ArticleEuropean radiology2018
Risk stratification of gallbladder polyps larger than 10 mm using high-resolution ultrasonography and texture analysis.
Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 48 citations in OpenAlex.
- An integrative deep learning model based on dual-mode ultrasound for diagnosing gallbladder polyps.Insights into imaging · 2026Article
- Ultrasound of the Gallbladder-An Update on Measurements, Reference Values, Variants and Frequent Pathologies: A Scoping Review.Life (Basel, Switzerland) · 2025Review
- Current status of artificial intelligence analysis for the diagnosis of gallbladder diseases using ultrasonography: a scoping review.Translational gastroenterology and hepatology · 2025Review
- Article
- Comparison of the Size Measurement of Gallbladder Polyps by Three Different Radiologists in Abdominal Ultrasonography.Tomography (Ann Arbor, Mich.) · 2024Article
- Radiomics-based machine learning and deep learning to predict serosal involvement in gallbladder cancer.Abdominal radiology (New York) · 2024Article
- Risk stratification of gallbladder masses by machine learning-based ultrasound radiomics models: a prospective and multi-institutional study.European radiology · 2023Article
- [Recent Updates on Management and Follow-up of Gallbladder Polyps].The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi · 2023Review
- Gallbladder polyps and adenomyomatosis.The British journal of radiology · 2023Review
- Contrast-Enhanced CT and Ultrasonography Features of Intracholecystic Papillary Neoplasm with or without associated Invasive Carcinoma.Korean journal of radiology · 2023Article
- An integrated radiomics nomogram based on conventional ultrasound improves discriminability between fibroadenoma and pure mucinous carcinoma in breast.Frontiers in oncology · 2023Article
- Imaging patterns of wall thickening type of gallbladder cancer.Clinical and experimental hepatology · 2022Review
- Vector textures derived from higher order derivative domains for classification of colorectal polyps.Visual computing for industry, biomedicine, and art · 2022Article
- Management and follow-up of gallbladder polyps: updated joint guidelines between the ESGAR, EAES, EFISDS and ESGE.European radiology · 2022Article
- Radiomics of Biliary Tumors: A Systematic Review of Current Evidence.Diagnostics (Basel, Switzerland) · 2022Review
- Computed tomography texture-based radiomics analysis in gallbladder cancer: initial experience.Clinical and experimental hepatology · 2021Article
- The Role of EUS and EUS-FNA in Differentiating Benign and Malignant Gallbladder Lesions.Diagnostics (Basel, Switzerland) · 2021Review
- How Can We Manage Gallbladder Lesions by Transabdominal Ultrasound?Diagnostics (Basel, Switzerland) · 2021Review
- Association between Texture Analysis Parameters and Molecular Biologic KRAS Mutation in Non-Mucinous Rectal Cancer.Taehan Yongsang Uihakhoe chi · 2021Article
- Texture Analysis of Gray-Scale Ultrasound Images for Staging of Hepatic Fibrosis.Taehan Yongsang Uihakhoe chi · 2021Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo assess important features for risk stratification of gallbladder (GB) polyps >10 mm using high-resolution ultrasonography (HRUS) and texture analysis.
methodsWe included 136 patients with GB polyps (>10 mm) who underwent both HRUS and cholecystectomy (non-neoplastic, n = 58; adenomatous, n = 32; and carcinoma, n = 46). Two radiologists retrospectively assessed HRUS findings and texture analysis. Multivariate analysis was performed to identify significant predictors for neoplastic polyps and carcinomas.
resultsSingle polyp (OR, 3.680-3.856) and larger size (OR, 1.450-1.477) were independently associated with neoplastic polyps (p < 0.05). In a single or polyp >14 mm, sensitivity for differentiating neoplastic from non-neoplastic polyps was 92.3%. To differentiate carcinoma from adenoma, sessile shape (OR, 9.485-41.257), larger size (OR, 1.267-1.303), higher skewness (OR, 6.382) and lower grey-level co-occurrence matrices (GLCM) contrast (OR, 0.963) were significant predictors (p < 0.05). In a polyp >22 mm or sessile, sensitivity for differentiating carcinomas from adenomas was 93.5-95.7%. If a polyp demonstrated at least one HRUS finding and at least one texture feature, the specificity for diagnosing carcinoma was increased to 90.6-93.8%.
conclusionIn a GB polyp >10 mm, single and diameter >14 mm were useful for predicting neoplastic polyps. In neoplastic polyps, sessile shape, diameter >22 mm, higher skewness and lower GLCM contrast were useful for predicting carcinoma. KEY POINTS: • Risk of neoplastic polyp is low in <14 mm and multiple polyps • A sessile polyp or >22 mm has increased risk for GB carcinomas • Higher skewness and lower GLCM contrast are predictors of GB carcinoma • HRUS is useful for risk stratification of GB polyps >1 cm.
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