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Title: Pancreatic neuroendocrine neoplasms: Magnetic resonance imaging features according to grade and stage. Author: De Robertis R, Cingarlini S, Tinazzi Martini P, Ortolani S, Butturini G, Landoni L, Regi P, Girelli R, Capelli P, Gobbo S, Tortora G, Scarpa A, Pederzoli P, D'Onofrio M. Journal: World J Gastroenterol; 2017 Jan 14; 23(2):275-285. PubMed ID: 28127201. Abstract: AIM: To describe magnetic resonance (MR) imaging features of pancreatic neuroendocrine neoplasms (PanNENs) according to their grade and tumor-nodes-metastases stage by comparing them to histopathology and to determine the accuracy of MR imaging features in predicting their biological behavior. METHODS: This study was approved by our institutional review board; requirement for informed patient consent was waived due to the retrospective nature of the study. Preoperative MR examinations of 55 PanNEN patients (29 men, 26 women; mean age of 57.6 years, range 21-83 years) performed between June 2013 and December 2015 were reviewed. Qualitative and quantitative features were compared between tumor grades and stages determined by histopathological analysis. RESULTS: Ill defined margins were more common in G2-3 and stage III-IV PanNENs than in G1 and low-stage tumors (P < 0.001); this feature had high specificity in the identification of G2-3 and stage III-IV tumors (90.3% and 96%, 95%CI: 73.1-97.5 and 77.7-99.8). The mean apparent diffusion coefficient value was significantly lower in G2-3 and stage III-IV lesions compared to well differentiated and low-stage tumors (1.09 × 10-3 mm2/s vs 1.45 × 10-3 mm2/s and 1.10 × 10-3 mm2/s vs 1.53 × 10-3 mm2/s, P = 0.003 and 0.001). Receiving operator characteristic analysis determined optimal cut-offs of 1.21 and 1.28 × 10-3 mm2/s for the identification of G2-3 and stage III-IV tumors, with sensitivity and specificity values of 70.8/80.7% and 64.5/64% (95%CI: 48.7-86.6/60-92.7 and 45.4-80.2/42.6-81.3). CONCLUSION: MR features of PanNENs vary according to their grade of differentiation and their stage at diagnosis and could predict the biological behavior of these tumors.[Abstract] [Full Text] [Related] [New Search]