Abstract
We aimed to analyze CT features of persistent subsolid nodules (SSN) ≦3 cm diagnosed pathologically as adenocarcinoma spectrum to investigate whether parameters enable distinction between invasive pulmonary adenocarcinomas (IPAs) and pre-invasive lesions. A total of 129 patients with 141 SSNs confirmed with surgically pathologic proof were retrospectively reviewed. Of 141 SSNs, there were 57 pure ground-glass nodules (GGNs), 22 heterogeneous GGNs, and 62 part-solid nodules. SSN subclassification showed a significant linear trend with invasive degree of the adenocarcinoma spectrum (pure GGNs 7%; heterogeneous GGNs 36.4%; part-solid nodules 85.5%, P for trend <0.0001). For IPA detection in 141 SSNs, a solid part of ≧3 mm was the most specificity (sensitivity, 76.9%; specificity, 94.7%), followed by air-bronchogram sign (sensitivity, 53.8%; specificity, 89.5%), SSN subclassification (sensitivity, 81.5%; specificity, 88.2%), and a lesion size ≧12 mm (sensitivity, 84.6%; specificity, 76.3%). For IPA detection in 79 pure or heterogeneous GGNs, the heterogeneous GGN sign was the most useful finding, with most specificity (sensitivity, 66.7%; specificity, 79.1%), followed by CT attenuation (HU) of ≧−493 (sensitivity, 75%; specificity, 74.6%) and a lesion size ≧10 mm (sensitivity, 83.3%; specificity, 70.1%). In conclusion, this simple combined visual and semiquantitative analysis of CT features helps distinguish IPAs from pre-invasive lesions.
Highlights
With the introduction of low-dose computed tomography (LDCT) for lung cancer screening in recent years, persistent subsolid nodules (SSNs) have played an important role in highly association with lung adenocarcinomas[1,2,3,4]
There were no significant differences in sex ratio and the frequency of multiple primary lung cancer (MPLC) percentages among these two groups
We demonstrated that simple semiquantitative analysis of CT features enables the differentiation of invasive pulmonary adenocarcinomas (IPAs) lesions from pre-invasive/minimally invasive lesions that appear as SSNs with size ≦ 3 cm
Summary
With the introduction of low-dose computed tomography (LDCT) for lung cancer screening in recent years, persistent subsolid nodules (SSNs) have played an important role in highly association with lung adenocarcinomas[1,2,3,4]. This new classification addresses these new concepts of invasiveness degree in the adenocarcinoma spectrum, such as atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive pulmonary adenocarcinoma (IPA) according to the 2011 International Association for the Study of Lung Cancer, the American Thoracic Society, and the European Respiratory Society (IASLC/ ATS/ERS) classification[5]. We want to investigate the association between characteristic CT features and the pathologic invasiveness of the lung adenocarcinoma spectrum based on the novel SSN classification system
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