Overtreatment of Nonneoplastic Gallbladder Polyps due to Inadequate Routine Ultrasound Assessment

Management of incidentally detected gallbladder polyps: a review of clinical scenarios using the 2022 SRU gallbladder polyp consensus guidelines

Gallbladder (GB) polyps are a common incidental finding on sonography, but only a small fraction of polyps become GB cancer. The Society of Radiologists in Ultrasound (SRU) consensus committee recently performed an extensive literature review and published guidelines for GB polyp follow-up/management to provide clarity among the many heterogeneous recommendations that are available to clinicians. As these guidelines have become adopted into clinical practice, challenging clinical scenarios have arisen including GB polyps in primary sclerosing cholangitis (PSC), high risk geographic/genetic patient populations, shrinking polyps, pedunculated vs sessile polyps, thin vs thick stalked polyps, vascular polyps and multiple polyps. According to the SRU guidelines, clinicians should refer to gastroenterology guidelines when managing GB polyps in patients with known PSC. If patients at high geographic/genetic risk develop GB polyps, 'extremely low risk' polyps may be managed as 'low risk' and 10-14 mm 'extremely low risk' or '7-14 mm' low risk polyps that decrease in size by ≥ 4 mm require no follow-up. Thin-stalked or pedunculated polyps are 'extremely low risk' and thick-stalked pedunculated polyps are 'low risk'. Sessile polyps are 'low risk' but should receive immediate specialist referral if features suggestive of GB cancer are present. Neither polyp multiplicity nor vascularity impact risk of GB cancer and follow up should be based on morphology alone.

Comparison of the Size Measurement of Gallbladder Polyps by Three Different Radiologists in Abdominal Ultrasonography

BACKGROUND

There is little information regarding the size measurement differences in gallbladder (GB) polyps performed by different radiologists on abdominal ultrasonography (US).

AIM

To reveal the differences in GB polyp size measurements performed by different radiologists on abdominal US.

METHODS

From June to September 2022, the maximum diameter of 228 GB polyps was measured twice on abdominal US by one of three radiologists (a third-year radiology resident [reader A], a radiologist with 7 years of experience in abdominal US [reader B], and an abdominal radiologist with 8 years of experience in abdominal US [reader C]). Intra-reader agreements for polyp size measurements were assessed by intraclass correlation coefficient (ICC). A Bland-Altman plot was used to visualize the differences between the first and second size measurements in each reader.

RESULTS

Reader A, reader B, and reader C evaluated 65, 77, and 86 polyps, respectively. The mean size of measured 228 GB polyps was 5.0 ± 1.9 mm. Except for the case where reader A showed moderate intra-reader agreement (0.726) for polyps with size ≤ 5 mm, all readers showed an overall high intra-reader reliability (reader A, ICC = 0.859; reader B, ICC = 0.947, reader C, ICC = 0.948), indicative of good and excellent intra-reader agreements. The 95% limit of agreement of reader A, B, and C was 1.9 mm of the mean in all three readers.

CONCLUSIONS

GB polyp size measurement on abdominal US showed good or excellent intra-reader agreements. However, size changes of approximately less than 1.9 mm should be interpreted carefully because these may be within the measurement error.

The value of CT radiomics combined with deep transfer learning in predicting the nature of gallbladder polypoid lesions

BACKGROUND

Computed tomography (CT) radiomics combined with deep transfer learning was used to identify cholesterol and adenomatous gallbladder polyps that have not been well evaluated before surgery.

PURPOSE

To investigate the potential of various machine learning models, incorporating radiomics and deep transfer learning, in predicting the nature of cholesterol and adenomatous gallbladder polyps.

MATERIAL AND METHODS

A retrospective analysis was conducted on clinical and imaging data from 100 patients with cholesterol or adenomatous polyps confirmed by surgery and pathology at our hospital between September 2015 and February 2023. Preoperative contrast-enhanced CT radiomics combined with deep learning features were utilized, and t-tests and least absolute shrinkage and selection operator (LASSO) cross-validation were employed for feature selection. Subsequently, 11 machine learning algorithms were utilized to construct prediction models, and the area under the ROC curve (AUC), accuracy, and F1 measure were used to assess model performance, which was validated in a validation group.

RESULTS

The Logistic algorithm demonstrated the most effective prediction in identifying polyp properties based on 10 radiomics combined with deep learning features, achieving the highest AUC (0.85 in the validation group, 95% confidence interval = 0.68-1.0). In addition, the accuracy (0.83 in the validation group) and F1 measure (0.76 in the validation group) also indicated strong performance.

CONCLUSION

The machine learning radiomics combined with deep learning model based on enhanced CT proves valuable in predicting the characteristics of cholesterol and adenomatous gallbladder polyps. This approach provides a more reliable basis for preoperative diagnosis and treatment of these conditions.

Ultrasound Surveillance of Small, Incidentally Detected Gallbladder Polyps: Projected Benefits by Sex, Age, and Comorbidity Level

OBJECTIVE

Incidentally detected gallbladder polyps are commonly encountered when performing upper abdominal ultrasound. Our purpose was to estimate the life expectancy (LE) benefit of ultrasound-based gallbladder surveillance in patients with small (6-7 to <10 mm), incidentally detected gallbladder polyps, accounting for patient sex, age, and comorbidity level.

METHODS

We developed a decision-analytic Markov model to evaluate hypothetical cohorts of women and men with small gallbladder polyps, with varying age (66-80 years) and comorbidity level (none, mild, moderate, severe). Drawing from current evidence, in the base case, we assumed no increased risk of gallbladder cancer in patients with small gallbladder polyps. To estimate maximal possible LE gains from surveillance, we assumed perfect cancer control consequent to 5 years of surveillance. We varied key assumptions including cancer risk and test performance characteristics in sensitivity analysis.

RESULTS

Projected LE gains from surveillance were <3 days across most cohorts and scenarios evaluated. For 66- and 80-year-olds with no comorbidities, LE gains were 1.46 and 1.45 days, respectively, for women, and 0.67 and 0.75 days for men. With 10 years of surveillance, LE gains increased to 2.94 days for 66-year-old women with no comorbidities (men: 1.35 days). If we assumed a 10% increase in gallbladder cancer risk among individuals with polyps, LE gains increased slightly to 1.60 days for 66-year-old women with no comorbidities (men: 0.74 days). Results were sensitive to test performance and surgical mortality.

DISCUSSION

Even under unrealistic, optimistic assumptions of cancer control, ultrasound surveillance of incidentally detected small gallbladder polyps provided limited benefit.

RadioGraphics Update: New Follow-up and Management Recommendations for Polypoid Lesions of the Gallbladder

Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new informaion such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.

Incidental Findings of Gallbladder and Bile Ducts-Management Strategies: General Aspects, Gallbladder Polyps and Gallbladder Wall Thickening-A World Federation of Ultrasound in Medicine and Biology (WFUMB) Position Paper

The World Federation of Ultrasound in Medicine and Biology (WFUMB) is addressing the issue of incidental findings with a series of position papers to give advice on characterization and management. The biliary system (gallbladder and biliary tree) is the third most frequent site for incidental findings. This first part of the position paper on incidental findings of the biliary system is related to general aspects, gallbladder polyps and other incidental findings of the gallbladder wall. Available evidence on prevalence, diagnostic work-up, malignancy risk, follow-up and treatment is summarized with a special focus on ultrasound techniques. Multiparametric ultrasound features of gallbladder polyps and other incidentally detected gallbladder wall pathologies are described, and their inclusion in assessment of malignancy risk and decision- making on further management is suggested.

Management of Incidentally Detected Gallbladder Polyps: Society of Radiologists in Ultrasound Consensus Conference Recommendations

Gallbladder polyps (also known as polypoid lesions of the gallbladder) are a common incidental finding. The vast majority of gallbladder polyps smaller than 10 mm are not true neoplastic polyps but are benign cholesterol polyps with no inherent risk of malignancy. In addition, recent studies have shown that the overall risk of gallbladder cancer is not increased in patients with small gallbladder polyps, calling into question the rationale for frequent and prolonged follow-up of these common lesions. In 2021, a Society of Radiologists in Ultrasound, or SRU, consensus conference was convened to provide recommendations for the management of incidentally detected gallbladder polyps at US. See also the editorial by Sidhu and Rafailidis in this issue.

Gallbladder Polyp Classification in Ultrasound Images Using an Ensemble Convolutional Neural Network Model

Differential diagnosis of true gallbladder polyps remains a challenging task. This study aimed to differentiate true polyps in ultrasound images using deep learning, especially gallbladder polyps less than 20 mm in size, where clinical distinction is necessary. A total of 501 patients with gallbladder polyp pathology confirmed through cholecystectomy were enrolled from two tertiary hospitals. Abdominal ultrasound images of gallbladder polyps from these patients were analyzed using an ensemble model combining three convolutional neural network (CNN) models and a 5-fold cross-validation. True polyp diagnosis with the ensemble model that learned only using ultrasonography images achieved an area under receiver operating characteristic curve (AUC) of 0.8960 and accuracy of 83.63%. After adding patient age and polyp size information, the diagnostic performance of the ensemble model improved, with a high specificity of 88.35%, AUC of 0.9082, and accuracy of 87.61%, outperforming the individual CNN models constituting the ensemble model. In the subgroup analysis, the ensemble model showed the best performance with AUC of 0.9131 for polyps larger than 10 mm. Our proposed ensemble model that combines three CNN models classifies gallbladder polyps of less than 20 mm in ultrasonography images with high accuracy and can be useful for avoiding unnecessary cholecystectomy with high specificity.