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Pancreatic Neuroendocrine Neoplasms: Clinical Value of Diffusion-Weighted Imaging
Riccardo De Robertis1, Mirko D'Onofrio, Giulia Zamboni
1Department of Radiology, Casa di cura Pederzoli, Peschiera del Garda, Italy.
Background/Aims:
Diffusion-weighted imaging (DWI) can depict random motions of water molecules in biological tissues during magnetic resonance (MR) examinations. Few papers have tested its application to pancreatic neuroendocrine neoplasms (PanNENs). The aim of this paper is to assess the clinical value of DWI regarding the identification and characterization of PanNENs and diagnosis of liver metastases.
Methods:
Preoperative MR examinations of 30 PanNEN patients were retrospectively reviewed; 30 patients with pathologically proven pancreatic ductal adenocarcinoma (PDAC) were included to compare the imaging features. Qualitative and quantitative MR features were compared between histotypes. A blinded-reader comparison of diagnostic confidence for PanNENs and liver metastases was conducted on randomized image sets. All results were compared with pathological data.
Results:
PanNEN conspicuity was higher on DW images compared to conventional MR sequences. DWI had higher detection rates for PanNENs than had conventional sequences (93.3 vs. 71.1%). Sharp margins and absence of main pancreatic duct/common bile duct dilation and chronic pancreatitis were more common among PanNENs as compared to PDACs. Arterial iso- or hyperenhancement and portal hyperenhancement were more frequent within PanNENs as compared to PDACs. No differences between histotypes were found for quantitative features. Arterial-phase images had the highest interobserver agreement for the diagnosis of PanNEN (Cohen's κ = 0.667). DWI provided the highest detection rate for liver metastases as well as excellent interobserver agreement for the diagnosis of liver metastases (κ = 0.932), with good accuracy (AUC = 0.879-0.869).
Conclusion:
DWI has clinical value regarding the identification of PanNENs and the diagnosis of liver metastases, while conventional MR sequences are fundamental for their characterization.

