Related Experiment Video
Updated: Apr 6, 2026

Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024
US characteristics for the prediction of neoplasm in gallbladder polyps 10 mm or larger
Jin Sil Kim1, Jeong Kyong Lee2, Yookyung Kim1
1Department of Radiology and Medical Research Institute, School of Medicine, Ewha Womans University, 911-1 Mok-dong, Yangcheon-gu, Seoul, 158-710, Korea.
Purpose:
To evaluate the characteristics of gallbladder polyps 10 mm or larger to predict a neoplasm in US examinations.
Materials And Methods:
Fifty-three patients with gallbladder polyps ≥ 10 mm with follow-up images or pathologic diagnosis were included in the retrospective study. All images and reports were reviewed to determine the imaging characteristics of gallbladder polyps. Univariate and multivariate analyses were used to evaluate predictors for a neoplastic polyp.
Results:
A neoplastic polyp was verified in 12 of 53 patients and the mean size was 13.9 mm. The univariate analysis revealed that adjacent gallbladder wall thickening, larger size (≥15 mm), older age (≥57 years), absence of hyperechoic foci in a polyp, CT visibility, sessile shape, a solitary polyp, and an irregular surface were significant predictors for a neoplastic polyp. In the multivariate analysis, larger size (≥15 mm) was a significant predictor for a neoplastic polyp.
Conclusion:
A polyp size ≥15 mm was the strongest predictor for a neoplastic polyp with US. The hyperechoic foci in a polyp and CT visibility would be useful indicators for the differentiation of a neoplastic polyp, in addition to the established predictors.
Key Points:
• A polyp size ≥15 mm is the strongest predictor for a neoplastic polyp with US. • Hyperechoic foci in a polyp and CT visibility are new predictors. • The rate of malignancy is low in polyps even 10 mm or larger (15.1 %).
More Related Videos
06:55Diagnosis of Neoplasia in Barrett’s Esophagus using Vital-dye Enhanced Fluorescence Imaging
Published on: May 11, 2014
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025