ArticleLa Radiologia medica2017
Can MDCT or EUS features predict the histopathological grading scheme of pancreatic neuroendocrine neoplasms?
Article in La Radiologia medica, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors.BMC medical imaging · 2025Article
- Article
- Diagnostic imaging of gastrointestinal neuroendocrine tumours (GI-NETs): relationship between MDCT features and 2010 WHO classification.La Radiologia medica · 2019Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo identify whether the features of preoperative MDCT or EUS could predict the histopathological grading scheme of pancreatic neuroendocrine neoplasms (pNENs).
methodsA total of 25 patients with pNENs were enrolled in the present study. The qualitative and quantitative variables were reviewed. The qualitative variables included location, contour, border, necrosis, intratumoral vessel, homogeneity, calcification, peripancreatic fat/vessel infiltration, pancreatic duct dilatation, mass within pancreas, lymphadenopathy and hepatic metastasis on MDCT and border, echogenicity, cystic/solid and blood flow on EUS. The quantitative variables included long diameter (LD), short diameter (SD), unenhanced mass attenuation (UMA), unenhanced pancreatic attenuation (UPA), arterial phase mass attenuation (APMA), arterial phase pancreatic attenuation (APPA), portal venous phase mass attenuation (PVPMA), portal venous phase pancreatic attenuation (PVPPA), arterial phase enhancement degree (APED) and portal venous phase enhancement degree (PVPED). In addition, sex and age were also evaluated. Histopathological classifications met the criterion of 2010 edition WHO Histopathological Classifications. Kruskal-Wallis test and Boruta algorithm were conducted.
resultsLymphadenopathy and peripancreatic fat or vascular invasion foretold higher histopathological grading level while well-defined border on EUS image lower grading level.
conclusionsLymphadenopathy, border on EUS image and peripancreatic fat or vascular invasion can predict the histopathological grading scheme of pNENs.
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