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不同病理级别膀胱神经内分泌肿瘤CT表现
引用本文:谌丹丹,江新青,杨蕊梦,刘国顺,魏新华.不同病理级别膀胱神经内分泌肿瘤CT表现[J].中国医学影像技术,2020,36(8):1207-1210.
作者姓名:谌丹丹  江新青  杨蕊梦  刘国顺  魏新华
作者单位:广州市第一人民医院放射科, 广东 广州 510180
基金项目:广州市卫生健康科技项目(20191A011003)。
摘    要:目的 观察不同病理级别膀胱神经内分泌肿瘤(NET)的CT表现。方法 回顾性分析经手术病理证实的17例膀胱NET患者的临床、病理及CT资料,参照2010年WHO消化道NET分级标准对其进行分级并分为低级别组(G1和G2级)和高级别组(G3级),比较组间临床及CT表现差异。结果 17例膀胱NET中,G1级6例,G2级2例,G3级9例;低级别组8例,高级别组9例;组间性别及年龄(t=-3.43,P=0.03、0.04),肿瘤最大径、囊变坏死、周围侵犯及转移差异均有统计学意义(P均<0.05)。低级别组动脉期肿瘤绝对强化程度(58.62±12.45)HU]高于高级别组(31.88±8.86)HU,t=5.15,P<0.01]。结论 不同病理级别膀胱NET的CT表现有一定特征性,结合临床有助于诊断。

关 键 词:膀胱肿瘤  诊断  体层摄影术  X线计算机  病理学
收稿时间:2019/7/17 0:00:00
修稿时间:2020/3/6 0:00:00

CT manifestations of bladder neuroendocrine tumors with different pathological grades
CHEN Dandan,JIANG Xinqing,YANG Ruimeng,LIU Guoshun,WEI Xinhua.CT manifestations of bladder neuroendocrine tumors with different pathological grades[J].Chinese Journal of Medical Imaging Technology,2020,36(8):1207-1210.
Authors:CHEN Dandan  JIANG Xinqing  YANG Ruimeng  LIU Guoshun  WEI Xinhua
Institution:Department of Radiology, Guangzhou First People''s Hospital, Guangzhou 510180, China
Abstract:Objective To observe CT manifestations of bladder neuroendocrine tumors (NET) with different pathological grades. Methods Clinical, pathological and CT data of 17 patients with bladder NET confirmed with pathology were retrospectively analyzed. According to the WHO 2010 pathological classification standard, all tumors were classified and then divided into low-grade group (G1 and G2) and high-grade group (G3). The differences of clinical and CT findings were compared between 2 groups. Results Among 17 cases of bladder NET, 6 were G1, 2 were G2 and 9 were G3 tumors. There were 8 cases in low-grade group and 9 cases in high-grade group, respectively. Statistically differences of patients gender and ages (t=-3.43) (P=0.03, 0.04), also of the maximum tumor size, cystic change or necrosis, peripheral invasion and metastasis were found between 2 groups (all P<0.05). The arterial absolute enhancement degree of tumors in low-grade group (58.62±12.45]HU) was higher than that in high-grade group (31.88±8.86]HU) (t=5.15, P<0.01). Conclusion CT manifestations of bladder NET with different pathological grades had certain characteristics, being helpful to diagnosis combined with clinical data.
Keywords:urinary bladder neoplasms  diagnosis  tomography  X-ray computed  pathology
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