Effectiveness and application of artificial intelligence for endoscopic screening of colorectal cancer: the future is now

ABSTRACT

Introduction

Artificial intelligence (AI) in gastrointestinal endoscopy includes systems designed to interpret medical images and increase sensitivity during examination. This may be a promising solution to human biases and may provide support during diagnostic endoscopy.

Areas covered

This review aims to summarize and evaluate data supporting AI technologies in lower endoscopy, addressing their effectiveness, limitations, and future perspectives.

Expert opinion

Computer-aided detection (CADe) systems have been studied with promising results, allowing for an increase in adenoma detection rate (ADR), adenoma per colonoscopy (APC), and a reduction in adenoma miss rate (AMR). This may lead to an increase in the sensitivity of endoscopic examinations and a reduction in the risk of interval-colorectal cancer. In addition, computer-aided characterization (CADx) has also been implemented, aiming to distinguish adenomatous and non-adenomatous lesions through real‐time assessment using advanced endoscopic imaging techniques. Moreover, computer-aided quality (CADq) systems have been developed with the aim of standardizing quality measures in colonoscopy (e.g. withdrawal time and adequacy of bowel cleansing) both to improve the quality of examinations and set a reference standard for randomized controlled trials.

KEYWORDS:

• Endoscopy
• CAD
• ADR
• Colonoscopy
• Artificial Intelligence

Article highlights

• CADe system for colonoscopy is precise, reliable, and user-friendly, allowing increased ADR, APC, and lower AMR with similar operational time and low false-positive rate.

• CADx systems are promising, but further studies are needed to assess their efficacy.

• CADq systems will be able to increase the quality of colonoscopy and may work together with CADe to further enhance the detection rate of lesions.

• In the future, the role of AI will not replace humans but help endoscopists increase their efficiency, leveling the performance of different operators worldwide.

• The gradual spread of AI systems in colonoscopy will increase the effectiveness of colorectal cancer screening and surveillance worldwide.

• Key-quality measures of colonoscopy and the operator’s skills must always be maintained at high standards, even with the use of AI.

Declaration of interest

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

A reviewer on this manuscript is the CEO of Satisfai Health. The remaining reviewers have no other relevant financial relationships or otherwise to disclose.

Additional information

Funding

This paper received no funding.