CT Features Predict the Optimal Therapeutic Approach for Pancreatic Neuroendocrine Neoplasms

Abstract

Objective. To determine whether MDCT features of pancreatic neuroendocrine tumors can predict the pathological tumor grade. Materials and methods. 30 patients with histologically confirmed pancreatic neuroendocrine tumors (pNET) underwent preoperative contrast CT examinations from 2012 to 2015. 19 tumors were classified as G1 and 11 as G2 according to the WHO 2010 classification. We evaluated several CT-features of pNET, such as tumor contrast enhancement pattern, homogeneity, cystic or necrotic change, size, vascular involvement, upstream pancreatic duct dilatation, presence of regional and distant metastasis. Tumor density was measured at all phases. CT-features were compared between tumor grades using Mann-Whitney U-test and f-Fisher test. We evaluated the performances of the CT findings to diagnose G2 tumors. Results. Mean tumor size was significantly higher (p < 0.05) in grade 2 pNET. G2 pNET were more often nonhomogenous and had poorly defined margin. Tumor density was significantly higher in the group of grade 1 tumors. Mean arterial enhancement ratio in G1 pNET was 1.66 ± 0.42, in G2 pNET - 1.04 ± 0.39 (p < 0.01). Mean portal enhancement ratio in G1 pNET was 1.28 ± 0.25, in G2 pNET - 0.9 ± 0.1 (p < 0.05). Arterial enhancement ratio <1.1, tumor size > 20 mm, ill-defined borders and non-homogenous contrast enhancement showed 83%, 74%, 67% and 63% accuracy in differentiating Grade 2 pNET from Grade 1 pNET. Conclusion. Several CT-features of pNET, such as tumor contrast enhancement, homogeneity and size can predict the tumor grade.