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Review

Adenoma detection rate in colonoscopy: how can it be improved?

, , , , &
Pages 1089-1099 | Received 21 Feb 2023, Accepted 18 Oct 2023, Published online: 26 Oct 2023
 

ABSTRACT

Introduction

The introduction of widespread colonoscopy screening programs has helped in decreasing the incidence of Colorectal Cancer (CRC). However, ‘back-to-back’ colonoscopies revealed relevant percentage of missed adenomas. Quality indicators were created to further homogenize detection performances and decrease the incidence of post-colonoscopy CRC. Among them, the Adenoma Detection Rate (ADR), defined as the percentage obtained by dividing the number of endoscopic procedures in which at least one adenoma was resected, by the total number of procedures, was found to be inversely associated with the risks of interval colorectal cancer, advanced-stage interval cancer, and fatal interval cancer.

Areas covered

In this paper, we performed a comprehensive review of the literature focusing on promising new devices and technologies, which are meant to positively affect the endoscopist performance in detecting adenomas, therefore increasing ADR.

Expert opinion

Considering the current knowledge, although several devices and technologies have been proposed with this intent, the recent implementation of AI ranked over all of the other strategies and it is likely to become the new standard within few years. However, the combination of different device/technologies need to be investigated in the future aiming at even further increasing of endoscopist detection performances.

Article highlights

  • ADR is the most dependable measure of the risk of PCCRC occurrence.

  • The implementation of Endocuff Vision improves the adenoma detection rate.

  • The benefits of Methylene blue are diminished by the increase in withdrawal time, as such per-oral administration may have a significant role in the future.

  • LCI enhances the rate of adenoma detection in multiple trials.

  • Artificial Intelligence enhances the rate of adenoma detection in both expert and non-expert settings.

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

All authors contributed to this paper with conception, literature review, drafting, critical revision and editing, and approval of the final version.

Additional information

Funding

This paper was not funded.

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