Purpose: The objective of our study was to evaluate the combined hyperdense gallbladder wall-lumen sign on computed tomography (CT) in diagnosing gangrenous cholecystitis. Material and methods: We retrospectively reviewed the unenhanced CT scans of surgically proven cases of acute gangrenous (GCh) and non-gangrenous cholecystitis (nonGCh). Eleven cases of pathologically proven acute gangrenous cholecystitis and 12 consecutive cases of surgically proven acute non-gangrenous cholecystitis that underwent CT at our institute were included in the study so as to have 1 : 1 control. The Hounsfield unit (HU) value of the gallbladder wall and intraluminal bile was measured. Interobserver variability for individual CT findings was also assessed. Results: The gangrenous cholecystitis group had significantly higher HU values of wall and bile (median value of 33 HU vs. 21 HU and median value of 21 HU vs. 8.5 HU, respectively, p < 0.05). The area under the receiver operator characteristic curve for HU lumen was 0.80 (95% CI: 0.62-0.98, p = 0.014) with an ideal cutoff at 31.5 HU, where the sensitivity was 54.5% and specificity was 91.7%. HU lumen has an even better assessment for gangrenous cholecystitis with AUC of its ROC as 0.92 (95% CI: 0.80-1.00, p = 0.001) with an ideal cutoff at 12.5 HU, where the sensitivity was 81.8% and specificity was 91.7%. The combined wall-lumen cutoff is 35 HU with sensitivity of 100% and specificity of 75%. Conclusion: A cutoff CT density value of the gallbladder wall of more than 31.5 HU, intraluminal bile more than 12.5 HU, and combined wall-lumen HU of more than 35 can predict GCh.

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Colorectal cancers are more common in the West than in Asian subcontinent. An increasing trend in the occurrence of colorectal signet cell carcinomas has been observed, exhibiting association with inflammatory bowel disease. Its distinct clinical features, pathognomonic, histologic, and radiologic appearance make it an unmissable entity. We report two such cases in the background of inflammatory bowel disease. We aim to familiarize our readers with its cross-sectional imaging features.