Risk stratification of gallbladder polyps larger than 10 mm using high-resolution ultrasonography and texture analysis

A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma

BACKGROUND

Gallbladder carcinoma (GBC) is highly malignant, and its early diagnosis remains difficult. This study aimed to develop a deep learning model based on contrast-enhanced computed tomography (CT) images to assist radiologists in identifying GBC.

METHODS

We retrospectively enrolled 278 patients with gallbladder lesions (> 10 mm) who underwent contrast-enhanced CT and cholecystectomy and divided them into the training (n = 194) and validation (n = 84) datasets. The deep learning model was developed based on ResNet50 network. Radiomics and clinical models were built based on support vector machine (SVM) method. We comprehensively compared the performance of deep learning, radiomics, clinical models, and three radiologists.

RESULTS

Three radiomics features including LoG_3.0 gray-level size zone matrix zone variance, HHL first-order kurtosis, and LHL gray-level co-occurrence matrix dependence variance were significantly different between benign gallbladder lesions and GBC, and were selected for developing radiomics model. Multivariate regression analysis revealed that age ≥ 65 years [odds ratios (OR) = 4.4, 95% confidence interval (CI): 2.1-9.1, P < 0.001], lesion size (OR = 2.6, 95% CI: 1.6-4.1, P < 0.001), and CA-19-9 > 37 U/mL (OR = 4.0, 95% CI: 1.6-10.0, P = 0.003) were significant clinical risk factors of GBC. The deep learning model achieved the area under the receiver operating characteristic curve (AUC) values of 0.864 (95% CI: 0.814-0.915) and 0.857 (95% CI: 0.773-0.942) in the training and validation datasets, which were comparable with radiomics, clinical models and three radiologists. The sensitivity of deep learning model was the highest both in the training [90% (95% CI: 82%-96%)] and validation [85% (95% CI: 68%-95%)] datasets.

CONCLUSIONS

The deep learning model may be a useful tool for radiologists to distinguish between GBC and benign gallbladder lesions.

Risk stratification model for incidentally detected gallbladder polyps: A multicentre study

PURPOSE

We aimed to develop a 4-level risk stratification model using a scoring system based on conventional ultrasound to improve the diagnosis of gallbladder polyp.

METHOD

Patients with histopathologically confirmed gallbladder polyps were consecutively recruited from three medical centres. Conventional ultrasound findings and clinical characteristics were acquired prior to cholecystectomy. Risk factors for neoplastic and malignant polyps were used to build a risk stratification system via interobserver agreement and multivariate logistic regression analysis. The model was retrospectively trained using 264 pre-surgical samples and prospectively validated using 106 pre-surgical samples. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and malignant polyp rate.

RESULTS

In total, 370 patients (mean age, 51.68 ± 14.41 years, 156 men) were enrolled in this study. Size (≥12 mm), shape (oblate or round), single, vascularity, gallbladder stone or sludge were considered risk factors for neoplastic polyps. Size (≥14 mm), shape (oblate), single, disrupted gallbladder wall, and gallbladder stone or sludge were risk factors for malignant polyps (all p < 0.05). In the scoring system, the sensitivity, specificity, and AUC of score ≥ 9 in diagnosing neoplastic polyps were 0.766, 0.788, and 0.876 respectively; and the sensitivity, specificity, and AUC of score ≥ 15 in diagnosing malignant polyps were 0.844, 0.926, and 0.949 respectively. In our model, the malignancy rates at the four levels were 0 % (0/24), 1.28 % (2/156), 9.26 % (5/54), and 70.37 % (38/54), respectively.

CONCLUSIONS

The 4-level risk stratification model based on conventional ultrasound imaging showed excellent performance in classifying gallbladder polyps.

Endoscopic Diagnosis of Extra-Luminal Cancers

The last 2 decades have seen an emergence of endoscopic technologies and techniques allowing for minimally invasive modalities for assessing and sampling lesions outside of the gastrointestinal lumen, including the chest, abdomen, and pelvis. Incorporating these new endoscopic approaches has revolutionized the diagnosis and staging of extra-luminal malignancies and has enabled more accessible and safer tissue acquisition.

Radiomics-based machine learning and deep learning to predict serosal involvement in gallbladder cancer

OBJECTIVE

Our study aimed to determine whether radiomics models based on contrast-enhanced computed tomography (CECT) have considerable ability to predict serosal involvement in gallbladder cancer (GBC) patients.

MATERIALS AND METHODS

A total of 152 patients diagnosed with GBC were retrospectively enrolled and divided into the serosal involvement group and no serosal involvement group according to paraffin pathology results. The regions of interest (ROIs) in the lesion on all CT images were drawn by two radiologists using ITK-SNAP software (version 3.8.0). A total of 412 features were extracted from the CT images of each patient. The Mann‒Whitney U test was applied to identify features with significant differences between groups. Seven machine learning algorithms and a deep learning model based on fully connected neural networks (f-CNNs) were used for radiomics model construction. The prediction efficacy of the models was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Through the Mann‒Whitney U test, 75 of the 412 features extracted from the CT images of patients were significantly different between groups (P < 0.05). Among all the algorithms, logistic regression achieved the highest performance with an area under the curve (AUC) of 0.944 (sensitivity 0.889, specificity 0.8); the f-CNN deep learning model had an AUC of 0.916, and the model showed high predictive power for serosal involvement, with a sensitivity of 0.733 and a specificity of 0.801.

CONCLUSION

Radiomics models based on features derived from CECT showed convincing performances in predicting serosal involvement in GBC.

Risk stratification of gallbladder masses by machine learning-based ultrasound radiomics models: a prospective and multi-institutional study

OBJECTIVE

This study aimed to evaluate the diagnostic performance of machine learning (ML)-based ultrasound (US) radiomics models for risk stratification of gallbladder (GB) masses.

METHODS

We prospectively examined 640 pathologically confirmed GB masses obtained from 640 patients between August 2019 and October 2022 at four institutions. Radiomics features were extracted from grayscale US images and germane features were selected. Subsequently, 11 ML algorithms were separately used with the selected features to construct optimum US radiomics models for risk stratification of the GB masses. Furthermore, we compared the diagnostic performance of these models with the conventional US and contrast-enhanced US (CEUS) models.

RESULTS

The optimal XGBoost-based US radiomics model for discriminating neoplastic from non-neoplastic GB lesions showed higher diagnostic performance in terms of areas under the curves (AUCs) than the conventional US model (0.822-0.853 vs. 0.642-0.706, p < 0.05) and potentially decreased unnecessary cholecystectomy rate in a speculative comparison with performing cholecystectomy for lesions sized over 10 mm (2.7-13.8% vs. 53.6-64.9%, p < 0.05) in the validation and test sets. The AUCs of the XGBoost-based US radiomics model for discriminating carcinomas from benign GB lesions were higher than the conventional US model (0.904-0.979 vs. 0.706-0.766, p < 0.05). The XGBoost-US radiomics model performed better than the CEUS model in discriminating GB carcinomas (AUC: 0.995 vs. 0.902, p = 0.011).

CONCLUSIONS

The proposed ML-based US radiomics models possess the potential capacity for risk stratification of GB masses and may reduce the unnecessary cholecystectomy rate and use of CEUS.

CLINICAL RELEVANCE STATEMENT

The machine learning-based ultrasound radiomics models have potential for risk stratification of gallbladder masses and may potentially reduce unnecessary cholecystectomies.

KEY POINTS

• The XGBoost-based US radiomics models are useful for the risk stratification of GB masses. • The XGBoost-based US radiomics model is superior to the conventional US model for discriminating neoplastic from non-neoplastic GB lesions and may potentially decrease unnecessary cholecystectomy rate for lesions sized over 10 mm in comparison with the current consensus guideline. • The XGBoost-based US radiomics model could overmatch CEUS model in discriminating GB carcinomas from benign GB lesions.

Value of Micro Flow Imaging in the Prediction of Adenomatous Polyps

OBJECTIVE

The aim of this study was to assess the value of micro flow imaging (MFI) in distinguishing adenomatous polyps from cholesterol polyps.

METHODS

A total of 143 patients who underwent cholecystectomy for gallbladder polyps were retrospectively analyzed. B-mode ultrasound (BUS), color Doppler flow imaging (CDFI), MFI and contrast-enhanced ultrasound (CEUS) were performed before cholecystectomy. The weighted kappa consistency test was used to evaluate the agreement of vascular morphology among CDFI, MFI and CEUS. Ultrasound image characteristics, including BUS, CDFI and MFI images, were compared between adenomatous polyps and cholesterol polyps. The independent risk factors for adenomatous polyps were selected. The diagnostic performance of MFI combined with BUS in determining adenomatous polyps was compared with CDFI combined with BUS.

RESULTS

Of the 143 patients, 113 cases were cholesterol polyps, and 30 cases were adenomatous polyps. The vascular morphology of gallbladder polyps was more clearly depicted by MFI than CDFI, and it had better agreement with CEUS. Differences in maximum size, height/width ratio, hyperechoic spot and vascular intensity on CDFI and MFI images were significant between adenomatous polyps and cholesterol polyps (p < 0.05). The maximum size, height/width ratio, and vascular intensity on MFI images were independent risk factors for adenomatous polyps. For MFI combined with BUS, sensitivity, specificity and accuracy were 90.00%, 94.69% and 93.70%, respectively. Area under the receiver operating characteristic curve (AUC) of MFI combined with BUS was significantly higher than that of CDFI combined with BUS (AUC = 0.923 vs. 0.784).

CONCLUSION

Compared with CDFI combined with BUS, MFI combined with BUS had higher diagnostic performance in determining adenomatous polyps.

An integrated radiomics nomogram based on conventional ultrasound improves discriminability between fibroadenoma and pure mucinous carcinoma in breast

Objective

To evaluate the ability of integrated radiomics nomogram based on ultrasound images to distinguish between breast fibroadenoma (FA) and pure mucinous carcinoma (P-MC).

Methods

One hundred seventy patients with FA or P-MC (120 in the training set and 50 in the test set) with definite pathological confirmation were retrospectively enrolled. Four hundred sixty-four radiomics features were extracted from conventional ultrasound (CUS) images, and radiomics score (Radscore) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Different models were developed by a support vector machine (SVM), and the diagnostic performance of the different models was assessed and validated. A comparison of the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) was performed to evaluate the incremental value of the different models.

Results

Finally, 11 radiomics features were selected, and then Radscore was developed based on them, which was higher in P-MC in both cohorts. In the test group, the clinic + CUS + radiomics (Clin + CUS + Radscore) model achieved a significantly higher area under the curve (AUC) value (AUC = 0.86, 95% CI, 0.733-0.942) when compared with the clinic + radiomics (Clin + Radscore) (AUC = 0.76, 95% CI, 0.618-0.869, P > 0.05), clinic + CUS (Clin + CUS) (AUC = 0.76, 95% CI, 0.618-0.869, P< 0.05), Clin (AUC = 0.74, 95% CI, 0.600-0.854, P< 0.05), and Radscore (AUC = 0.64, 95% CI, 0.492-0.771, P< 0.05) models, respectively. The calibration curve and DCA also suggested excellent clinical value of the combined nomogram.

Conclusion

The combined Clin + CUS + Radscore model may help improve the differentiation of FA from P-MC.

Gallbladder polyps and adenomyomatosis

Incidental findings are commonly detected during examination of the gallbladder. Differentiating benign from malignant lesions is critical because of the poor prognosis associated with gallbladder malignancy. Therefore, it is important that radiologists and sonographers are aware of common incidental gallbladder findings, which undoubtedly will continue to increase with growing medical imaging use. Ultrasound is the primary imaging modality used to examine the gallbladder and biliary tree, but contrast-enhanced ultrasound and MRI are increasingly used. This review article focuses on two common incidental findings in the gallbladder; adenomyomatosis and gallbladder polyps. The imaging features of these conditions will be reviewed and compared between radiological modalities, and the pathology, epidemiology, natural history, and management will be discussed.

Contrast-Enhanced CT and Ultrasonography Features of Intracholecystic Papillary Neoplasm with or without associated Invasive Carcinoma

OBJECTIVE

To assess the contrast-enhanced CT and ultrasonography (US) findings of intracholecystic papillary neoplasm (ICPN) and determine the imaging features predicting ICPN associated with invasive carcinoma (ICPN-IC).

MATERIALS AND METHODS

In this retrospective study, we enrolled 119 consecutive patients, including 60 male and 59 female, with a mean age ± standard deviation of 63.3 ± 12.1 years, who had pathologically confirmed ICPN (low-grade dysplasia [DP] = 34, high-grade DP = 35, IC = 50) and underwent preoperative CT or US. Two radiologists independently assessed the CT and US findings, focusing on wall and polypoid lesion characteristics. The likelihood of ICPN-IC was graded on a 5-point scale. Univariable and multivariable logistic regression analyses were performed to identify significant predictors of ICPN-IC separately for wall and polypoid lesion findings. The performances of CT and US in distinguishing ICPN-IC from ICPN with DP (ICPN-DP) was evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

For wall characteristics, the maximum wall thickness (adjusted odds ratio [aOR] = 1.4; 95% confidence interval [CI]: 1.1-1.9) and mucosal discontinuity (aOR = 5.6; 95% CI: 1.3-23.4) on CT were independently associated with ICPN-IC. Among 119 ICPNs, 110 (92.4%) showed polypoid lesions. Regarding polypoid lesion findings, multiplicity (aOR = 4.0; 95% CI: 1.6-10.4), lesion base wall thickening (aOR = 6.0; 95% CI: 2.3-15.8) on CT, and polyp size (aOR = 1.1; 95% CI: 1.0-1.2) on US were independently associated with ICPN-IC. CT showed a higher diagnostic performance than US in predicting ICPN-IC (AUC = 0.793 vs. 0.676; p = 0.002).

CONCLUSION

ICPN showed polypoid lesions and/or wall thickening on CT or US. A thick wall, multiplicity, presence of wall thickening in the polypoid lesion base, and large polyp size are imaging findings independently associated with invasive cancer and may be useful for differentiating ICPN-IC from ICPN-DP.

A Bayesian network prediction model for gallbladder polyps with malignant potential based on preoperative ultrasound

BACKGROUND

It is important to identify gallbladder polyps (GPs) with malignant potential and avoid unnecessary cholecystectomy by constructing prediction model. The aim of the study is to develop a Bayesian network (BN) prediction model for GPs with malignant potential in a long diameter of 8-15 mm based on preoperative ultrasound.

METHODS

The independent risk factors for GPs with malignant potential were screened by χ² test and Logistic regression model. Prediction model was established and validated using data from 1296 patients with GPs who underwent cholecystectomy from January 2015 to December 2019 at 11 tertiary hospitals in China. A BN model was established based on the independent risk variables.

RESULTS

Independent risk factors for GPs with malignant potential included age, number of polyps, polyp size (long diameter), polyp size (short diameter), and fundus. The BN prediction model identified relationships between polyp size (long diameter) and three other variables [polyp size (short diameter), fundus and number of polyps]. Each variable was assigned scores under different status and the probabilities of GPs with malignant potential were classified as [0-0.2), [0.2-0.5), [0.5-0.8) and [0.8-1] according to the total points of [- 337, - 234], [- 197, - 145], [- 123, - 108], and [- 62,500], respectively. The AUC was 77.38% and 75.13%, and the model accuracy was 75.58% and 80.47% for the BN model in the training set and testing set, respectively.

CONCLUSION

A BN prediction model was accurate and practical for predicting GPs with malignant potential patients in a long diameter of 8-15 mm undergoing cholecystectomy based on preoperative ultrasound.

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.

Value of Conventional Ultrasound-based Scoring System in Distinguishing Adenomatous Polyps From Cholesterol Polyps

BACKGROUND AND AIM

Ultrasound has increased the detection of gallbladder polyps, but it has limitations in evaluating the nature of gallbladder polyps, especially the maximum size of 1.0 to 1.5 cm. We assessed the value of ultrasound scoring system based on independent predictive parameters in distinguishing adenomatous polyps from cholesterol polyps with the maximum size of 1.0 to 1.5 cm.

MATERIALS AND METHODS

We enrolled 163 patients with gallbladder polyps (1.0 to 1.5 cm) who underwent ultrasonography and cholecystectomy. Ultrasound image characteristics were compared between cholesterol polyps and adenomatous polyps in the training cohort from April 2018 to January 2020. An ultrasound scoring system was constructed in the training cohort, and its diagnostic performance was evaluated in the validation cohort from February 2020 to February 2021.

RESULTS

Maximum size, height/width ratio, stone or sludge, vascularity, and hyperechoic spot were significantly different between cholesterol polyps and adenomatous polyps in the training cohort ( P <0.05). The independent predictive parameters for adenomatous polyps were lower height/width ratio, presence of vascularity and absence of hyperechoic spot. The total score was as follows: (height/width ratio, <0.9=4, ≥0.9=0) + (vascularity, present=3, absent=0) + (hyperechoic spot, absent=2, present=0). The sensitivity, specificity and accuracy of ultrasound scoring system ≥5 for diagnosis of adenomatous polyps in the validation cohort were 73.33%, 80.49%, and 78.57%, respectively.

CONCLUSIONS

The ultrasound scoring system aids in distinguishing adenomatous polyps from cholesterol polyps, and effectively decreasing unnecessary cholecystectomy.

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.

Vector textures derived from higher order derivative domains for classification of colorectal polyps

Textures have become widely adopted as an essential tool for lesion detection and classification through analysis of the lesion heterogeneities. In this study, higher order derivative images are being employed to combat the challenge of the poor contrast across similar tissue types among certain imaging modalities. To make good use of the derivative information, a novel concept of vector texture is firstly introduced to construct and extract several types of polyp descriptors. Two widely used differential operators, i.e., the gradient operator and Hessian operator, are utilized to generate the first and second order derivative images. These derivative volumetric images are used to produce two angle-based and two vector-based (including both angle and magnitude) textures. Next, a vector-based co-occurrence matrix is proposed to extract texture features which are fed to a random forest classifier to perform polyp classifications. To evaluate the performance of our method, experiments are implemented over a private colorectal polyp dataset obtained from computed tomographic colonography. We compare our method with four existing state-of-the-art methods and find that our method can outperform those competing methods over 4%-13% evaluated by the area under the receiver operating characteristics curves.

Contrast-enhanced CT radiomics for prediction of recurrence-free survival in gallbladder carcinoma after surgical resection

OBJECTIVES

Gallbladder carcinoma (GBC) is the most common and aggressive biliary tract malignancy with high postoperative recurrence rates. This single-center study aimed to develop and validate a radiomics signature to estimate GBC recurrence-free survival (RFS).

METHODS

This study retrospectively included 204 consecutive patients with pathologically diagnosed GBC and were randomly divided into development (n = 142) and validation (n = 62) cohorts (7:3). The radiomics features of tumor were extracted from preoperative contrast-enhanced CT imaging for each patient. In the development cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression was employed to develop a radiomics signature for RFS prediction. The patients were stratified into high-score or low-score groups according to their median value of radiomics score. A nomogram was established using multivariable Cox regression by incorporating significant pathological predictors and radiomics signatures.

RESULTS

The radiomics signature based on 12 features could discriminate high-risk patients with poor RFS. Multivariate Cox analysis revealed that pT3/4 stage (hazard ratio, [HR] = 2.691), pN2 stage (HR = 3.60), poor differentiation grade (HR = 2.651), and high radiomics score (HR = 1.482) were independent risk variables associated with worse RFS and were incorporated to construct a nomogram. The nomogram displayed good prediction performance in estimating RFS with AUC values of 0.895, 0.935, and 0.907 at 1, 3, and 5 years, respectively.

CONCLUSIONS

The radiomics signature and combined nomogram may assist in predicting RFS in GBC patients.

KEY POINTS

• A radiomics signature extracted from preoperative contrast-enhanced CT can be a useful tool to preoperatively predict RFS of GBC. • T3/T4 stage, N2, poor tumor differentiation, and high radiomics score were positively associated with postoperative recurrence.

Radiomics of Biliary Tumors: A Systematic Review of Current Evidence

Biliary tumors are rare diseases with major clinical unmet needs. Standard imaging modalities provide neither a conclusive diagnosis nor robust biomarkers to drive treatment planning. In several neoplasms, texture analyses non-invasively unveiled tumor characteristics and aggressiveness. The present manuscript aims to summarize the available evidence about the role of radiomics in the management of biliary tumors. A systematic review was carried out through the most relevant databases. Original, English-language articles published before May 2021 were considered. Three main outcome measures were evaluated: prediction of pathology data; prediction of survival; and differential diagnosis. Twenty-seven studies, including a total of 3605 subjects, were identified. Mass-forming intrahepatic cholangiocarcinoma (ICC) was the subject of most studies (n = 21). Radiomics reliably predicted lymph node metastases (range, AUC = 0.729−0.900, accuracy = 0.69−0.83), tumor grading (AUC = 0.680−0.890, accuracy = 0.70−0.82), and survival (C-index = 0.673−0.889). Textural features allowed for the accurate differentiation of ICC from HCC, mixed HCC-ICC, and inflammatory masses (AUC > 0.800). For all endpoints (pathology/survival/diagnosis), the predictive/prognostic models combining radiomic and clinical data outperformed the standard clinical models. Some limitations must be acknowledged: all studies are retrospective; the analyzed imaging modalities and phases are heterogeneous; the adoption of signatures/scores limits the interpretability and applicability of results. In conclusion, radiomics may play a relevant role in the management of biliary tumors, from diagnosis to treatment planning. It provides new non-invasive biomarkers, which are complementary to the standard clinical biomarkers; however, further studies are needed for their implementation in clinical practice.

Longitudinal Ultrasound Assessment of Changes in Size and Number of Incidentally Detected Gallbladder Polyps

BACKGROUND. Previous European multisociety guidelines recommend routine follow-up imaging of gallbladder polyps (including polyps < 6 mm in patients without risk factors) and cholecystectomy for polyp size changes of 2 mm or more. OBJECTIVE. The purpose of this study was to assess longitudinal changes in the number and size of gallbladder polyps on serial ultrasound examinations. METHODS. This retrospective study included patients who underwent at least one ultrasound examination between January 1, 2010, and December 31, 2020 (as part of a hepatocellular carcinoma screening and surveillance program) that showed a gallbladder polyp. Number of polyps and size of largest polyp were recorded based primarily on review of examination reports. Longitudinal changes on serial examinations were summarized. Pathologic findings from cholecystectomy were reviewed. RESULTS. Among 9683 patients, 759 (8%) had at least one ultrasound examination showing a polyp. Of these, 434 patients (248 men, 186 women; mean age, 50.6 years) had multiple examinations (range, 2-19 examinations; mean, 4.8 examinations per patient; mean interval between first and last examinations, 3.6 ± 3.1 [SD] years; maximum interval, 11.0 years). Among these 434 patients, 257 had one polyp, 40 had two polyps, and 137 had more than two polyps. Polyp size was 6 mm or less in 368 patients, 7-9 mm in 52 patients, and 10 mm or more in 14 patients. Number of polyps increased in 9% of patients, decreased in 14%, both increased and decreased on serial examinations in 22%, and showed no change in 55%. Polyp size increased in 10% of patients, decreased in 16%, both increased and decreased on serial examinations in 18%, and showed no change in 56%. In 9% of patients, gallbladder polyps were not detected on follow-up imaging; in 6% of patients, gallbladder polyps were not detected on a follow-up examination but were then detected on later studies. No gallbladder carcinoma was identified in 19 patients who underwent cholecystectomy. CONCLUSION. Gallbladder polyps fluctuate in size, number, and visibility over serial examinations. Using a 2-mm threshold for growth, 10% increased in size. No carcinoma was identified. CLINICAL IMPACT. European multisociety guidelines that propose surveillance of essentially all polyps and a 2-mm size change as the basis for cholecystectomy are likely too conservative for clinical application.

Management and follow-up of gallbladder polyps: updated joint guidelines between the ESGAR, EAES, EFISDS and ESGE

Abstract

Main recommendations

Primary investigation of polypoid lesions of the gallbladder should be with abdominal ultrasound. Routine use of other imaging modalities is not recommended presently, but further research is needed. In centres with appropriate expertise and resources, alternative imaging modalities (such as contrast-enhanced and endoscopic ultrasound) may be useful to aid decision-making in difficult cases. Strong recommendation, low–moderate quality evidence.

Cholecystectomy is recommended in patients with polypoid lesions of the gallbladder measuring 10 mm or more, providing the patient is fit for, and accepts, surgery. Multidisciplinary discussion may be employed to assess perceived individual risk of malignancy. Strong recommendation, low-quality evidence.

Cholecystectomy is suggested for patients with a polypoid lesion and symptoms potentially attributable to the gallbladder if no alternative cause for the patient’s symptoms is demonstrated and the patient is fit for, and accepts, surgery. The patient should be counselled regarding the benefit of cholecystectomy versus the risk of persistent symptoms. Strong recommendation, low-quality evidence.

If the patient has a 6–9 mm polypoid lesion of the gallbladder and one or more risk factors for malignancy, cholecystectomy is recommended if the patient is fit for, and accepts, surgery. These risk factors are as follows: age more than 60 years, history of primary sclerosing cholangitis (PSC), Asian ethnicity, sessile polypoid lesion (including focal gallbladder wall thickening > 4 mm). Strong recommendation, low–moderate quality evidence.

If the patient has either no risk factors for malignancy and a gallbladder polypoid lesion of 6–9 mm, or risk factors for malignancy and a gallbladder polypoid lesion 5 mm or less, follow-up ultrasound of the gallbladder is recommended at 6 months, 1 year and 2 years. Follow-up should be discontinued after 2 years in the absence of growth. Moderate strength recommendation, moderate-quality evidence.

If the patient has no risk factors for malignancy, and a gallbladder polypoid lesion of 5 mm or less, follow-up is not required. Strong recommendation, moderate-quality evidence.

If during follow-up the gallbladder polypoid lesion grows to 10 mm, then cholecystectomy is advised. If the polypoid lesion grows by 2 mm or more within the 2-year follow-up period, then the current size of the polypoid lesion should be considered along with patient risk factors. Multidisciplinary discussion may be employed to decide whether continuation of monitoring, or cholecystectomy, is necessary. Moderate strength recommendation, moderate-quality evidence.

If during follow-up the gallbladder polypoid lesion disappears, then monitoring can be discontinued. Strong recommendation, moderate-quality evidence.

Source and scope

These guidelines are an update of the 2017 recommendations developed between the European Society of Gastrointestinal and Abdominal Radiology (ESGAR), European Association for Endoscopic Surgery and other Interventional Techniques (EAES), International Society of Digestive Surgery–European Federation (EFISDS) and European Society of Gastrointestinal Endoscopy (ESGE). A targeted literature search was performed to discover recent evidence concerning the management and follow-up of gallbladder polyps. The changes within these updated guidelines were formulated after consideration of the latest evidence by a group of international experts. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was adopted to define the strength of recommendations and the quality of evidence.

Key Point

• These recommendations update the 2017 European guidelines regarding the management and follow-up of gallbladder polyps.

The Role of EUS and EUS-FNA in Differentiating Benign and Malignant Gallbladder Lesions

Endoscopic ultrasonography (EUS) has greater spatial resolution than other diagnostic imaging modalities. In addition, if gallbladder lesions are found and gallbladder cancer is suspected, EUS is an indispensable modality, enabling detailed tests for invasion depth evaluation using the Doppler mode and ultrasound agents. Furthermore, for gallbladder lesions, EUS fine-needle aspiration (EUS-FNA) can be used to differentiate benign and malignant forms of conditions, such as xanthogranulomatous cholecystitis, and collect evidence before chemotherapy. EUS-FNA is also useful for highly precise and specific diagnoses. However, the prevention of bile leakage, an accidental symptom, is highly important. Advancements in next-generation sequencing (NGS) technologies facilitate the application of multiple parallel sequencing to EUS-FNA samples. Several biomarkers are expected to stratify treatment for gallbladder cancer; however, NGS can unveil potential predictive genomic biomarkers for the treatment response. It is believed that NGS may be feasible with samples obtained using EUS-FNA, further increasing the demand for EUS-FNA.

Current update on gallbladder carcinoma

Gallbladder (GB) carcinoma is a relatively rare malignancy and is associated with poor prognosis. Numerous risk factors have been associated with the development of GB carcinoma. GB carcinomas may present as mass lesions replacing the GB, focal or diffuse thickening of the GB wall, and intraluminal mass in the GB. Various benign conditions can mimic GB carcinoma. This article reviews the epidemiology, pathology, clinical findings, imaging features, and management of GB carcinomas.

How Can We Manage Gallbladder Lesions by Transabdominal Ultrasound?

The most important role of ultrasound (US) in the management of gallbladder (GB) lesions is to detect lesions earlier and differentiate them from GB carcinoma (GBC). To avoid overlooking lesions, postural changes and high-frequency transducers with magnified images should be employed. GB lesions are divided into polypoid lesions (GPLs) and wall thickening (GWT). For GPLs, classification into pedunculated and sessile types should be done first. This classification is useful not only for the differential diagnosis but also for the depth diagnosis, as pedunculated carcinomas are confined to the mucosa. Both rapid GB wall blood flow (GWBF) and the irregularity of color signal patterns on Doppler imaging, and heterogeneous enhancement in the venous phase on contrast-enhanced ultrasound (CEUS) suggest GBC. Since GWT occurs in various conditions, subdividing into diffuse and focal forms is important. Unlike diffuse GWT, focal GWT is specific for GB and has a higher incidence of GBC. The discontinuity and irregularity of the innermost hyperechoic layer and irregular or disrupted GB wall layer structure suggest GBC. Rapid GWBF is also useful for the diagnosis of wall-thickened type GBC and pancreaticobiliary maljunction. Detailed B-mode evaluation using high-frequency transducers, combined with Doppler imaging and CEUS, enables a more accurate diagnosis.

Association between Texture Analysis Parameters and Molecular Biologic KRAS Mutation in Non-Mucinous Rectal Cancer

Purpose

To evaluate the association between magnetic resonance imaging (MRI)-based texture parameters and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation in patients with non-mucinous rectal cancer.

Materials and Methods

Seventy-nine patients who had pathologically confirmed rectal non-mucinous adenocarcinoma with or without KRAS-mutation and had undergone rectal MRI were divided into a training (n = 46) and validation dataset (n = 33). A texture analysis was performed on the axial T2-weighted images. The association was statistically analyzed using the Mann-Whitney U test. To extract an optimal cut-off value for the prediction of KRAS mutation, a receiver operating characteristic curve analysis was performed. The cut-off value was verified using the validation dataset.

Results

In the training dataset, skewness in the mutant group (n = 22) was significantly higher than in the wild-type group (n = 24) (0.221 ± 0.283; -0.006 ± 0.178, respectively, p = 0.003). The area under the curve of the skewness was 0.757 (95% confidence interval, 0.606 to 0.872) with a maximum accuracy of 71%, a sensitivity of 64%, and a specificity of 78%. None of the other texture parameters were associated with KRAS mutation (p > 0.05). When a cut-off value of 0.078 was applied to the validation dataset, this had an accuracy of 76%, a sensitivity of 86%, and a specificity of 68%.

Conclusion

Skewness was associated with KRAS mutation in patients with non-mucinous rectal cancer.

Texture Analysis of Gray-Scale Ultrasound Images for Staging of Hepatic Fibrosis

Purpose

Materials and Methods

Results

Conclusion

Preoperative ultrasound-based radiomics score can improve the accuracy of the Memorial Sloan Kettering Cancer Center nomogram for predicting sentinel lymph node metastasis in breast cancer

PURPOSE

To develop a combined nomogram by incorporating the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram and ultrasound (US)-based radiomics score (Radscore) for predicting sentinel lymph node (SLN) metastasis in invasive breast cancer.

MATERIALS AND METHODS

This retrospective study was approved by the ethics committee of our institution, and written informed consent was waived. A total of 452 patients with invasive breast cancer who received SLN Biopsy in a single center were included between January 2016 and December 2019. The patients were divided into a training set (n = 318) and a validation set (n = 134). A total of 1216 features were extracted from the regions of interest (ROIs) of the tumors on conventional ultrasound. The maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to build the Radscore. Afterward, the diagnostic performance was assessed and validated. Comparison of receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were performed to evaluate the incremental value of the combined model.

RESULTS

Obtained from 18 features, the Radscore indicated a favorable discriminatory capability in the training set with an area under the curve (AUC) of 0.834, whereas a value of 0.770 was observed in the validation set. The AUC of the combined model was 0.901 (95 % confidence interval (95 % CI): 0.865-0.938) in the training set and 0.833 (95 % CI: 0.788-0.878) in the validation set. Both of them were superior to MSKCC or imaging Radscore alone (P < 0.05). DCA demonstrated that the combined model was superior to the others in terms of clinical practicability.

CONCLUSION

Preoperative US-based Radscore can improve the accuracy of clinical MSKCC nomogram for SLN metastasis prediction in breast cancer.

Texture analysis on bi-parametric MRI for evaluation of aggressiveness in patients with prostate cancer

PURPOSE

To evaluate the association between texture parameters based on bi-parametric MRI and Gleason score (GS) in patients with prostate cancer (PCa) and to evaluate diagnostic performance of any significant parameter for discriminating clinically significant cancer (CSC, GS ≥ 7) from non-CSC.

METHODS

A total of 116 patients who had been confirmed as prostate adenocarcinoma by radical prostatectomy or biopsy were divided into a training (n = 65) and a validation dataset (n = 51). All of the patients underwent preoperative 3T-MRI. Texture analysis was performed on axial T2WI and ADC maps (generated from b values, 0 and 1000 s/mm²) using dedicated software to cover the whole tumor volume. The correlation coefficient was calculated to evaluate the association between texture parameters and GS, and subsequent multiple regression analyses were applied for the significant parameters. To extract an optimal cut-off value for prediction of CSC, ROC curve analysis was performed.

RESULTS

In the training dataset, gray-level co-occurrence matrix (GLCM) entropy on ADC map was the only significant indicator for GS (coefficient of determination R², 0.4227, P = 0.0034). The AUC of GLCM entropy on ADC map was 0.825 (95% CI 0.711-0.907) with a maximum accuracy of 82%, a sensitivity of 86%, a specificity of 71%. When a cut-off value of 2.92 was applied to the validation dataset, it showed an accuracy of 92%, a sensitivity of 98%, and a specificity of 70%.

CONCLUSION

GLCM entropy on ADC map was associated with GS in patients with PCa and its estimated accuracy for discriminating CSC from non-CSC was 82%.

Gallbladder cancer revisited: the evolving role of a radiologist

Gallbladder cancer is the most common malignancy of the biliary tract. It is also the most aggressive biliary tumor with the shortest median survival duration. Complete surgical resection, the only potentially curative treatment, can be accomplished only in those patients who are diagnosed at an early stage of the disease. Majority (90%) of the patients present at an advanced stage and the management involves a multidisciplinary approach. The role of imaging in gallbladder cancer cannot be overemphasized. Imaging is crucial not only in detecting, staging, and planning management but also in guiding radiological interventions. This article discusses the role of a radiologist in the diagnosis and management of gallbladder cancer.

Gallbladder polyps: Correlation of size and clinicopathologic characteristics based on updated definitions

Background

Different perspectives exist regarding the clinicopathologic characteristics, biology and management of gallbladder polyps. Size is often used as the surrogate evidence of polyp behavior and size of ≥1cm is widely used as cholecystectomy indication. Most studies on this issue are based on the pathologic correlation of polyps clinically selected for resection, whereas, the data regarding the nature of polypoid lesions from pathology perspective -regardless of the cholecystectomy indication- is highly limited.

Methods

In this study, 4231 gallbladders -606 of which had gallbladder carcinoma- were reviewed carefully pathologically by the authors for polyps (defined as ≥2 mm). Separately, the cases that were diagnosed as “gallbladder polyps” in the surgical pathology databases were retrieved.

Results

643 polyps identified accordingly were re-evaluated histopathologically. Mean age of all patients was 55 years (range: 20–94); mean polyp size was 9 mm. Among these 643 polyps, 223 (34.6%) were neoplastic: I. Non-neoplastic polyps (n = 420; 65.4%) were smaller (mean: 4.1 mm), occurred in younger patients (mean: 52 years). This group consisted of fibromyoglandular polyps (n = 196) per the updated classification, cholesterol polyps (n = 166), polypoid pyloric gland metaplasia (n = 41) and inflammatory polyps (n = 17). II. Neoplastic polyps were larger (mean: 21 mm), detected in older patients (mean: 61 years) and consisted of intra-cholecystic neoplasms (WHO’s “adenomas” and “intracholecystic papillary neoplasms”, ≥1 cm; n = 120), their “incipient” version (<1 cm) (n = 44), polypoid invasive carcinomas (n = 26) and non-neoplastic polyps with incidental dysplastic changes (n = 33). In terms of size cut-off correlations, overall, only 27% of polyps were ≥1 cm, 90% of which were neoplastic. All (except for one) ≥2 cm were neoplastic. However, 14% of polyps <1 cm were also neoplastic. Positive predictive value of ≥1 cm cut-off -which is widely used for cholecystectomy indication-, was 94.3% and negative predictive value was 85%.

Conclusions

Approximately a third of polypoid lesions in the cholecystectomies (regardless of the indication) prove to be neoplastic. The vast majority of (90%) of polyps ≥1 cm and virtually all of those ≥2 cm are neoplastic confirming the current impression that polyps ≥1 cm ought to be removed. However, this study also illustrates that 30% of the neoplastic polyps are <1 cm and therefore small polyps should also be closely watched, especially in older patients.

Analysis of risk factors for gallbladder polyp formation - A retrospective study based on serial ultrasounds

AIM

To evaluate gallbladder polyp (GBP) formation related risk factors based on serial ultrasounds (US).

METHODS

Risk factors related GBP formation were retrospectively investigated among participants, who had US reexamination and interval >180 days in 5 years. After groups were divided based on US, we compared final data and initial data in GBP new incidence group. Then compared the data in GBP new incidence group and GBP(-) group.

RESULTS

Overall 20 447 participants were recruited, including 18 243 in GBP (-) group and 2204 in GBP group. The mean diameters of polyps were 0.455 ± 0.198 mm in initial and 0.420 ± 0.180 mm in final examination. GBP new incidence group included 797 participants. Percentage of GBP new incidence participants was higher than GBP resolved (36.16% vs. 11.71%). Participants in middle age were more likely have GBP size increase or new incidence, and participants in old age (≥60 years old) were with GBP size decrease or resolved. In GBP new incidence group, participants in final US showed higher FBG, higher LDL, lower HDL, higher ALT and higher AST than initial US. Compared with GBP (-) group and, same risk factors, in addition with age, were shown in GBP new incidence group, Logistic regression analysis show that higher LDL, lower HDL and higher AST were risk factors for GBP formation.

CONCLUSION

Participants in middle age were more likely to have GBP new incidence. Higher LDL, lower HDL and higher AST were independently risk factors for GBP formation.

Benign gallbladder diseases: Imaging techniques and tips for differentiating with malignant gallbladder diseases

Benign gallbladder diseases usually present with intraluminal lesions and localized or diffuse wall thickening. Intraluminal lesions of the gallbladder include gallstones, cholesterol polyps, adenomas, or sludge and polypoid type of gallbladder cancer must subsequently be excluded. Polyp size, stalk width, and enhancement intensity on contrast-enhanced ultrasound and degree of diffusion restriction may help differentiate cholesterol polyps and adenomas from gallbladder cancer. Localized gallbladder wall thickening is largely due to segmental or focal gallbladder adenomyomatosis, although infiltrative cancer may present similarly. Identification of Rokitansky-Aschoff sinuses is pivotal in diagnosing adenomyomatosis. The layered pattern, degree of enhancement, and integrity of the wall are imaging clues that help discriminate innocuous thickening from gallbladder cancer. High-resolution ultrasound is especially useful for analyzing the layering of gallbladder wall. A diffusely thickened wall is frequently seen in inflammatory processes of the gallbladder. Nevertheless, it is important to check for coexistent cancer in instances of acute cholecystitis. Ultrasound used alone is limited in evaluating complicated cholecystitis and often requires complementary computed tomography. In chronic cholecystitis, preservation of a two-layered wall and weak wall enhancement are diagnostic clues for excluding malignancy. Magnetic resonance imaging in conjunction with diffusion-weighted imaging helps to differentiate xathogranulomatous cholecystitis from gallbladder cancer by identifying the presence of fat and degree of diffusion restriction. Such distinctions require a familiarity with typical imaging features of various gallbladder diseases and an understanding of the roles that assorted imaging modalities play in gallbladder evaluations.

Deep learning-based decision support system for the diagnosis of neoplastic gallbladder polyps on ultrasonography: Preliminary results

Ultrasonography (US) has been considered image of choice for gallbladder (GB) polyp, however, it had limitations in differentiating between nonneoplastic polyps and neoplastic polyps. We developed and investigated the usefulness of a deep learning-based decision support system (DL-DSS) for the differential diagnosis of GB polyps on US. We retrospectively collected 535 patients, and they were divided into the development dataset (n = 437) and test dataset (n = 98). The binary classification convolutional neural network model was developed by transfer learning. Using the test dataset, three radiologists with different experience levels retrospectively graded the possibility of a neoplastic polyp using a 5-point confidence scale. The reviewers were requested to re-evaluate their grades using the DL-DSS assistant. The areas under the curve (AUCs) of three reviewers were 0.94, 0.78, and 0.87. The DL-DSS alone showed an AUC of 0.92. With the DL-DSS assistant, the AUCs of the reviewer’s improved to 0.95, 0.91, and 0.91. Also, the specificity of the reviewers was improved (65.1–85.7 to 71.4–93.7). The intraclass correlation coefficient (ICC) improved from 0.87 to 0.93. In conclusion, DL-DSS could be used as an assistant tool to decrease the gap between reviewers and to reduce the false positive rate.

Intraobserver and interobserver reliability in sonographic size measurements of gallbladder polyps

OBJECTIVES

To evaluate the intraobserver and interobserver reliability of gallbladder polyp measurements using transabdominal US and the factors that affect reliability.

METHODS

From November 2017 to February 2018, two radiologists measured the maximum diameter of 91 gallbladder polyps using transabdominal US. Intraobserver and interobserver agreement were determined using 95% Bland-Altman limits of agreement and intraclass correlation coefficients (ICCs). The effects of image settings, polyp location, and polyp size were evaluated by comparing ICCs using z tests.

RESULTS

The intraobserver agreement rates were 0.960 (95% confidence interval [CI], 0.939-0.973) for observer 1 and 0.962 (95% CI, 0.943-0.975) for observer 2. The ICCs between the two observers were 0.963 (95% CI, 0.926-0.979) for the first measurement and 0.973 (95% CI, 0.950-0.984) for the second measurement. The 95% limits of agreement on repeated measurements were 22.3-25.2% of the mean, and those between the two observers were 25.5-34.2% of the mean. ICCs for large polyps (≥ 5 mm) were significantly higher than those for small polyps (< 5 mm). There were no significant differences in the ICCs between image settings and polyp location.

CONCLUSIONS

Polyp size measurements using transabdominal US are highly repeatable and reproducible. Polyp size significantly affects the reliability of measurement. Diameter changes of approximately less than 25% may fall within the measurement error; this should be considered while interpreting the change in size during follow-up US, especially for small polyps.

KEY POINTS

• Gallbladder polyp size measurement using transabdominal US is highly repeatable and reproducible. • Diameter changes of approximately less than 25% should be interpreted carefully, especially in small polyps.

Cross-sectional Imaging of Gallbladder Carcinoma: An Update

Gallbladder Carcinoma (GBCA) is the most common biliary tract malignancy. As the disease is often diagnosed clinically in an advanced stage, the survival rates are dismal. Imaging studies allow for an early diagnosis of malignancy, though the findings may be indistinguishable from non-malignant disease processes affecting the gallbladder. Attempts have been made to make a specific diagnosis of GBCA at an early stage on imaging studies. Ultrasonography (US) is the most commonly employed technique for gallbladder evaluation. Gallbladder wall thickening is the most common finding of early GBCA and in this context, US is non-specific. Recently, contrast enhanced ultrasound has been shown to be effective in differentiating benign from malignant disease. Multidetector computed tomography represents the most robust imaging technique in evaluation of GBCA. It provides relatively sensitive evaluation of mural thickening, though it is not entirely specific and issues in differentiating GBCA from xanthogranulomatous cholecystitis do arise. Due to its superior soft tissue resolution, Magnetic Resonance Imaging (MRI) provides excellent delineation of gallbladder and biliary tree involvement. When coupled with functional MRI techniques, such as diffusion-weighted and perfusion imaging, it provides a useful problem solving tool for interrogating the malignant potential of nonspecific gallbladder lesions and detection of metastases. Positron emission tomography has a role in detection of distant metastases and following patients following treatment for malignancy. We review the current role of various imaging modalities in evaluating patients with GBCA.