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腮腺良恶性肿瘤的CT影像学表现及鉴别价值研究 被引量:27

Study on the CT Imaging Findings and Differential Value of Benign and Malignant Parotid Tumors
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摘要 目的分析腮腺良恶性肿瘤的CT影像学表现,总结CT在是腮腺良恶性肿瘤鉴别诊断中的应用价值。方法回顾性分析2013年1月~2015年1月在我院经病理证实为腮腺原发性良性肿瘤的51例患者及45例腮腺恶性肿瘤患者的临床资料,分析其CT影像学特征,96例患者均作CT平扫与增强扫描,影像学资料完整,并作统计学处理,分析CT在鉴别良恶性腮腺肿瘤中的应用价值。结果本组96例患者,良性肿瘤51例,病灶共59个,恶性肿瘤45例,共计45个病灶;良性肿瘤患者部位、形态、密度、边界、囊变、淋巴结肿大及强化程度与恶性肿瘤患者对比差异有统计学意义(P<0.05)。结论恶性肿瘤形态多不规则,边界不清晰,多呈浸润性生长表现,增强扫描后,有显著强化特点,有非规则坏死囊变表现,可见颈部淋巴结肿大,反之则多认定为良性病变。 Objective To analyze the CT imaging findings of benign and malignant parotid tumors and to summarize the application value of CT in differential diagnosis of benign and malignant parotid tumors. Methods The clinical datum of 51 patients with primary benign parotid tumors and 45 patients with malignant parotid tumors pathologically confirmed in the hospital from January 2013 to January 2015 were retrospectively analyzed and the CT imaging characteristics were also analyzed. The 96 patients were given nonenhanced CT and enhanced scanning. The imaging datum were integrated and were statistically analyzed. The the application value of CT in differential diagnosis of benign and malignant parotid tumors was analyzed. Results Among 96 patients in the group, there were 51 cases of benign tumor with a total of 59 lesions and 45 cases of malignant tumors with a total of 45 lesions; The differences in location, shape, density, boundary, cystic degeneration, lymph node enlargement and strengthening degree between the patients with benign tumor and with malignant tumors were statistically significant(P0.05). Conclusion Most of the shape of malignant tumors are irregular and the boundary is not clear, performing as infiltrative growth. After enhanced scan, the tumors were with significantly enhanced features and irregular cystic necrosis performance, showing cervical lymph nodes enlargement and conversely, they are identified as benign lesions.
出处 《中国CT和MRI杂志》 2017年第1期5-7,19,共4页 Chinese Journal of CT and MRI
关键词 腮腺肿瘤 CT 良恶性 鉴别 特点 Parotid Tumor CT Benign and Malignant Identification Characteristics
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