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find Keyword "pancreatic neuroendocrine tumor" 3 results
  • The texture analysis of CT images used for the discrimination of nonhypervascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas

    Objective To determine feasibility of texture analysis of CT images for the discrimination of nonhypervascular pancreatic neuroendocrine tumor (PNET) from pancreatic ductal adenocarcinoma (PDAC). Methods CT images of 15 pathologically proved as PNETs and 30 PDACs in West China Hospital of Sichuan University from January 2009 to January 2017 were retrospectively analyzed. Results Thirty best texture parameters were automatically selected by the combination of Fisher coefficient (Fisher)+classification error probability combined with average correlation coefficients (PA)+mutual information (MI). The 30 texture parameters of arterial phase (AP) CT images were distributed in co-occurrence matrix (18 parameters), run-length matrix (10 parameters), and autoregressive model (2 parameters). The distribution of parameters in portal venous phase (PVP) were co-occurrence matrix (15 parameters), run-length matrix (10 parameters), histogram (1 parameter), absolute gradient (1 parameter), and autoregressive model (3 parameters). In AP and PVP, the parameter with the highest diagnostic performance were both Teta2, and the area under curve (AUC) value was 0.829 and 0.740 (P<0.001,P=0.009), respectively. By the B11 of MaZda, the misclassification rate of raw data analysis (RDA)/K nearest neighbor classification (KNN), principal component analysis (PCA)/KNN, linear discriminant analysis (LDA)/KNN, and nonlinear discriminant analysis (NDA)/artificial neural network (ANN) was 28.89% (13/45), 28.89% (13/45), 0 (0/45), and 4.44% (2/45), respectively. In PVP, the misclassification rate of RDA/KNN, PCA/KNN, LDA/KNN, and NDA/ANN was 35.56% (16/45), 33.33% (15/45), 4.44% (2/45), and 11.11% (5/45), respectively. Conclusions CT texture analysis is feasible in the discrimination of nonhypervascular PNET and PDAC. Teta2 is the parameter with the highest diagnostic performance, and in AP, LDA/KNN modality has the lowest misclassification rate.

    Release date:2018-06-15 10:49 Export PDF Favorites Scan
  • Mapping knowledge domains analysis of pancreatic neuroendocrine neoplasm research based on CiteSpace

    ObjectiveTo investigate current status and hot issues of pancreatic neuroendocrine neoplasm (pNEN) imaging research.MethodsThe literatures focusing on pNEN and published from 1998 to 2018 were retrieved from the core database of Web of Science. The quantitative analysis of literatures was then conducted by using the CiteSpace software based on the bibliometrics method. The research trend was then summarized systematically and the potential research fronts and focuses were explored.ResultsA total of 190 articles in the field of pNEN imaging research were retrieved, and the top three countries in the literatures were the United States, Germany, and Italy. The clustering of co-citation of pNEN included the endoscopic ultrasound, current diagnosis, prospective evaluation, cystic pancreatic neuroendocrine tumor, hypervascular neuroendocrine tumor, nonfunctioning pancreatic neuroendocrine tumor, intravoxel incoherent motion, and metastastic lesion. The hot of keywords in the field of pNEN included the fine needle aspiration, CT, diagnosis, pancreas, cancer, neuroendocrine tumor, neoplasm, carcinoma, and management. The hot keywords clustering had the neuroendocrine tumor, pancreatic mass size, non-hyperfunctioning neuroendocrine tumor, CT appearance, metastatic lesion, ancillary studies, somatostatin analogues, somatostatinoma, intraoperative ultrasound, and multiple endcorine neoplasia 1.ConclusionAccurate imaging diagnosis of pNEN is still a hot issue in this field.

    Release date:2019-01-16 10:05 Export PDF Favorites Scan
  • Laparoscopic hepatic vein deprivation

    ObjectiveTo investigate the value of laparoscopic liver venous deprivation (LLVD) in promoting the growth of contralateral future liver remnant (FLR) during two-step hepatectomy. MethodThe clinicopathologic data of a 45-year-old female patient with pancreatic neuroendocrine tumor with multiple liver metastases (grade G2) treated by two-step hepatectomy based on LLVD in January 2022 in the Sichuan Provincial People’s Hospital were analyzed retrospectively. ResultsThe liver function returned to normal within 10 d after LLVD, and the relative increase ratio of FLR reached to 98.35% on postoperative day 10. The laparoscopic right hemi-hepatectomy and distal pancreatectomy plus splenectomy was performed without any postoperative complications, and the patient was discharged from hospital on postoperative day 8. No tumor recurrence or metastasis occurred during the follow-up period. ConclusionsFrom the analysis results of this case, the LLVD could promote the growth of FLR safely and effectively. LLVD provides an alternative surgical method of two-step hepatectomy for treatment of benign and malignant liver tumors.

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