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作 者:黄立萍 张勇 徐朱烽 郭坤 HUANG Li-ping;ZHANG Yong;XU Zhu-feng;GUO Kun(Department of Radiology,Nanjing Lishui People's Hospital,Nanjing 211200,Jiangsu Province,China)
机构地区:[1]南京市溧水区人民医院影像科,江苏南京211200
出 处:《中国CT和MRI杂志》2022年第4期59-61,共3页Chinese Journal of CT and MRI
摘 要:目的 分析周围型肺癌与肺内炎性肿块患者影像学特点及CT诊断鉴别价值。方法 选择2015年1月至2018年12月期间我院收治的40例周围型肺癌患者,另选择40例肺内炎性肿块患者进行回顾性分析,患者均有明确手术病理佐证及完整胸部CT影像学资料,对比两种不同病症的CT影像学差异。结果 周围型肺癌患者CT影像密度均匀、边缘清晰,可见“分叶”、“毛刺”征及胸膜“凹陷”征、“空泡”征,而肺内炎性肿块患者CT影像病灶内密度多不均匀,可见钙化及多发空洞、边缘模糊,二者比较差异有统计学意义(P<0.05);以病变形态分类为标准,对肺内炎性肿块诊断的敏感度、特异度和准确度分别为72.50%(29/40)、65.00%(26/40)、68.75%(55/80);以病变形态分类为基础,结合征象及病史进行修正后对肺内炎性肿块诊断的敏感度、特异度和准确度分别为85.00%(34/40)、77.50%(31/40)、81.25%(65/80)。结论 从CT检查所反映的病灶形态、大小、密度、边缘及周围肺部改变等影像学特点和临床病史等方面全面综合分析,或可更好地区分这周围型肺癌与肺内炎性肿块,指导临床诊疗方案的合理制定。Objective To analyze the imaging features and differential diagnosis value of CT in patients with peripheral lung cancer and lung inflammatory masses. Methods During the period from January 2015 to December 2018, 40 patients with peripheral lung cancer who were admitted to the hospital were enrolled. Another 40 patients with lung inflammatory masses were enrolled for retrospective analysis. All could be clearly confirmed by surgical pathology, and there were complete chest CT imaging data in them. CT imaging differences between two different symptoms were compared. Results CT imaging features in patients with peripheral lung cancer mainly included even density, clear edges, "lobulation" sign, "burr" sign, "pleural depression" sign and "vocule" sign. CT imaging features in patients with lung inflammatory masses in the lesions is uneven, with calcification, multiple cavities and blurred edges. The differences between the two were statistically significant(P<0.05). Taking the classifications of lesion morphology, sensitivity, specificity and accuracy for the diagnosis of lung inflammatory masses were 72.50%(29/40), 65.00%(26/40), and 68.75%(55/80), respectively. Based on classifications of lesion morphology, after correction according to signs and medical history, sensitivity, specificity and accuracy for the diagnosis of lung inflammatory masses were 85.00%(34/40), 77.50%(31/40) and 81.25%(65/80), respectively. Conclusion The comprehensive comprehensive analysis on imaging features and clinical medical history such as lesions morphology, size, density, marginal and peripheral lung changes reflected by CT examination may better distinguish the peripheral lung cancer from lung inflammatory masses, and guide the reasonable formulation of clinical diagnosis and treatment plans.
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