RESUMO
Objective: To investigate the value of texture analysis based on enhanced renal CT for identification of chromophobe cell renal carcinoma (CCRC) and renal oncocytoma (RO). Methods: CT images of 64 patients with CCRC and 31 with RO were retrospectively analyzed. ITK-SNAP version 4.11.0 software was used to delineate the region of interest, and A.K.Version v3.0.0.R software was used to extract texture features. Random forest model was established using texture features included in random forest algorithm. Logistic regression was used to evaluate the discriminative the efficacy of the established models for differential diagnosis of CCRC and RO. Results: The first 20 texture parameters selected with random forest algorithm from corticomedullary phase, nephrographic phase and both of them, with weight values from high to low, were evaluated with Logistic regression, and the AUC values were 0.876, 0.861 and 0.945, respectively. Conclusion: Texture analysis based on enhanced renal CT images has clinical value in differential diagnosis of CCRC and RO.