Predicting invasiveness of subsolid nodules: a HRCT-based model for lung adenocarcinoma

BACKGROUND: Subsolid nodules (SSNs) pose a diagnostic challenge in lung adenocarcinoma management. High-resolution computed tomography (HRCT) allows detailed characterization of SSNs, aiding in distinguishing pathological subtypes. OBJECTIVE: To investigate the correlation between HRCT features and pathological subtypes of SSNs, and their association with nodule size and morphological features. METHODS: Clinical and HRCT data from 84 patients with surgically confirmed lung adenocarcinoma were retrospectively analyzed. All patients underwent preoperative CT scans, with lesions measuring ≤3.0 cm and a ground-glass opacity component ≥50%. The evaluated CT characteristics included leison size, lobulation, spiculation, pleural indentation, and CT values. Pathological diagnosis were established according to the latest classification standards. RESULTS: Significant differences were observed among AIS, MIA, and IAC groups in age, lobulation, spiculation, and nodule size (all P