Retrospective Cohort Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastrointest Endosc. Dec 8, 2023; 4(2): 18-26
Published online Dec 8, 2023. doi: 10.37126/aige.v4.i2.18
Artificial intelligence fails to improve colonoscopy quality: A single centre retrospective cohort study
Naeman Goetz, Katherine Hanigan, Richard Kai-Yuan Cheng
Naeman Goetz, Katherine Hanigan, Richard Kai-Yuan Cheng, Department of Gastroenterology, Redcliffe Hospital, Redcliffe 4020, Australia
Author contributions: All authors conceived the idea. KH collated the data from the departmental database; Goetz N performed the statistical analysis and was primarily responsible for writing the manuscript; Cheng RKY provided substantial revisions to the manuscript.
Institutional review board statement: The study was approved by the local Human Research Ethics Committee (HREC/2023/MNHA/100582).
Informed consent statement: A waiver of consent was obtained from the HREC.
Conflict-of-interest statement: The authors declare there is no potential sources of conflict of interest. This study was not funded, with research work conducted in-kind.
Data sharing statement: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
STROBE statement: The authors have read the STROBE Statement – checklist of items, and the manuscript was prepared and revised according to the STROBE Statement – checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Naeman Goetz, BSc, MD, Doctor, Department of Gastroenterology, Redcliffe Hospital, Anzac Ave, Redcliffe QLD 4020, Redcliffe 4020, Australia. naeman.goetz@health.qld.gov.au
Received: September 4, 2023
Peer-review started: September 4, 2023
First decision: November 1, 2023
Revised: November 7, 2023
Accepted: November 30, 2023
Article in press: November 30, 2023
Published online: December 8, 2023
Processing time: 93 Days and 5.7 Hours
ARTICLE HIGHLIGHTS
Research perspectives

While Artificial Intelligence Assisted Colonoscopy (AIAC) has shown promise in early randomised controlled trials (RCTs), further validation is required to assess its utility and cost-effectiveness in centres with high baseline performance metrics, where gains from artificial intelligence (AI) are likely to be far more incremental. Specifically, longitudinal studies that assess the impact of AIAC on interval cancer rates are required.

Research conclusions

In our institution, introduction of AIAC failed to improve key benchmarks of colonoscopy quality, including adenoma detection rate (ADR), sessile serrated lesion detection rate (SSLDR) and withdrawal time. An important limitation of our investigation is the relatively brief observation period following AIAC implementation, that the ‘on time’ of the AI assistance mode was not recorded as well as the retrospective design.

Research results

The study included 746 AIAC procedures and 2162 conventional colonoscopy (CC) procedures performed by seven endoscopists. Baseline patient demographics were similar, with a median age of 60 years and a slight female predominance (52.1%). Procedure indications, bowel preparation quality, and caecal intubation rates were comparable between groups. AIAC had a slightly longer withdrawal time compared to CC, but the difference was not statistically significant. The introduction of AIAC did not significantly change ADR (52.1% for AIAC vs 52.6% for CC, P = 0.91) or SSLDR (17.4% for AIAC vs 18.1% for CC, P = 0.44).

Research methods

This retrospective observational cohort study was conducted at a single center in Brisbane, Australia, encompassing all patients who underwent colonoscopy during the study period. Colonoscopy quality markers for CCs conducted from October 2021 to October 2022 were compared with AIAC markers following the implementation of the Olympus Endo-AID module from October 2022 to January 2023. Proceduralists who conducted over 50 procedures before and after AIAC introduction were included. Procedures for surveillance of inflammatory bowel disease were excluded. Patient demographics, proceduralist specialisation, indication for colonoscopy, and colonoscopy quality metrics were collected. We determined the ADR and SSLDR for both CC and AIAC.

Research objectives

The objective of our investigation was to assess the effect of AIAC on key benchmarks of colonoscopy quality including the detection rate of adenomas (ADR) and SLLDR as well as withdrawal time in comparison to CC.

Research motivation

In recent years, rapid technological advancements and a focus on quality improvement have garnered significant enthusiasm for AIAC as a means of improving key markers of colonoscopy quality. While early data appears promising, this technology requires validation in day-to-day clinical practice.

Research background

AIAC has emerged as a potential tool for improving colonoscopy quality and mitigating factors such as proceduralist fatigue or inattention in a procedure that is substantially operator dependent. However, published data on the utility and cost-effectiveness in real-world clinical settings is limited.