Current and future implications of artificial intelligence in colonoscopy

Abstract

Gastrointestinal endoscopy has proved to be a perfect context for the development of artificial intelligence (AI) systems that can aid endoscopists in many tasks of their daily activities. Lesion detection (computer-aided detection, CADe) and lesion characterization (computer-aided characterization, CADx) during colonoscopy are the clinical applications of AI in gastroenterology for which by far the most evidence has been published. Indeed, they are the only applications for which more than one system has been developed by different companies, is currently available on the market, and may be used in clinical practice. Both CADe and CADx, alongside hopes and hypes, come with potential drawbacks, limitations and dangers that must be known, studied and researched as much as the optimal uses of these machines, aiming to stay one step ahead of the possible misuse of what will always be an aid to the clinician and never a substitute. An AI revolution in colonoscopy is on the way, but the potential uses are infinite and only a fraction of them have currently been studied. Future applications can be designed to ensure all aspects of colonoscopy quality parameters and truly deliver a standardization of practice, regardless of the setting in which the procedure is performed. In this review, we cover the available clinical evidence on AI applications in colonoscopy and offer an overview of future directions.

Artificial intelligence in endoscopy: Overview, applications, and future directions

“…[ 5 ] CADq uses AI to evaluate the quality of endoscopic procedures for the purpose of improving the accuracy and efficiency of diagnostic assessments as well as improving overall administration of the procedure. [ 7 ] Below, we provide an overview of these domains [ Figure 2 ], with specific applications discussed in detail in the following section.…”

Optical diagnosis in still images of colorectal polyps: comparison between expert endoscopists and PolyDeep, a Computer-Aided Diagnosis system

“…CAD system is a general term that encompasses the ability to detect and classify colonic lesions. There is a large amount of evidence of the impact of the Computer-Aided Detection (CADe) systems in diagnostic colonoscopy ( 9 , 10 ). However, Computer-Aided Diagnosis (CADx) systems need more research and the information related to the optical diagnosis is, so far, limited with a wide area of improvement ( 8 ).…”

“…However, Computer-Aided Diagnosis (CADx) systems need more research and the information related to the optical diagnosis is, so far, limited with a wide area of improvement ( 8 ). In the available literature, there are reviews with meta-analysis and several controlled clinical studies of CADe and CADx (refers to the ability of detect and classify colorectal lesions respectively) systems which provide significant evidence of the benefits of integrating CAD systems in colonoscopies ( 8 , 10 ). The implementation of these systems may improve and establish a minimum quality standard in clinical practice ( 10 ).…”