Radiomics model-based algorithm for preoperative prediction of pancreatic ductal adenocarcinoma grade.

Objective: To develop diagnostic radiomic model-based algorithm for pancreatic ductal adenocarcinoma (PDAC) grade prediction.

Methods: Ninety-one patients with histologically confirmed PDAC and preoperative CT were divided into subgroups based on tumor grade. Two histology-blinded radiologists independently segmented lesions for quantitative texture analysis in all contrast enhancement phases.

Computed tomography-based radiomics approach in pancreatic tumors characterization.

Radiomics (or texture analysis) is a new imaging analysis technique that allows calculating the distribution of texture features of pixel and voxel values depend on the type of ROI (3D or 2D), their relationships in the image. Depending on the software, up to several thousand texture elements can be obtained. Radiomics opens up wide opportunities for differential diagnosis and prognosis of pancreatic neoplasias.

Reproducibility of CT texture features of pancreatic neuroendocrine neoplasms.

Purpose: To evaluate the reproducibility of textural features of pancreatic neuroendocrine neoplasms (PNENs), obtained under various CT-scanning conditions.

Methods And Materials: We included 12 patients with PNENs and 2 contrast enhanced CT (CECT): 1) from our center according to standard CT-protocol; 2) from another institution. Two radiologists independently segmented the entire neoplasm volume using a 3D region of interest by LIFEx application on the arterial phase and then copied it to the other phases.

[Use of fludarabin in conjunction with other cytostatics in the treatment of non-Hodgkin lymphoma resistant to standard chemotherapy].

The investigation involved 50 patients (fludarabin+cyclophosphamide+prednisolone (FCP)--30; fludarabin+mitoxanthrone+prednisolone (FMP)--17; fludarabin+cyclophosphamide--3). FMP proved the most effective (60%). Yet, FCP results were clinically significant (29%).