Related Experiment Video
Updated: Mar 7, 2026
Utilizing High Resolution Ultrasound to Monitor Tumor Onset and Growth in Genetically Engineered Pancreatic Cancer Models
Published on: April 7, 2018
Can MDCT or EUS features predict the histopathological grading scheme of pancreatic neuroendocrine neoplasms?
Hui Zhu1,2, Lang Ying3, Wei Tang1,2
1Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
Purpose:
To identify whether the features of preoperative MDCT or EUS could predict the histopathological grading scheme of pancreatic neuroendocrine neoplasms (pNENs).
Methods:
A 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.
Results:
Lymphadenopathy and peripancreatic fat or vascular invasion foretold higher histopathological grading level while well-defined border on EUS image lower grading level.
Conclusions:
Lymphadenopathy, border on EUS image and peripancreatic fat or vascular invasion can predict the histopathological grading scheme of pNENs.
