Artificial intelligence and colonoscopy: current status and future perspectives

Abstract

Objective

Application of artificial intelligence in medicine is now attracting substantial attention. In the field of gastrointestinal endoscopy, computer‐aided diagnosis for colonoscopy is the most investigated area, although it is still in the pre‐clinical phase. Because colonoscopy is performed by humans, it is inherently an imperfect procedure. Computer‐aided diagnosis assistance is expected to improve its quality regarding automated polyp detection and characterization (i.e., predicting the polyp's pathology). It could help prevent endoscopists from missing polyps as well as provide a precise optical diagnosis for those detected. Ultimately, these functions that computer‐aided diagnosis provides could produce a higher adenoma detection rate and reduce the cost of polypectomy for hyperplastic polyps.

Methods and Results

Currently, research on automated polyp detection has been limited to experimental assessments using an algorithm based on ex vivo videos or static images. The performance for clinical use was reported to have >90% sensitivity with acceptable specificity. In contrast, the research on automated polyp characterization seems to surpass that for polyp detection. Prospective studies of in vivo use of artificial intelligence technologies have been reported by several groups, some of which showed a >90% negative predictive value for differentiating diminutive (≤5 mm) rectosigmoid adenomas, which exceeded the threshold for optical biopsy.

Conclusion

We introduce the potential of using computer‐aided diagnosis for colonoscopy and describe the most recent conditions for regulatory approval for artificial intelligence‐assisted medical devices.

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