Pratap, Thara

Abstract Gallbladder (GB) cancer is an aggressive biliary malignancy with a silent clinical course, leading to delayed diagnosis and poor outcomes. Early detection and accurate staging are pivotal for guiding management, yet diagnosis remains challenging due to overlapping imaging features with benign pathologies. This review synthesizes the current state-of-the-art imaging modalities, including ultrasound (USG), multiphase computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)/CT, and PET/MRI, highlighting their roles in diagnosis, staging, and treatment planning. A systematic USG-based triaging helps in management decision. Algorithmic approach to GB masses and incidental GB polyps is also covered with future directives on artificial intelligence and radiomics.

Alcohol use disorder (AUD) is a significant public health challenge, affecting multiple organs and organ systems, and fetal health. Additionally, AUD also significantly contributes to self-harm and road accidents. Beyond its health effects, AUD creates economic and political challenges, including escalating treatment costs and the complex alcohol regulation policies. Despite global impact, AUD remains under-addressed in countries like India due to cultural norms and limited resources. Early recognition of AUD is vital for better outcomes, relying on thorough clinical evaluation and patient history. However, denial, inebriation, or lack of awareness often delays diagnosis. Imaging techniques like ultrasound, CT, and MRI effectively depict AUD-related organ damage and aid in detecting chronic alcohol use. Radiologists play a crucial role in identifying these manifestations, contributing to its early detection and treatment. This review article highlights the imaging of alcohol use related disorders and diseases affecting different organs and organ systems at various stages. The review is presented in two parts: the first focuses on alcohol burden, alcohol metabolism and toxicity, and imaging findings of AUD-related abdominal diseases and disorders.

Abstract Objective The aim of this study was to identify the most useful contrast-enhanced computed tomography (CECT) features for differentiating pancreatic ductal adenocarcinoma (PDAC) from mass-forming chronic pancreatitis (MFCP) in chronic calcific pancreatitis (CCP). Methods In total, 101 patients with CCP and focal pancreatic mass formed the study group. Sixteen qualitative and four quantitative parameters were analyzed. Qualitative parameters included size, site, margin, intralesional hypodensity, collateral duct sign, abrupt pancreatic duct (PD) cutoff, upstream PD dilatation, distal pancreatic atrophy, double duct sign, enhancement pattern, contrast attenuation, peripancreatic inflammation, vascular involvement, regional nodes, and metastasis. Quantitative parameters included duct-to-body ratio, common bile duct (CBD) diameter, main pancreatic duct (MPD) diameter, and carcinoembryonic antigen 19-9 (CA19-9). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for prediction of PDAC. A receiver operating characteristic (ROC) curve analysis was performed and the area under ROC curve (AUROC) was calculated to determine diagnostic accuracy to assess the optimal cutoff. Results PDAC was confirmed in 48 patients and MFCP in 53 patients. A duct-to-body ratio greater than 0.48 had 95.5% sensitivity, 83.3% specificity, 80.8% PPV, 96.2% NPV, and 88.5% accuracy for predicting PDAC. A CBD diameter cutoff ≥9.5 mm had an accuracy of 75% (p < 0.019) and an MPD cutoff ≥6.25 mm had an accuracy of 67.8% (p = 0.008) for predicting PDAC. On binary logistic regression, the duct-to-body ratio was found to be the significant independent factor associated with malignancy. Conclusion A duct-to-body ratio greater than 0.48, intralesional hypodensity, and abrupt duct cutoff are the most helpful computed tomography (CT) features for distinguishing PDAC from MFCP in CCP. On binary logistic regression, the duct-to-body ratio was found to be a significant independent factor. Interspersed normal parenchyma was observed as a very specific sign of MFCP. Intraparenchymal hypodensity has high specificity, but further validation is needed.