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A prospective multicenter randomized controlled trial on artificial intelligence assisted colonoscopy for enhanced

Dong Kyun Park^1,2, Eui Joo Kim¹, Jong Pil Im³

¹Division of Gastroenterology, Department of Internal Medicine, Gachon University Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774 beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea.

Scientific Reports

|October 25, 2024

Summary

An AI-assisted colon polyp detection program significantly improved polyp detection rates (PDR) and adenoma detection rates (ADR) during colonoscopies. This artificial intelligence tool enhances colorectal cancer prevention by aiding clinicians in identifying more polyps.

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Area of Science:

Medical Imaging
Artificial Intelligence in Medicine
Gastroenterology

Background:

Colorectal cancer (CRC) screening and prevention rely heavily on colon polyp detection and removal during colonoscopy.
Early detection of polyps is crucial for reducing CRC incidence and mortality.

Purpose of the Study:

To develop an artificial intelligence (AI)-assisted colon polyp detection program using the RetinaNet algorithm.
To verify the clinical utility and performance of the AI program in a real-world setting.

Main Methods:

Development of an AI model using a fully anonymized dataset with 10-fold cross-validation (9,639 training images, 1,070 validation images per fold).
Transfer learning was applied using a still image-based model to video data from 56 patients for real-time endoscopy application.
Prospective randomized controlled trial across six institutions involving 805 patients to compare AI-assisted colonoscopy with standard colonoscopy.

Main Results:

The AI-assisted group demonstrated significantly higher polyp detection rates (PDR) compared to the standard colonoscopy group.
Adenoma detection rates (ADR) were also significantly improved in the AI-assisted group.
Multivariate analysis indicated an odds ratio (OR) of 1.50 for polyp detection when using the AI model.

Conclusions:

The AI-assisted colon polyp detection program is clinically beneficial, enhancing polyp identification during colonoscopy.
Implementation of this AI tool can lead to improved adenoma detection rates, thereby strengthening colorectal cancer prevention strategies.