Differential Diagnosis of Pancreatic Serous Cystadenomas and Mucinous Cystadenomas: Utility of Texture Analysis in Combination with Morphological Characteristics

Abstract Background Texture analysis of medical images has been reported to be a reliable technique for differential diagnosis of neoplasms. This study was to investigate the performance of textural features and the combined performance of textural features and morphological characteristics in the differential diagnosis of pancreatic serous and mucinous cystadenomas. Methods We retrospectively reviewed 59 patients with pancreatic serous cystadenoma and 32 patients with pancreatic mucinous cystadenoma at our hospital. Textural features were extracted using the LifeX software, and the least absolute shrinkage and selection operator (LASSO) method was applied to select the textural features. The differential diagnostic abilities of morphological features, textural features, and their combination were evaluated using receiver operating characteristic (ROC) analysis, with the area under the receiver operating characteristic curve (AUC) as the main indicator. Results The combination of morphological characteristics and textural features showed a higher AUC (0.893, 95% CI 0.816-0.970) than use of morphological characteristics (0.783, 95% CI 0.665-0.900) or textural features (0.777, 95% CI 0.673-0.880) alone. Conclusions In conclusion, our preliminary results highlighted the potential of CT texture analysis to discriminate pancreatic serous cystadenomas from mucinous cystadenomas. Furthermore, the combination of morphological and textural features can significantly improve the diagnostic performance, which may provide a reliable method to select patients with indication of surgical intervention in consideration of the different treatment principles of the two diseases.