肝脏原发性神经内分泌肿瘤的MRI表现及其病理学基础分析

目的探讨不同级别的原发肝脏神经内分泌肿瘤(primary hepatic neuroendocrine tumors,PHNETs)MRI表现及其相应的病理学基础。材料与方法回顾性分析6例PHNETs的MRI及病理学资料,分析不同级别PHNETs的MRI表现及相关病理学基础。结果 G1级1例,MRI表现为单发结节,T1WI呈稍低信号、T2WI呈稍高信号,信号均匀,动脉期明显均匀强化,门脉期及延迟期强化程度有所减低,其病理表现为瘤细胞呈小梁状排列,周围血窦丰富。G2级3例,其中1例为多发,T1WI表现为不均匀稍低信号、T2WI表现为不均匀稍高信号,所有病灶内均可见类圆形T2WI高信号,3个病灶内可见出血信号,动脉期不均匀明显强化,门脉期及延迟期强化程度减低,但持续强化,且部分病灶强化范围有扩大趋势;镜下瘤细胞呈缎带样排列,瘤周血窦丰富,且周围伴随纤维化,3个病灶窦腔内见出血。G3级2例,均多发,MRI表现为T1WI、T2WI不均匀信号,肿块体积较大,动脉期不均匀轻度强化,门脉及延迟期呈持续强化,程度减低;肿瘤细胞呈片状浸润性生长,核大、异型性明显、间质血管相对丰富,肿瘤内见多灶性坏死。结论 MRI表现可反映不同级别PHNETs的病理学特征,有助于提高PHNETs术前诊断的准确度。

MRI findings of primary hepatic neuroendocrine tumors:correlation with pathology

Objective: To investigate MR imaging findings of primary hepatic neuroendocrine tumors (PHNETs) and their correlation with the 2010 WHO pathological classification. Materials and Methods: We analyzed MRI imagings of 6 patients who were diagnosed with PHNET and correlated the data with the 2010 WHO classification of neuroendocrine tumors. Results: According to the 2010 WHO classification system, 1 case was defined as G1, 3 cases were defined as G2, and 2 cases were defined as G3. The Grade 1 tumor was singular, solid nodules with prolonged enhancement from the arterial phase to the delayed phase. The lesion showed hypointensity on T1-weighted imaging, mildy high intensity on T2-weighted and homogeneous. The tumor cell arranged in a beam, and blood sinus was abundant. Grade 2 tumors could have a singular or multiple distribution pattern, signal intensities were heterogeneous on T1-and T2-weighted imaging with hemorrhage and necrosis. The tumor showed marked peripheral enhancement in the arterial phase and slight hyper-intensity relatived to the surrounding liver parenchyma in the delayed phase. Grade 3 tumors had multiple lesions, internal necrosis or coagulation necrosis, which showed the slight and prolonged enhancement from the arterial phase to the delayed phase. HE staining of the tumor showed tumor cell arranged as solid nests, and blood sinus was mildly abundant. Conclusions: MRI can reflect pathological features of PHNETs, which are helpful in accurately diagnosing PHNETs.