Flat colorectal adenocarcinoma: a worrisome false negative of artificial intelligence-assisted colonoscopy

Endoscopy 2022; 54(11): 1122-1123
DOI: 10.1055/a-1738-9632

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¹Department of Endoscopy and Hepatogastroenterology, Pavillon L, Edouard Herriot Hospital, Lyon, France

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Clara Yzet

¹Department of Endoscopy and Hepatogastroenterology, Pavillon L, Edouard Herriot Hospital, Lyon, France

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Jérôme Rivory

¹Department of Endoscopy and Hepatogastroenterology, Pavillon L, Edouard Herriot Hospital, Lyon, France

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Guillaume Pontarollo

²Institute of Pathology Est, Hospices Civils de Lyon, Lyon, France

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El Houcine Latif

³Yansys Medical, Vichy, France

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Adrien Bartoli

⁴EnCoV, Institut Pascal, UMR 6602, CNRS/UCA/CHU, Clermont-Ferrand, France

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Mathieu Pioche

¹Department of Endoscopy and Hepatogastroenterology, Pavillon L, Edouard Herriot Hospital, Lyon, France

References
1 Ebigbo A, Palm C, Probst A. et al. A technical review of artificial intelligence as applied to gastrointestinal endoscopy: clarifying the terminology. Endosc Int Open 2019; 7: E1616-E1623
2 Repici A, Badalamenti M, Maselli R. et al. Efficacy of real-time computer-aided detection of colorectal neoplasia in a randomized trial. Gastroenterology 2020; 159: 512-520.e7
3 Wang P, Liu P, Glissen Brown JR. et al. Lower adenoma miss rate of computer-aided detection-assisted colonoscopy vs routine white-light colonoscopy in a prospective tandem study. Gastroenterology 2020; 159: 1252-1261.e5
4 Lafeuille P, Lambin T, Yzet C. et al. Flat colorectal sessile serrated polyp: an example of what artificial intelligence does not easily detect. Endoscopy 2021;
5 Lafeuille P, Rivory J, Lambin T. et al. Non-granular laterally spreading tumors: potential superficial cancers that artificial intelligence does not easily detect. Endoscopy 2021;