Deep-learning enabled ultrasound based detection of gallbladder cancer in northern India: a prospective diagnostic study.

Background: Gallbladder cancer (GBC) is highly aggressive. Diagnosis of GBC is challenging as benign gallbladder lesions can have similar imaging features. We aim to develop and validate a deep learning (DL) model for the automatic detection of GBC at abdominal ultrasound (US) and compare its diagnostic performance with that of radiologists. Methods: In this prospective study, a multiscale, second-order pooling-based DL classifier model was trained (training and validation cohorts) using the US data of patients with gallbladder lesions acquired between August 2019 and June 2021 at the Postgraduate Institute of Medical Education and research, a tertiary care hospital in North India. The performance of the DL model to detect GBC was evaluated in a temporally independent test cohort (July 2021-September 2022) and was compared with that of two radiologists. Findings: The study included 233 patients in the training set (mean age, 48 ± (2SD) 23 years; 142 women), 59 patients in the validation set (mean age, 51.4 ± 19.2 years; 38 women), and 273 patients in the test set (mean age, 50.4 ± 22.1 years; 177 women). In the test set, the DL model had sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of 92.3% (95% CI, 88.1-95.6), 74.4% (95% CI, 65.3-79.9), and 0.887 (95% CI, 0.844-0.930), respectively for detecting GBC which was comparable to both the radiologists. The DL-based approach showed high sensitivity (89.8-93%) and AUC (0.810-0.890) for detecting GBC in the presence of stones, contracted gallbladders, lesion size <10 mm, and neck lesions, which was comparable to both the radiologists (p = 0.052-0.738 for sensitivity and p = 0.061-0.745 for AUC). The sensitivity for DL-based detection of mural thickening type of GBC was significantly greater than one of the radiologists (87.8% vs. 72.8%, p = 0.012), despite a reduced specificity. Interpretation: The DL-based approach demonstrated diagnostic performance comparable to experienced radiologists in detecting GBC using US. However, multicentre studies are warranted to explore the potential of DL-based diagnosis of GBC fully. Funding: None.

Contrast Enhanced CT Versus MRI for Accurate Diagnosis of Wall-thickening Type Gallbladder Cancer.

Introduction: Diagnosis of wall-thickening type gallbladder cancer (GBC) is challenging. Computed tomography (CT) and magnetic resonance imaging (MRI) are commonly utilized to evaluate gallbladder wall thickening. However, there is a lack of data comparing the performance of CT and MRI for the detection of wall-thickening type GBC. Aim: We aim to compare the diagnostic accuracy of CT and MRI in diagnosis of wall-thickening type GBC. Materials and methods: This prospective study comprised consecutive patients suspected of wall-thickening type GBC who underwent preoperative contrast-enhanced CT and MRI. The final diagnosis was based on the histopathology of the resected gallbladder lesion. Two radiologists independently reviewed the characteristics of gallbladder wall thickening at CT and MRI. The association of CT and MRI findings with histological diagnosis and the interobserver agreement of CT and MRI findings were assessed. Results: Thirty-three patients (malignancy, 13 and benign, 20) were included. None of the CT findings were significantly associated with GBC. However, at MRI, heterogeneous enhancement, indistinct interface with the liver, and diffusion restriction were significantly associated with malignancy (P = 0.006, <0.001, and 0.005, respectively), and intramural cysts were significantly associated with benign lesions (P = 0.012). For all MRI findings, the interobserver agreement was substantial to perfect (kappa = 0.697-1.000). At CT, the interobserver agreement was substantial to perfect (k = 0.631-1.000). Conclusion: These findings suggest that MRI may be preferred over CT in patients with suspected wall thickening type GBC. However, larger multicenter studies must confirm our findings.

Proposal for a new morphological "combined type" of gallbladder cancer: description of radiopathological characteristics and comparison with other morphological types.

OBJECTIVE: To describe the radiopathological characteristics of a new morphological "combined type" of gallbladder cancer (GBC) and compare it with the mass replacing gallbladder and thickening types of GBC. MATERIALS AND METHODS: The imaging and pathological details of consecutive patients with GBC between August 2020 and December 2022 were retrospectively reviewed. Two radiologists reviewed computed tomography/magnetic resonance imaging in consensus for the morphological type of GBC. The radiologists classified GBC as mass replacing gallbladder, wall thickening, and combined type. The combined type was defined as a mass arising from the thickened wall of an adequately distended gallbladder that extended exophytically into the adjacent liver parenchyma. The presence of calculi, site, and size of lesion, biliary/portal vein involvement, liver, lymph node, and omental metastases was compared among the various types. The pathological characteristics were also compared. RESULTS: Of the 481 patients (median age 55 years, 63.2% females) included in the study, mass replacing gallbladder, wall thickening, and combined-type GBC were seen in 42.8% (206/481), 40.5% (195/481), and 16.6% (80/481) of patients, respectively. In the combined type of GBC, biliary/portal vein involvement was seen in 63.7% (51/80) and 7.5% (6/80) of patients. Liver, lymph node, and omental metastases were seen in 67.5% (54/80), 40% (32/80), and 41.2% (33/80) patients, respectively. Liver metastases were significantly more common in the combined type (p = 0.002). There were no significant differences in pathological characteristics among the various types. CONCLUSION: Combined-type GBC is less common than the mass replacing gallbladder and thickening types and is associated with a higher risk of liver metastases.

Multiparametric MR imaging with diffusion-weighted, intravoxel incoherent motion, diffusion tensor, and dynamic contrast-enhanced perfusion sequences to assess gallbladder wall thickening: a prospective study based on surgical histopathology.

OBJECTIVE: To investigate the diagnostic performance of a multiparametric magnetic resonance imaging (MRI) protocol comprising quantitative MRI (diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and dynamic contrast-enhanced (DCE) perfusion MRI) and conventional MRI in the characterization of gallbladder wall thickening (GWT). METHODS: This prospective study comprised consecutive adults with GWT who underwent multiparametric MRI between July 2020 and April 2022. Two radiologists evaluated the MRI independently. The final diagnosis was based on surgical histopathology. The association of MRI parameters with malignant GWT was evaluated. The area under the curve (AUC) for the quantitative MRI parameters and diagnostic performance of conventional, and multiparametric MRI were compared. The interobserver agreement between two radiologists was calculated. RESULTS: Thirty-five patients (mean age, 56 years, 23 females) with GWT (25 benign and ten malignant) were evaluated. The quantitative MRI parameters significantly associated with malignant GWT were apparent diffusion coefficient on DWI (p = 0.007) and mean diffusivity (MD) on DTI (p = 0.013), perfusion fraction (f) on IVIM (p = 0.033), time to peak enhancement (TTP, p = 0.008), and wash in rate (p = 0.049) on DCE-MRI. TTP had the highest AUC of 0.790, followed by MD (0.782) and f (0.742) (p = 0.213) for predicting malignant GWT. Multiparametric MRI had significantly higher sensitivity (90% vs. 80%, p = 0.045) than conventional MRI for diagnosing malignant GWT. The two radiologists' reading had substantial to near-perfect agreement (kappa = 0.639-1) and moderate to strong correlation (interclass correlation coefficient = 0.5-0.88). CONCLUSION: Multiparametric protocol incorporating advanced sequences improved the diagnostic performance of MRI for differentiating benign and malignant GWT. KEY POINTS: • Multiparametric MRI had 90% sensitivity and 88% specificity for diagnosing malignant GWT, compared to 80% sensitivity and 88% specificity for conventional CE-MRI. • Among the quantitative MRI parameters, TTP (perfusion-MRI) had the highest AUC of 0.790, followed by MD (0.782) and IVIM-f (0.742). • For most quantitative MRI parameters, there was moderate to strong agreement (ICC = 0.5-0.88).

Grayscale ultrasonography findings for characterization of gallbladder wall thickening in non-acute setting: a systematic review and meta-analysis.

BACKGROUND: The accurate characterization of gallbladder wall thickening (GWT) into benign or malignant on ultrasound (US) is a significant challenge. METHODS: We searched the MEDLINE and EMBASE databases for studies reporting two-dimensional grayscale US in benign and malignant GWT. The pooled prevalence was calculated using a generalized linear mixed method with a random-effects model. The pooled sensitivity and specificity were calculated using a bivariate random-effects model. RESULTS: Of the 7309 studies screened by titles, 73 studies with 18,008 patients were included. The most common findings in xanthogranulomatous cholecystitis (XGC) were lack of wall disruption and intramural hypoechoic nodules while adenomyomatosis (ADM) was frequently associated with intramural cysts and intramural echogenic foci. Echogenic foci, lack of gallbladder wall disruption, and hypoechoic nodules had a sensitivity of 89%, 77%, and 66% and specificity of 86%, 51%, and 80%, respectively for the diagnosis of benign GWT. Focal thickening and indistinct liver interface had a sensitivity of 75% and 55% and specificity of 64% and 69%, respectively for the diagnosis of malignant GWT. CONCLUSION: intramural features (echogenic foci, hypoechoic nodules), gallbladder wall disruption, and liver interface are useful US features for the characterization of GWT.

Gallbladder reporting and data system (GB-RADS) for risk stratification of gallbladder wall thickening on ultrasonography: an international expert consensus.

The Gallbladder Reporting and Data System (GB-RADS) ultrasound (US) risk stratification is proposed to improve consistency in US interpretations, reporting, and assessment of risk of malignancy in gallbladder wall thickening in non-acute setting. It was developed based on a systematic review of the literature and the consensus of an international multidisciplinary committee comprising expert radiologists, gastroenterologists, gastrointestinal surgeons, surgical oncologists, medical oncologists, and pathologists using modified Delphi method. For risk stratification, the GB-RADS system recommends six categories (GB-RADS 0-5) of gallbladder wall thickening with gradually increasing risk of malignancy. GB-RADS is based on gallbladder wall features on US including symmetry and extent (focal vs. circumferential) of involvement, layered appearance, intramural features (including intramural cysts and echogenic foci), and interface with the liver. GB-RADS represents the first collaborative effort at risk stratifying the gallbladder wall thickening. This concept is in line with the other US-based risk stratification systems which have been shown to increase the accuracy of detection of malignant lesions and improve management.

Imaging patterns of wall thickening type of gallbladder cancer.

Gallbladder cancer (GBC) has a high incidence in certain geographical regions. Morphologically, GBC presents as a mass replacing the gallbladder, a polypoidal lesion, or wall thickening. The incidence of preoperative diagnosis of wall thickening type of GBC is less well studied. The patterns of mural involvement and extramural spread are not well described in the literature. Additionally, wall thickening in the gallbladder does not always indicate malignancy and can be secondary to inflammatory or benign gallbladder diseases and extracholecystic causes and systemic pathologies. Objective reporting of gallbladder wall thickening will help us appreciate GBC's early features. In this review, we illustrate the imaging patterns of wall thickening type of GBC.

Computed tomography texture-based radiomics analysis in gallbladder cancer: initial experience.

Aim of the study: To investigate computed tomography (CT) texture parameters in suspected gallbladder cancer (GBC) and assess its utility in predicting histopathological grade and overall survival. Material and methods: This retrospective pilot study included consecutive patients with clinically suspected GBC. CT images, clinical, and histological or cytological data were retrieved from the database. CT images were reviewed by two radiologists. A single axial CT section in the portal venous phase was selected for texture analysis. Radiomic feature extraction was done using commercially available research software. Results: Thirty-eight patients (31 females, mean age 53.1 years) were included. Malignancy was confirmed in 29 patients in histopathology or cytology analysis, and the rest had no features of malignancy. Exophytic gallbladder mass with associated gallbladder wall thickening was present in 22 (58%) patients. Lymph nodal, liver, and omental metastases were present in 10, 1, and 3 patients, respectively. The mean overall survival was 9.7 months. There were significant differences in mean and kurtosis at medium texture scales to differentiate moderately differentiated and poorly differentiated adenocarcinoma (p < 0.05). The only texture parameter that was significantly associated with survival was kurtosis (p = 0.020) at medium texture scales. In multivariate analysis, factors found to be significantly associated with length of overall survival were mean number of positive pixels (p = 0.02), skewness (p = -0.046), kurtosis (0.018), and standard deviation (p = 0.045). Conclusions: Our preliminary results highlight the potential utility of CT texture-based radiomics analysis in patients with GBC. Medium texture scale parameters including both mean and kurtosis, or kurtosis alone, may help predict the histological grade and survival, respectively.