Can a Polyp Detection and Characterization System Predict Complete Resection?
Artificial intelligence
Polyp detection software
Polyp resection
Polypectomy
Journal
Digestive diseases (Basel, Switzerland)
ISSN: 1421-9875
Titre abrégé: Dig Dis
Pays: Switzerland
ID NLM: 8701186
Informations de publication
Date de publication:
2022
2022
Historique:
received:
23
11
2020
accepted:
15
03
2021
pubmed:
4
5
2021
medline:
15
1
2022
entrez:
3
5
2021
Statut:
ppublish
Résumé
Artificial Intelligence (AI) is one of the most evolving fields in endoscopy. We aimed to test if a system for polyp detection and polyp characterization can be used to predict complete endoscopic resection of colon adenomas. We used the CAD-Eye AI system (Fujifilm Europe) in consecutive patients who received polypectomy using a cold snare. After resection, the submucosal space was flushed with water using an irrigation pump. Images were obtained using the CAD Eye system, and the characterization of the system was noted and afterward compared to histology of the removed specimen. In total, 17 polypectomies were observed, and in no case the AI was able to give information about resection status. First, the resection plane itself was classified as being adenomatous in all cases, while, second, all adenomas were resected completely, thus harboring no potential for overlying misinterpretations in the images. An AI system trained to characterize polyps in healthy surrounding colorectal mucosa cannot predict the state of resection after removal of the adenoma. This is explained by the training and programming. Endoscopists using AI from now on should learn about the basics of AI and the pitfalls in interpreting results from AI.
Identifiants
pubmed: 33940578
pii: 000516974
doi: 10.1159/000516974
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
115-118Informations de copyright
© 2021 The Author(s) Published by S. Karger AG, Basel.