A Sessile Serrated Lesion Overlying a Submucosal Colonic Lipoma: An Endoscopic Rarity Identified Using Artificial Intelligence
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Citações na Scopus
1
Tipo de produção
article
Data de publicação
2023
Título da Revista
ISSN da Revista
Título do Volume
Editora
INT SCIENTIFIC INFORMATION, INC
Citação
AMERICAN JOURNAL OF CASE REPORTS, v.24, article ID e940499, 5p, 2023
Resumo
Objective: Rare coexistence of disease or pathologyBackground: Lipomas are benign, slow-growing mesenchymal neoplasms, more prevalent in females, with a peak incidence in the fifth to sixth decades of life. Generally, due to their low clinical relevance, they receive little attention in the literature. Uncommon in the colon, lipomas are most often identified as an incidentaloma in asymptomatic patients during colonoscopy, and overlapping with epithelial lesions is a rare finding. Serrated polyps used to be considered as hyperplastic polyps without any malignant potential; however, currently, the serrated pathway accounts for one-third of all colorectal cancers. Here, we describe a rare case of a sessile serrated lesion on a submucosal lipoma identified with the aid of artificial intelligence.Case Report: A 60-year-old woman underwent screening colonoscopy for colorectal cancer after a positive fecal immunochemical test. A high-definition colonoscopy with the aid of artificial intelligence (Fujifilm CAD EYE) was performed. A flat lesion at the right colon was diagnosed with white-light endoscopy simultaneously identified by artificial intelligence, which classified the lesion as hyperplastic. Resection was performed through mucosectomy, and a sign of naked fat was observed at the base of the resected lesion. Histopathology of the specimen characterized a submucosal lipoma associated with a sessile serrated lesion.Conclusions: We describe a rare case of sessile serrated lesion on a colon lipoma, identified with the aid of artificial intelligence. We carried out a brief literature review and discussed the main findings and aspects related to the literature.
Palavras-chave
Artificial Intelligence, Colonoscopy, Lipoma
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