Background: Primary hepatic neuroendocrine carcinomas (PHNECs) are rare and asymptomatic, and are therefore difficult to distinguish radiologically from other liver carcinomas. In this study, we aimed to determine the computed tomography (CT), magnetic resonance imaging (MRI), and digital subtraction angiography (DSA) features of PHNECs. Methods: A retrospective analysis of 11 patients with pathologically proven PHNECs was performed from January 2009 to September 2014. The CT, MRI, and DSA image features were analysed. Results: Ten of the eleven patients exhibited two or more lesions, and one patient exhibited a single lesion. Abdominal CT of 8 cases revealed multiple round or oval-shaped masses with well-defined borders, which were heterogeneous and hypodense on precontrast CT images. Significant diffuse heterogeneous enhancement was observed during the arterial phase in 8 cases, and the enhancement was slightly higher than the attenuation of the surrounding normal liver parenchyma and indistinct edges of small lesions during the portal phase. Well circumscribed (11 cases), lobulated (5 cases) or multiple nodular masses (4 cases), nodule (1 case) and irregular masses (1 case) of high signal intensity were observed on T2WI and DWI of MR images. The masses were well circumscribed, heterogeneous, and hypointense on T1WI, with significant enhancement of the solid carcinoma portion in the early arterial phase and continued enhancement in the portal venous phase. Characteristic lobulated or multiple nodular masses were observed in MRI. DSA showed multiple hypervascular carcinoma-staining lesions with sharp edges in the arterial phase. Conclusion: The CT, MRI, and DSA images of PHNECs exhibit specific characteristic features. Appropriate combinations of the available imaging modalities could therefore optimize the evaluation of patients with PHNECs.
CITATION STYLE
Yang, K., Cheng, Y. S., Yang, J. J., Jiang, X., & Guo, J. X. (2017). Primary hepatic neuroendocrine tumors: Multi-modal imaging features with pathological correlations. Cancer Imaging, 17(1). https://doi.org/10.1186/s40644-017-0120-x
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