Gallbladder polyps and the challenge of distinguishing benign lesions from cancer

Dooren, M. van; Reuver, Philip R. de

doi:10.1002/ueg2.12287

Cited by 4 publications

(1 citation statement)

References 20 publications

(31 reference statements)

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“…[82] Preoperative US characteristics for polyps sized ≥ 10 mm to 15 mm have been proposed in various prediction models to distinguish the risk of neoplastic polyps. [83][84][85][86] Suspected findings include a single polyp, cross-sectional area ≥ 85 mm 2 , broad base, and medium echogenicity. [87] Size is the main risk factor, while multiplicity is related to benign disease.…”

Section: Diagnosismentioning

confidence: 99%

Contemporary diagnosis and management of gallbladder polyps

Pavlidis,

Galanis,

Pavlidis

2023

Gastroenterol Funct Med

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Gallbladder (GB) polyps are present in 5%–10% of the general population and consist of true neoplastic polyps (adenomas) and pseudopolyps (predominantly cholesterol, inflammatory, hyperplastic, focal adenomyomatosis). True polyps, although relatively rare neoplastic lesions (0.5%) are considered an important factor in malignant transformation and cancer development (5%) when their size is ≥ 1 cm. Given that it is essential to diagnose GB adenocarcinoma at an early stage to optimize therapeutic management, controversy exists about whether cholecystectomy is always necessary. Their imaging characteristics, size ≥ 1 cm, age > 50 years and genetic predisposition determine the indications for immediate cholecystectomy. In younger patients with polyps < 1 cm in size and without a familial history of GB carcinoma, imaging follow-up by ultrasound (US) seems to be a reasonable recommended policy. A scoring system by multivariate analysis (cross-sectional area > 123 mm2, positive blood flow signal, age > 55.5 years, alanine aminotransferase (ALT) levels > 50 U/L and an ALT/AST (aspartate aminotransferase) ratio > 0.77) can accurately predict true polyps. The widely accepted size threshold for US follow-up is 7 mm, and for intervention, it is 10 mm. Computed tomography or better magnetic resonance imaging can overcome any misdiagnosis of conventional US incidental findings alone that may lead to potentially unnecessary operations. In challenging cases, high-resolution US, novel three-dimensional US, endoscopic US or contrast-enhanced endoscopic US could be helpful. Novel microflow imaging can safely predict polyps. Risk factors for malignancy include age > 60 years, large gallstones, primary sclerosing cholangitis, Asian ethnicity and sessile polyps accompanied by focal gallbladder wall thickening > 4 mm. For polyps sized 6–9 mm, the absence of growth at recommended follow-up (6 months, one year, and two years) indicates treatment discontinuation; however, it is not required for size < 5 mm without risk factors. In addition to laparoscopic cholecystectomy, the standard management, novel interventional modalities preserving the GB in selected cases include per-oral transmural endoscopic resection of GB polyps after a bridge of endoscopic US-guided cholecystostomy or laparoscopic gallbladder-preserving polypectomy. Generally, there are still no precise and strong evidence-based guidelines; thus, the management policy of GB polyps should be individualized in ambiguous cases.

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Section: Diagnosismentioning

confidence: 99%

Contemporary diagnosis and management of gallbladder polyps

Pavlidis,

Galanis,

Pavlidis

2023

Gastroenterol Funct Med

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Preoperative prediction model for non-neoplastic and benign neoplastic polyps of the gallbladder

Wang,

Peng,

Liu

et al. 2024

European Journal of Surgical Oncology

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Establishing a Preoperative Predictive Model for Gallbladder Adenoma and Cholesterol Polyps Based on Machine Learning: A Multicentre Retrospective Study

Wang,

Qu,

Zeng

et al. 2024

Preprint

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Background With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenomas with a higher preoperative malignancy risk is crucial. This study aimed to establish a preoperative prediction model capable of accurately distinguishing between gallbladder adenomas and cholesterol polyps using machine learning algorithms. Materials and Methods We retrospectively analysed the patients' clinical baseline data, serological indicators, and ultrasound imaging data. Using 12 machine learning algorithms, 110 combination predictive models were constructed. The models were evaluated using internal and external cohort validation, receiver operating characteristic curves, area under the curve (AUC) values, calibration curves, and clinical decision curves to determine the best predictive model. Results Among the 110 combination predictive models, the Support Vector Machine + Random Forest (SVM + RF) model demonstrated the highest AUC values of 0.972 and 0.922 in the training and internal validation sets, respectively, indicating an optimal predictive performance. The model-selected features included gallbladder wall thickness, polyp size, polyp echo, and pedicle. Evaluation through external cohort validation, calibration curves, and clinical decision curves further confirmed its excellent predictive ability for distinguishing gallbladder adenomas from cholesterol polyps. Additionally, this study identified age, adenosine deaminase level, and metabolic syndrome as potential predictive factors for gallbladder adenomas. Conclusion This study employed the latest machine learning combination algorithms and preoperative ultrasound imaging data to construct an SVM + RF predictive model, enabling effective preoperative differentiation of gallbladder adenomas and cholesterol polyps. These findings will assist clinicians in accurately assessing the risk of GPLs and providing personalised treatment strategies.

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Gallbladder polyps and the challenge of distinguishing benign lesions from cancer

Cited by 4 publications

References 20 publications

Contemporary diagnosis and management of gallbladder polyps

Contemporary diagnosis and management of gallbladder polyps

Preoperative prediction model for non-neoplastic and benign neoplastic polyps of the gallbladder

Establishing a Preoperative Predictive Model for Gallbladder Adenoma and Cholesterol Polyps Based on Machine Learning: A Multicentre Retrospective Study

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