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少发病灶继发性肝癌的CT诊断与鉴别诊断
引用本文:张志宏,孙志强,齐文玉. 少发病灶继发性肝癌的CT诊断与鉴别诊断[J]. 河南医学研究, 2010, 19(2): 205-208. DOI: 10.3969/j.issn.1004-437x2010.02.026
作者姓名:张志宏  孙志强  齐文玉
作者单位:洛阳洛轴医院,放射科,河南,洛阳,471003
摘    要:目的:探讨少发病灶继发性肝癌的CT表现及鉴别要点。方法:对25例少发病灶继发性肝癌的CT资料进行回顾性分析。25例中24例已确定原发肿瘤,其中1例乳腺癌患者肝内病变曾误诊为肝血管瘤,随访证实为继发肝癌。1例未确定原发肿瘤者经肝活检穿刺证实为继发肝癌。结果:25例继发肝癌中,原发灶来源于消化系统肿瘤较多(52%)。多数为圆形或类圆形病灶,边缘清晰,病灶直径<3cm居多。平扫绝大多数为低密度灶,增强呈边缘性强化,半数以上(16例)表现为"瞳孔"征、"牛眼"征或"圈饼"征等特征性改变。结论:少发病灶继发性肝癌也具有一定的特征性,只要我们密切结合临床病史及实验室检查,动态观察病灶变化,大多可明确诊断。

关 键 词:肝脏  继发肿瘤  少发病灶  X线计算机

Small lesions with secondary liver cancer CT diagnosis and differential diagnosis
ZHANG Zhi-hong,SUN Zhi-qiang,QI Wen-yu. Small lesions with secondary liver cancer CT diagnosis and differential diagnosis[J]. Henan Medical Research, 2010, 19(2): 205-208. DOI: 10.3969/j.issn.1004-437x2010.02.026
Authors:ZHANG Zhi-hong  SUN Zhi-qiang  QI Wen-yu
Abstract:Objective:Purpose:small lesions with secondary liver cancer CT manifestations and differential diagnosis.Methods:Small lesions in 25 patients with secondary liver CT data were analyzed retrospectively.25 cases identified 24 cases of primary tumors,including 1 liver disease patients with breast cancer misdiagnosed hemangiomas follow-up proved to be secondary to liver cancer.One cases of primary tumor were determined by liver needle biopsy confirmed secondary liver cancer.Results:25 cases of secondary liver cancer,primary tumor lesions derived from the digestive system more (52%).Mostly round or lesions,most of the edge of clear lesion diameter <3 cm majority.Plain the vast majority of low-density lesions,marginal increase was stronger,more than half (16 cases) the performance of the "pupil" sign or "bull’s-eye" sign or the "donut" sign and other characteristic changes.Conclusion:Small lesions with secondary liver cancer also have a certain characteristic,as long as we have been closely combined with the clinical history and laboratory examination,the dynamic changes observed lesions,most of them can be clearly diagnosed.
Keywords:liver  secondary tumor  fewer lesions  X-ray computed
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