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腮腺多形性腺瘤与腺淋巴瘤的CT影像特征及对比分析 被引量:5

CT Features and Contrastive Analysis of Pleomorphic Adenoma and Adenolymphoma of the Parotid Gland
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摘要 目的探究腮腺多形性腺瘤与腺淋巴瘤的CT影像特征及对比分析。方法选取我院2015年9月-2018年8月收治治疗的腮腺多形腺瘤和腺淋巴瘤患者各20例作为研究对象,其中腮腺淋巴瘤共25个病灶,腮腺多形性腮腺瘤共21个病灶,所有患者都完成了CT平扫以及增强扫描。分析比较患者的CT影像资料及病理。结果腮腺多形性腺瘤与腺淋巴瘤的生长轴线、发病部位、平扫及增强扫描CT值、肿瘤内低密度、肿瘤内或附近血管影等均存在统计学差异(P<0.05);在肿瘤大小、形态、左右叶分布方面等差异并不明显(P>0.05)。结论在通过CT影像扫描后可有效鉴别腮腺多形性腺瘤以及腺淋巴瘤,可清楚显示腮腺多形性腺瘤与腺淋巴瘤的部位、数目、周围结构及形态情况。 Objective To explore the CT features and comparative analysis of the polymorphous adenoma of the parotid gland and adenolymphoma. Methods A total of 20 cases of parotid adenomas and adenolymphoma treated in our hospital from September 2015 to August 2018 were selected as study objects, including 25 lesions of parotid gland lymphoma and 21 lesions of parotid gland polymorphous parotid adenoma. All the patients completed CT plain scan and enhanced scan. The CT image data and pathology of the patients were analyzed and compared. Results The growth axis, pathogenesis, CT value of plain scan and enhanced scan, low density in the tumor, and vascular shadow in or near the tumor were all statistically significant(P<0.05). Conclusion It is effective to identify the polymorphous adenoma and adenolymphoma of the parotid gland after CT image scanning, and it can clearly show the location, number,surrounding structure and morphology of the polymorphous adenoma and adenolymphoma of the parotid gland.
作者 郭作梁 陈晓华 马兴灿 马树华 Zuoliang GUO;Xiaohua CHEN;Xingcan MA;Shuhua MA(Department of Radiology,Chaonan Minsheng Hospital,Shantou 515144,China;Department of Radiology,Chaonan Minsheng Hospital,Shantou University,Department of Radiology,First Affiliated Hospital,Shantou University Medical College,Guangdong Provincial Key Laboratory of Medical Molecular Imaging,Shantou University Medical College,Shantou 515041,China Corresponding author:Shuhua MA)
出处 《心电图杂志(电子版)》 2019年第1期22-23,共2页 Journal of Electrocardiogram(Electronic Edition)
关键词 腮腺 多形性腺瘤 腺淋巴瘤 CT影像 分析 Parotid gland Pleomorphic adenoma Glands lymph node CT images Analysis
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