目的:分析囊腔类肺癌的CT征象与病理学基础,加深对此类病变的认识,以提高诊断准确率。方法:回顾性分析经手术病理证实的18例囊腔类肺癌的MSCT征象并与病理对照。结果:18例均为单发病灶,周围型肺癌,腺癌17例,鳞癌1例。CT共同征象:肺癌病灶中有囊腔,囊壁厚薄不均,不光滑。5例主要表现为囊腔;2例表现囊腔伴周围磨玻璃密度;3例呈囊腔与磨玻璃、实性密度混合;8例见囊腔伴周围实性密度。囊腔内壁结节、分隔、血管穿行分别占61.1%、66.7%、11.1%;囊壁外缘分叶征、毛刺征分别占50%、55.6%,血管集束征、胸膜凹陷征分别占38.9%、50%。动态随访1例磨玻璃结节内出现囊腔;1例囊腔逐渐增大,囊壁不规则增厚;3例囊腔缩小并实性成分增多;1例囊腔与磨玻璃、实性密度混合演变为囊腔与实性密度混合。结论:囊腔类肺癌的CT表现有一定的特征性,囊腔形态及周围表现、动态随访综合分析有助于诊断。
Abstract
Objective: To evaluate Multi-slice computed tomography features and pathological basis of lung cancer associated with cystic airspaces, and to improve understanding of such kind of lesions and to improve diagnostic accuracy. Methods: Eighteen cases surgery pathologically confirmed lung cancer associated with cystic airspaces were retrospectively analyzed with regard to Multi-slice computed tomography features and compared with pathology. Results: There were 18 cases(peripheral lung cancer, 17 adenocarcinoma, 1 squamou carcinoma). Common CT signs: lung cancer with cyst, thin or thick and unsmooth cystic wall. The lesion was predominant cysts in 5 cases, cysts and ground-glass nodule mixed lesions in 2 cases, cysts with ground-glass nodule and solid mixed lesions in 3 cases, cysts and solid mixed lesions in 8 cases. Cysts with mural nodules, septum and blood vessel passing were 61.1%, 66.7% and 11.1% respectively. Lobulation sign and speculation sign were 50% and 55.6% respectively. Vascular convergence sign and pleural indentation sign were 38.9% and 50% respectively. One lesion showed ground-glass opacity in cyst in dynamic follow-up. The cyst cavity gradually increased and cystic wall irregular thicken in one case. Three lesions showed decreased size of the cyst and enlarged nodules. Cyst with ground-glass nodule and solid mixed lesions in one case developed to cyst with solid mixed. Conclusion: The features of lung cancer associated with cystic airspaces have certain characteristics, dynamically follow-up analysis the shape of the cyst cavity and surrounding performance is helpful for diagnosis.
关键词
肺肿瘤;体层摄影术 /
螺旋计算机
Key words
Lung neoplasms /
Tomography, spiral computed
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