Echelard P, Roy SF, Trinh VQH, et al. - Researchers aimed at investigating if an incidental gallbladder carcinoma can be identified using a pre-grossing algorithm. In addition, they examined the utility of the algorithm in detecting high-grade dysplasia. A Classification and Regression Tree (CART) algorithm was developed by performing a retrospective study of clinical, pathological, and radiological findings in cholecystectomy recipients on a test set. This study was performed including 5,663 cholecystectomies, with 18 cases of incidental gallbladder carcinoma and 11 cases of high-grade dysplasia. In multivariate analysis, they identified the following as statistically significant distinguishing factors: patient age, surgical approach, operation duration, dilatation of the biliary tract and gallbladder gross anomalies. Unsupervised testing with a conditional inference tree indicated the utility of age, procedure type, and operation duration in identification of incidental gallbladder carcinoma from controls, while grossing parameters are required in high-grade dysplasia to identify half of the cases (5/11)