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Updated: Dec 27, 2025

High Resolution 3D Imaging of the Human Pancreas Neuro-insular Network
Published on: January 29, 2018
Pancreatic Neuroendocrine Neoplasms: CT Spectral Imaging in Grading
Wei-Xia Li1, Fei Miao1, Xue-Qin Xu1
1Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Rationale And Objectives:
The purpose of this study was to define the CT spectral imaging characteristics of pancreatic neuroendocrine neoplasms (PNENs) and evaluate their potential for differential diagnosis of nonlow grade (non-LG) PNENs from low grade (LG) PNENs.
Materials And Methods:
CT spectral imaging data of 54 pathologically proven PNENs were retrospectively reviewed. Patients were divided into two groups: 40 cases with grade 1 in LG PNENs group and 14 cases with grade 2 and grade 3 in non-LG PNENs group.
Results:
Gender, calcification, inhomogeneity, invasiveness, PD dilatation, lymph node enlargement, size, normalized iodine (water) concentration in arterial phase (AP) (Iodine (ap)), normalized effective-Z (Zap), slope of normalized CT spectral curves in both AP, and portal venous phase were found to be significant variables for differentiating non-LG PNENs from LG PNENs (p < 0.05). Non-LG PNENs had larger size and lower Zap and Iodine (ap) than LG PNENs. The tumor size, Zap and Iodine (ap) had fair to good diagnostic performance with the area under receiver-operating-characteristic curve (AUC) 0.843, 0.733, and 0.728, respectively. Multivariate analysis with logistic regression had higher AUC (p<0.05) than all the single parameters except for size.
Conclusion:
There were significant differences in CT spectral imaging parameters between non-LG and LG PNENs. Tumor size was the most promising independent parameter and the combination of quantitative parameters with qualitative parameters is the best predictor in differentiating of non-LG PNENs from LG PNENs. CT spectral imaging can help determine the malignancy of PNENs, which can better assist in surgical planning.

