Preoperative evaluating early recurrence in resectable pancreatic ductal adenocarcinoma by using CT radiomics.

OBJECTIVE: To investigate the feasibility of a radiomics model based on contrast-enhanced CT for preoperatively predicting early recurrence after curative resection in patients with resectable pancreatic ductal adenocarcinoma (PDAC). METHODS: One hundred and eighty-six patients with resectable PDAC who underwent curative resection were included and allocated to training set (131 patients) and validation set (55 patients). Radiomics features were extracted from arterial phase and portal venous phase images. The Mann-Whitney U test and least absolute shrinkage and selection operator (LASSO) regression were used for feature selection and radiomics signature construction. The radiomics model based on radiomics signature and clinical features was developed by the multivariate logistic regression analysis. Performance of the radiomics model was investigated by the area under the receiver operating characteristic (ROC) curve. RESULTS: The radiomics signature, consisting of three arterial phase and three venous phase features, showed optimal prediction performance for early recurrence in both training (AUC = 0.73) and validation sets (AUC = 0.66). Multivariate logistic analysis identified the radiomics signature (OR, 2.58; 95% CI 2.36-3.17; p = 0.002) and clinical stage (OR, 1.60; 95% CI 1.15-2.30; p = 0.007) as independent predictors. The AUC values for risk evaluation of early recurrence using the radiomics model incorporating clinical stage were 0.80 (training set) and 0.75 (validation set). CONCLUSION: The radiomics-based model integrating with clinical stage can predict early recurrence after upfront surgery in patients with resectable PDAC.

CoFe Nanoparticle-Decorated Reduced Graphene Oxide for the Highly Efficient Reduction of 4-Nitrophenol.

High-performance, nonprecious metal catalysts with special morphologies and easy-to-recycle properties are essential for the treatment of environmental pollutants. Herein, CoFe nanoparticle-decorated reduced graphene oxide (RGO) catalysts were designed and successfully fabricated, and the catalyst was then used to reduce 4-nitrophenol into 4-aminophenol. Outstanding catalytic properties with a reduction rate constant of 4.613 min-1 were achieved due to the synergistic properties of the CoFe metal alloy and the high-conductivity RGO components in the catalysts. In addition, the catalyst was conveniently recovered via magnets due to its inherent magnetic properties. The facile preparation, outstanding catalytic performance, structural stability, and low material costs make the CoFe/RGO nanocatalyst a promising candidate for potential applications in catalysis.

Impacts of lung and tumor volumes on lung dosimetry for nonsmall cell lung cancer.

The purpose of this study was to determine the impacts of lung and tumor volumes on normal lung dosimetry in three-dimensional conformal radiotherapy (3DCRT), step-and-shoot intensity-modulated radiotherapy (ssIMRT), and single full-arc volumetric-modulated arc therapy (VMAT) in treatment of nonsmall cell lung cancers (NSCLC). All plans were designed to deliver a total dose of 66 Gy in 33 fractions to PTV for the 32 NSCLC patients with various total (bilateral) lung volumes, planning target volumes (PTVs), and PTV locations. The ratio of the lung volume (total lung volume excluding the PTV volume) to the PTV volume (LTR) was evaluated to represent the impacts in three steps. (a) The least squares method was used to fit mean lung doses (MLDs) to PTVs or LTRs with power-law function in the population cohort (N = 32). (b) The population cohort was divided into three groups by LTRs based on first step and then by PTVs, respectively. The MLDs were compared among the three techniques in each LTR group (LG) and each PTV group (PG). (c) The power-law correlation was tested by using the adaptive radiation therapy (ART) planning data of individual patients in the individual cohort (N = 4). Different curves of power-law function with high R2 values were observed between averaged LTRs and averaged MLDs for 3DCRT, ssIMRT, and VMAT, respectively. In the individual cohort, high R2 values of fitting curves were also observed in individual patients in ART, although the trend was highly patient-specific. There was a more obvious correlation between LTR and MLD than that between PTV and MLD.