Two-dimensional Texture Analysis Based on CT Images to Differentiate Pancreatic Lymphoma and Pancreatic Adenocarcinoma: A Preliminary Study

Objective: To retrospectively assess the diagnostic performance of texture analysis and characteristics of CT images for the discrimination of pancreatic lymphoma (PL) from pancreatic adenocarcinoma (PA).

Methods: Fifteen patients with pathologically proved PL were compared with 30 age-matched controls with PA in a 1:2 ratio. Patients underwent a CT scan with three phases including the precontrast phase, the arterial phase, and the portal vein phase. The regions of interest of PA and PL were drawn and analyzed to derive texture parameters with MaZda software. Texture features and CT characteristics were selected for the discrimination of PA and PL by the least absolute shrinkage and selection operator and logistic regression analysis. Receiver operating characteristic analysis was performed to assess the diagnostic performance of texture analysis and characteristics of CT images.

Results: Sixty texture features were obtained by MaZda. Of these, four texture features were selected by least absolute shrinkage and selection operator. Following this, three texture features and nine CT characteristics were excluded by logistic regression analysis. Finally, "S(5, -5)SumAverg" (texture feature) and "Size" (CT characteristic) were selected for the receiver operating characteristic analysis. The AUC of "S(5, -5)SumAverg" and "Size" were to be 0.704 and 0.821, respectively, with no significance between them (p = 0.3064).

Conclusion: Two-dimensional texture analysis is a quantitative method for differential diagnosis of PL from PA. The diagnostic performance of both texture analysis and CT characteristics was similar.