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Pancreatic neuroendocrine tumors: Correlation between the contrast-enhanced computed tomography features and the pathological tumor grade

医学 病态的 神经内分泌肿瘤 霍恩斯菲尔德秤 放射科 胰腺肿瘤 转移 病理 核医学 胰腺癌 癌症 计算机断层摄影术 内科学
作者
Koji Takumi,Yoshihiko Fukukura,Michiyo Higashi,Junnichi Ideue,Tomokazu Umanodan,Hiroto Hakamada,Ichiro Kanetsuki,Takashi Yoshiura
出处
期刊:European Journal of Radiology [Elsevier]
卷期号:84 (8): 1436-1443 被引量:89
标识
DOI:10.1016/j.ejrad.2015.05.005
摘要

To determine whether CT features can predict the pathological tumor grades of pancreatic neuroendocrine tumors (PanNETs) according to the recent WHO classification.In all, 28 patients with histologically confirmed PanNETs underwent preoperative contrast CT examinations. Thirteen tumors were classified as G1 and 15 as G2. Two radiologists independently evaluated the CT features (tumor delineation, peripancreatic vascular involvement, upstream pancreatic duct dilatation, N (regional lymph node metastasis) and M (distant metastasis) grades, tumor homogeneity, cystic or necrotic change, and tumor conspicuity). The tumor sizes and Hounsfield unit values of all PanNETs during each phase on CT were measured by one radiologist. We compared the CT features between pathological tumor grades using Fisher's exact test for nominal scales and Mann-Whitney U test for ordinal scales or continuous variables. Additionally, we evaluated the performances of the CT findings and their combinations to diagnose G2 tumors.G2 tumors showed significantly larger in tumor size than G1 tumors (p=0.029). All 4 tumors with hepatic metastases were G2. Non-hyperattenuation compared with pancreatic parenchyma during portal venous phase (PVP) was significantly associated with G2 (p=0.016). The accuracy for G2 diagnosis of tumor size (≥20mm), M grade (M1), and tumor conspicuity (non-hyperattenuation during PVP) were 71%, 61%, and 71%, respectively, while the accuracy of their combination was 82%.Contrast-enhanced CT features (tumor size, M grade, and tumor conspicuity during PVP) can predict the pathological tumor grades of PanNETs.

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