• Discriminating between bronchiolar adenoma, adenocarcinoma in situ and minimally invasive adenocarcinoma of the lung with CT

    Diagn Interv Imaging . 2020 Dec;101(12):831-837. doi: 10.1016/j.diii.2020.05.005. Epub 2020 May 29.

    L Cao, Z Wang, T Gong, J Wang, J Liu, L Jin, Q Yuan

    Abstract

    Purpose: To identify computed tomography (CT) features that may help distinguish bronchiolar adenoma (BA) from lung adenocarcinomas in situ (AIS) and minimally invasive adenocarcinomas (MIA) among lung lesions presenting as ground-glass nodules (GGNs).

    Materials and methods: A total of 140 patients with GGNs confirmed by surgery and pathology, were reviewed retrospectively. There were 68 men and 72 women with a mean age of 64.3±8.9 (SD) years (range: 31 - 85 years). The CT features of BA, AIS, and MIA were analyzed and compared. CT features, including percentage of solid component, maximum diameter of solid component, lesion density, location, margin, shape, pseudo-cavitation, calcification, ill-defined peripheral opacity, and air bronchogram, were analyzed using multivariate logistic regression and receiver operating characteristic curves.

    Results: There were 11/140 (7.9%) patients with BA (mean age, 67.7±7.5 [SD]; range 45 - 77 years), 63/140 (45.0%) patients with AIS (mean age, 62.5±8.6 [SD]; range 36 - 69 years) and 66/140 (47.1%) patients with MIA (mean age, 63.5±7.9 [SD]; range 35 - 72 years). By comparison with AIS and MIA, significantly different CT features of BA included tumor size, solid component diameters, low CT attenuation of the ground-glass component, irregular shape, ill-defined peripheral opacity, pseudo-cavitation, and abnormal pulmonary vein. Ill-defined peripheral opacity (odds ratio, 1.060; 95% confidence interval [CI]: 1.020 - 1.380) and pseudo-cavitation (odds ratio, 1.236; 95% CI: 1.070 - 1.565) were variables independently associated with the diagnosis of BA.

    Conclusion: CT provides morphological features that allow differentiating between BA and AIS-MIA among lung lesions presenting as GGNs.

    Read Full Article Here: https://doi.org/10.1016/j.diii.2020.05.005