Safety of artificial intelligence-assisted optical diagnosis for leaving colorectal polyps in situ during colonoscopy (PRACTICE): a non-inferiority, randomised controlled trial

Giulio Antonelli, Federico Desideri, Patrizio Scarozza, Gianluca Andrisani, Giulia Zerboni, Manuele Furnari, Nicolò Bevilacqua, Marta Cossignani, Michela Di Fonzo, Fabrizio Cereatti, Giulia Navazzotti, Claudia Antenucci, Francesco Maria Di Matteo, Gerolamo Bevivino, Anna Caruso, Marco Spadaccini, Sara Schiavone, Cristina Grossi, Tommy Rizkala, Michele ComberlatoMichael Bretthauer, Prateek Sharma, Daniel Von Renteln, Douglas K Rex, Loredana Correale, Alessandro Repici, Yuichi Mori, Federico Iacopini, Cesare Hassan

Research output: Contribution to journalOriginal Articlepeer-review

Abstract

Background Guidelines recommend leaving in situ rectosigmoid polyps diagnosed during colonoscopy that are 5 mm or smaller if the endoscopist optically predicts them to be non-neoplastic. However, no randomised controlled trial has been done to examine the efficacy and safety of this strategy. Methods This open-label, multicentre, non-inferiority, randomised controlled trial enrolled adults age 18 years or older undergoing colonoscopy for screening, surveillance, or clinical indications across four Italian centres. Eligible patients were randomised 1:1 (with stratification by patient sex, age, and previous adenoma removal) via a central web-based system, to either the leave-in-situ group, in which endoscopists could leave non-neoplastic lesions in place after optical diagnosis, or the resect-all group, in which all detected polyps were systematically removed, regardless of optical diagnosis. Patients and endoscopists were not masked to group allocation but pathologists and investigators assessing outcomes were masked. All procedures in both groups were done with the assistance of a computer-aided detection and diagnosis system. Endoscopists optically diagnosed lesions through a combination of white light, blue light, and computer-aided detection. The primary outcome was the adenoma detection rate (ADR), defined as the proportion of participants with at least one adenoma detected (per-patient analysis), assessed by intention-to-treat, to determine whether the leave-in-situ strategy was non-inferior to the resect-all approach, with an absolute 10% non-inferiority margin. This trial was registered with ClinicalTrials.gov (NCT05500248) and is completed. Findings Between Oct 1, 2022, and April 30, 2024, 1147 patients were recruited and 895 patients (507 [57%] females, 388 [43%] males, mean age 61<middle dot>1 years [SD 9<middle dot>8]) were randomly assigned to either the leave-in-situ group (n=441) or resect-all group (n=454). 197 adenomas or colorectal cancers were detected in the leave-in-situ group and 211 in the resect-all group; the ADR was 44<middle dot>7% (95% CI 40<middle dot>4 to 49<middle dot>5) in the leave-in-situ group and 46<middle dot>5% (41<middle dot>8 to 51<middle dot>2) in the resect-all group (absolute difference-1<middle dot>8 percentage points, 95% CI-8<middle dot>9 to 4<middle dot>9; pnon-inferiority=0<middle dot>013). No colonoscopyrelated complications, including perforation and bleeding, were reported in either group. Interpretation The leave-in-situ strategy through optical diagnosis with computer-assisted diagnosis support does not reduce oncological safety of colonoscopy, as measured by ADR. By reducing unnecessary polypectomies, this strategy could be considered as an attractive option in colonoscopy practice. Funding European Society of Gastrointestinal Endoscopy. Copyright (c) 2025 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.
Original languageEnglish
Pages (from-to)915-923
Number of pages9
JournalLANCET GASTROENTEROLOGY & HEPATOLOGY
Volume10
Issue number10
DOIs
Publication statusPublished - Oct 2025

Keywords

  • Humans
  • Colonoscopy/methods
  • Male
  • Female
  • Middle Aged
  • Colonic Polyps/surgery
  • Artificial Intelligence
  • Adenoma/surgery
  • Colorectal Neoplasms/surgery
  • Aged
  • Diagnosis, Computer-Assisted/methods

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