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.
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.