Application of the quantitative parameters of HRCT in predicting the pathological invasiveness of subreal nodule lung adenocarcinoma

Objective To evaluate the application of HRCT quantitative parameters in differentiating subsolid nodules (SSNs) in the forms of invasive adenocarcinoma (IAC), minimally invasive adenocarcinoma (MIA) and preinvasive lesions (PIL). Methods A total of 116 patients with peripheral lung adenocarcinoma who were pathologically diagnosed with and characterized in SSNs through CT scanning in the Second Hospital of Xuzhou Medical University from June 2017 to June 2021 were enrolled. Their clinical data were retrospectively analyzed, with 116 SSNs including 56 pure ground glass nodules (pGGNs) and 60 partial solid nodules (PSNs). According to their prognosis, the patients were divided into two groups: a PIL/MIA group (n=65) and an IAC group (n=51). Univariate and binary logistic regression analyses were performed to identify the independent risk factors for predicting IAC. Results According to univariate analysis, there were statistical differences in average CT value, the maximal CT value, CT difference between nodules and lung tissue, mass, volume, and 3D long diameter between the two groups (all P<0.001). According to binary logistic regression and receiver operating characteristic (ROC) analysis, CT difference and mass were the independent risk factors for IAC. The threshold of CT difference for diagnosing IAC was 420.83 HU AUC: 0.873; sensitivity: 82.4%; and specificity: 81.5%, while the threshold of mass for diagnosing IAC was 513.89 mg AUC: 0.888; sensitivity: 72.5%; and specificity: 92.3%. The AUC of CT difference combined with mass to diagnose IAC was 0.944, with a sensitivity of 90.2% and a specificity of 89.2%. Conclusions Mass and CT difference are reliable indicators to predict the invasiveness of SSNs. The combined use of mass and CT difference has a higher value in predicting their invasiveness than mass or CT difference alone.