• Arch Iran Med · Dec 2024

    Radiological Findings for Distinguishing Between Xanthogranulomatous Cholecystitis and Gallbladder Cancer.

    • Ahmet Bozer and Nagihan Durgun.
    • Department of Radiology, Izmir City Hospital, Izmir, Turkey.
    • Arch Iran Med. 2024 Dec 1; 27 (12): 674682674-682.

    BackgroundXanthogranulomatous cholecystitis (XGC) is a rare, chronic gallbladder inflammation often mistaken for gallbladder cancer (GBC) on imaging. Accurate differentiation is vital for appropriate treatment. This study aims to enhance computed tomography (CT) scan diagnostic accuracy for distinguishing XGC from GBC.MethodsThis retrospective study included patients diagnosed with XGC and GBC between 2014 and 2023. CT images of 70 patients (16 GBC, 54 XGC) were reviewed. Radiologists assessed CT parameters: gallbladder wall thickening, intramural hypoattenuating nodules, enhancement characteristics, mucosal line continuity, pericholecystic fat stranding, presence of stones, bile duct dilatation, hepatic invasion, invasion to adjacent structures, and lymph node size.ResultsAmong 70 patients, there were 38 males (54%) and 32 females (46%), with a median age of 62 years. GBC patients were significantly older (median age 72 years) compared to XGC patients (60 years) (P=0.001). Diffuse gallbladder wall thickening was more frequent in XGC (70%) than GBC (12.5%) (P<0.001). Continuous mucosal lines and intramural hypoattenuating nodules were more common in XGC (P<0.001 and P=0.010, respectively). Intrahepatic bile duct dilatation and invasion to adjacent structures were significantly linked with GBC (P<0.001 and P=0.043). Lymph nodes with a short axis>8 mm indicated GBC (P<0.001), with a cutoff providing 71.4% sensitivity and 84% specificity (AUC: 0.843, P<0.001). CT showed 75% sensitivity (95% CI: 48-93%), 74% specificity (95% CI: 60%-85%), and 74% accuracy (95% CI: 62%-84%).ConclusionCT imaging can effectively differentiate XGC from GBC, and larger studies can further improve diagnostic accuracy.© 2024 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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