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Diagnostic algorithm of magnifying endoscopy with narrow band imaging for superficial non‐ampullary duodenal epithelial tumors
Author(s) -
Kikuchi Daisuke,
Hoteya Shu,
Iizuka Toshiro,
Kimura Ryusuke,
Kaise Mitsuru
Publication year - 2014
Publication title -
digestive endoscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.5
H-Index - 56
eISSN - 1443-1661
pISSN - 0915-5635
DOI - 10.1111/den.12282
Subject(s) - medicine , narrow band imaging , pathological , endoscopy , radiology , pathology , diagnostic accuracy , pattern analysis , artificial intelligence , computer science
Background and Aim A novel diagnostic algorithm for magnifying endoscopy with narrow band imaging ( ME‐NBI ) for superficial non‐ampullary duodenal epithelial tumors ( SNADET ) is needed because of diagnostic difficulties. Methods In the present study, ME‐NBI images taken prior to endoscopic treatment were retrospectively analyzed to investigate the relationship between ME‐NBI findings and pathological findings. Lesions displaying a single surface pattern were classified as monotype, and those displaying multiple surface patterns as mixed type. Surface pattern was classified as preserved, micrified, or absent. In addition, vascular pattern was classified as absent, network, intrastructural vascular ( ISV ), or unclassified. Results According to the revised Vienna classification, 100% (23/23) of mixed‐type lesions were category 4/5 tumors, whereas approximately 50% (10/23) of monotype lesions were category 3 tumors. In the monotype lesions, the probability of category 4/5 tumor was 100% (2/2) in lesions with an unclassified vascular pattern, 64.3% (9/14) in lesions with an ISV pattern, 33.3% (1/3) in lesions with an absent pattern, and 25.0% (1/4) in lesions with a network pattern. Conclusion These findings suggest the possibility of developing an effective diagnostic algorithm for ME‐NBI for SNADET by determining their surface pattern and vascular pattern.