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在基于人群的肺癌CT筛查中检测到的肺部病变:良性病变的可靠发现。

Pulmonary lesions detected in population-based CT screening for lung cancer: reliable findings of benign lesions.

作者信息

Murakami Tadashi, Yasuhara Yoshifumi, Yoshioka Shinji, Uemura Masahiko, Mochizuki Teruhito, Ikezoe Junpei

机构信息

Department of Radiology, Ehime University School of Medicine, Shitsukawa, Japan.

出版信息

Radiat Med. 2004 Sep-Oct;22(5):287-95.

Abstract

PURPOSE

To identify the characteristics of benign pulmonary lesions in order to reduce false-positive rates in screening computed tomography (CT) and in order to reduce frequency of follow-up high-resolution CT (HRCT).

MATERIALS AND METHODS

We evaluated 238 screening-detected benign lesions and 23 screening-detected lung cancers for 12 characteristics: spiculation, well-defined margin, concave margin, polygonal shape, notch/lobulation, solid component, ground-glass opacity (GGO), air bronchogram, cavity, bubble-like appearance, pleural indentation, and vascular convergence. We also measured the lesion diameters to set a threshold for benign lesions. We tested combinations of these characteristics to differentiate benign lesions from lung cancers.

RESULTS

By using certain combinations of the characteristics that showed statistically significant differences between benign lesions and lung cancers, benign lesions could be extracted without contamination by lung cancer in screening CT, when the combination included solid component as a positive finding. In HRCT, more than 80% of the benign lesions could be extracted without contamination by lung cancer when the combination included GGO as a negative finding.

CONCLUSION

It seems possible to reduce the frequency of follow-up HRCT to establish a diagnosis of benign lesions using certain combinations of the characteristics of benign nodules.

摘要

目的

确定良性肺病变的特征,以降低筛查计算机断层扫描(CT)中的假阳性率,并减少后续高分辨率CT(HRCT)的检查频率。

材料与方法

我们评估了238个筛查发现的良性病变和23个筛查发现的肺癌的12项特征:毛刺征、边界清晰、边缘凹陷、多边形形态、切迹/分叶、实性成分、磨玻璃密度影(GGO)、空气支气管征、空洞、气泡样表现、胸膜凹陷和血管集束。我们还测量了病变直径以设定良性病变的阈值。我们测试了这些特征的组合以区分良性病变和肺癌。

结果

通过使用在良性病变和肺癌之间显示出统计学显著差异的某些特征组合,在筛查CT中,当组合包括实性成分作为阳性表现时,良性病变可以在不被肺癌污染的情况下被提取出来。在HRCT中,当组合包括GGO作为阴性表现时,超过80%的良性病变可以在不被肺癌污染的情况下被提取出来。

结论

利用良性结节特征的特定组合来建立良性病变的诊断,似乎有可能减少后续HRCT的检查频率。

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