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目的探讨周围型小肺癌的特征性CT表现及其形成的病理基础,并对个别误诊病例进行重点分析。方法对2013年3月至2015年6月50例经穿刺或手术病理证实的周围型小肺癌患者的CT影像学资料进行回顾性分析,总结其较具有特征性的CT表现。结果 50例周围型小肺癌全部为单发,右肺31例,左肺19例。46例首次诊断为肺癌或高度怀疑肺癌,4例误诊为结核,其中1例酷似结核并伴有肺内弥漫分布的粟粒样结节影,回顾分析发现此例临床癌性指标极高,1例误诊为良性结节。50例中47例CT表现为密度不均的圆形、椭圆形、不规则形结节影,1例表现为单发薄壁空腔影,1例表现为多个小结节堆积影,1例表现为密度欠均匀的小结节影;42例边缘见毛刺征,37例周围见血管集束征,分叶征32例,内见空洞并壁内结节者4例,含有空泡征者4例,胸膜凹陷征28例。结论周围型小肺癌具有一定的特征,如分叶征、空泡征、毛刺征、血管集束征及强化差值等,有利于周围型肺癌的诊断及鉴别诊断;同时因其表现亦具有一定的多样性,要结合临床综合分析,减少误诊及漏诊。
Objective To investigate the characteristic CT findings of peripheral small lung cancer and its pathological basis, and to analyze the cases of individual misdiagnosis. Methods From March 2013 to June 2015, 50 cases of peripheral small lung carcinoma confirmed by puncture or pathology were retrospectively analyzed and their CT features were compared. Results All the 50 cases of small peripheral lung cancer were single, 31 cases of right lung and 19 cases of left lung. 46 cases of the first diagnosis of lung cancer or highly suspected lung cancer, 4 cases misdiagnosed as tuberculosis, including 1 case resembles tuberculosis and pulmonary distribution of diffuse miliary nodules, retrospective analysis found that this case of clinical cancer indicators are extremely high, 1 case Misdiagnosed as benign nodules. Of the 50 cases, 47 cases showed circular, oval and irregular nodules with uneven density, one case showed single thin-wall cavity shadow, one case showed multiple small nodules buildup, 1 Cases showed a uniform density of small nodules; 42 cases of margin see the spiculation sign, 37 cases seen around the vascular bundles signs, lobulation sign in 32 cases, see hollow and wall nodules in 4 cases, with vacuolar sign 4 cases, 28 cases of pleural indentation. Conclusion Peripheral small lung cancer has some characteristics, such as lobulation, vacuole sign, burr sign, vascular bundles sign and strengthen the difference in favor of the diagnosis and differential diagnosis of peripheral lung cancer; at the same time because of its performance also has a certain Diversity, combined with clinical analysis, to reduce misdiagnosis and missed diagnosis.