Predictors of CT Morphologic Features to Identify Spread Through Air Spaces Preoperatively in Small-Sized Lung Adenocarcinoma - Qi, Lin; Xue, Ke; Cai, Yongjun; Lu, Jinjuan; Li, Xiaohu; Li, Ming (Frontiers in Oncology, 2021)
Objectives This study aimed to explore the predictive CT features of spread through air spaces (STAS) in patients with small-sized lung adenocarcinoma. Methods From January 2017 to May 2019，patients with confirmed pathology of small-sized lung adenocarcinoma (less than or equal to 2 cm) and who underwent surgery were retrospectively analyzed. The clinical, pathological, and surgical information and CT features were analyzed. Results A total of 47 patients with STAS (males, 61.7%; and mean age, 56±8years) and 143 patients without STAS (males, 58%; and mean age, 53±11 years) were included. Pathologically, papillary, micropapillary, solid predominant subtypes, and vascular and pleural invasion were most commonly observed features in STAS group. Radiologically, higher CTR, presence of spiculation, satellites, ground glass ribbon sign, pleural attachment, and unclear tumor-lung interface were more commonly observed features in the STAS group. CTR, presence of ground glass ribbons and pleural connection, and absence of cystic airspaces were considered as stable predictors of STAS in multivariate logistic models. The ROC analysis for predicting STAS demonstrated higher area under the curve (AUC) in the model that used CTR (0.760, 95% confidence interval, 0.69–0.83) for predicting STAS than in the model that used long diameter of entire lesion (0.640). Conclusions CTR is the best CT sign for predicting STAS in small-sized lung adenocarcinoma. The ground glass ribbon is a newly found indicator and has the potential for predicting STAS.