摘要
目的:探讨活动性肺结核薄层CT表现与痰涂片结果的关系。方法:回顾性分析347例活动性肺结核患者薄层CT表现,根据痰涂片结果,将其分成涂阳(n=145)、涂阴(n=202)两组。分别评价其薄层CT表现,包括微结节、结节、肿块、实变、空洞、磨玻璃样影、支气管异常以及病变数量和空洞腔的最大直径。结果:结节、肿块、微结节呈随机分布、小叶中心分布和反晕征、磨玻璃样影、薄壁空洞、均匀的支气管壁增厚伴管腔狭窄、不规则线状影、肺实质束带影、瘢痕周围肺气肿及纵隔淋巴结肿大的发病率,在两组之间差异无统计学意义(P>0.05)。相比之下,微结节呈结节病星系征和结节病丛征,实变、厚壁和虫蚀样空洞以及不均匀的支气管壁增厚伴管腔狭窄的发病率在涂阳者明显增加,差异有统计学意义(x2=4.132,x2=3.228,x2=6.041,x2=1.687;P<0.05)。结论:活动性肺结核薄层CT表现与涂阳性和涂阴性的活动性肺结核有一定程度的相关性。
Objective: To investigate the relationship between thin-section CT findings in active pulmonary tuberculosis and the outcome of sputum smears. Methods: Using reviewed analysis on thin-section CT scans of 347 patients with active pulmonary tuberculosis. The patients were assigned to two groups according to the results of sputum smears as follows: smears-positive (n=145) and smears-negative (n=202). Thin-section CT patterns of micronodules, nodules, masses, consolidation, cavity, ground-glass opacity, bronchial abnormalities, the number of lesions and the maximum diameter of the cavity lumen were assessed by the different sputum smears'results. Results: The frequency of nodules, masses, micronodules in random distribution, centrilobular distribution and reversed halo sign, ground-glass opacity, thin-walled cavities, bronchial wall thickening with smooth stenosis, irregular linear, parenchyma bands, pericicatricial emphysema and mediastinal lymphadenectasis between the two groups were not statistically significant (P〉0.05). In contrast, the frequency of micronodules in sarcoid galaxy sign and sarcoid cluster sign, consolidation, thick-walled and moth-eaten cavities and bronchial wall thickening with irregular stenosis or occlusion increased with smear-positive (x2 = 4. 132, x2 = 3.228, x2 = 6.041, X2 = 1.687 P〈0.05). Conclusion: Thin-section CT findings might be associated with the smear-positive and smear-negative active pulmonary tuberculosis.
出处
《中国医学装备》
2013年第6期44-48,共5页
China Medical Equipment
关键词
结核
肺
活动性
涂阳
涂阴
体层摄影术
X线计算机
薄层
Tuberculosis
pulmonary
active
Smear-positive
Smear-negative
Tomography
X-ray computed
Thinsection