. 2024 Jul 1;119(7):1318-1325. doi: 10.14309/ajg.0000000000002684. Epub 2024 Feb 2.

Abstract

Introduction: Both artificial intelligence (AI) and distal attachment devices have been shown to improve adenoma detection rate and reduce miss rate during colonoscopy. We studied the combined effect of Endocuff and AI on enhancing detection rates of various colonic lesions.

Methods: This was a 3-arm prospective randomized colonoscopy study involving patients aged 40 years or older. Participants were randomly assigned in a 1:1:1 ratio to undergo Endocuff with AI, AI alone, or standard high-definition (HD) colonoscopy. The primary outcome was adenoma detection rate (ADR) between the Endocuff-AI and AI groups while secondary outcomes included detection rates of polyp (PDR), sessile serrated lesion (sessile detection rate [SDR]), and advanced adenoma (advanced adenoma detection rate) between the 2 groups.

Results: A total of 682 patients were included (mean age 65.4 years, 52.3% male), with 53.7% undergoing diagnostic colonoscopy. The ADR for the Endocuff-AI, AI, and HD groups was 58.7%, 53.8%, and 46.3%, respectively, while the corresponding PDR was 77.0%, 74.0%, and 61.2%. A significant increase in ADR, PDR, and SDR was observed between the Endocuff-AI and AI groups (ADR difference: 4.9%, 95% CI: 1.4%-8.2%, P = 0.03; PDR difference: 3.0%, 95% CI: 0.4%-5.8%, P = 0.04; SDR difference: 6.4%, 95% CI: 3.4%-9.7%, P < 0.01). Both Endocuff-AI and AI groups had a higher ADR, PDR, SDR, and advanced adenoma detection rate than the HD group (all P < 0.01).

Discussion: Endocuff in combination with AI further improves various colonic lesion detection rates when compared with AI alone.

Trial registration: ClinicalTrials.gov NCT05133544.

Publication types

  • Randomized Controlled Trial

MeSH terms

  • Adenoma* / diagnosis
  • Adenoma* / diagnostic imaging
  • Adult
  • Aged
  • Artificial Intelligence*
  • Colonic Polyps / diagnosis
  • Colonic Polyps / diagnostic imaging
  • Colonoscopy* / methods
  • Colorectal Neoplasms* / diagnosis
  • Colorectal Neoplasms* / diagnostic imaging
  • Female
  • Humans
  • Male
  • Middle Aged
  • Prospective Studies

Associated data

  • ClinicalTrials.gov/NCT05133544