Construction of a predictive model of 2–3 cm ground-glass nodules developing into invasive lung adenocarcinoma using high-resolution CT

Abstract

BackgroundThe purpose of this study was to analyze the imaging risk factors for the development of 2–3 cm ground-glass nodules (GGN) for invasive lung adenocarcinoma and to establish a nomogram prediction model to provide a reference for the pathological prediction of 2–3 cm GGN and the selection of surgical procedures.MethodsWe reviewed the demographic, imaging, and pathological information of 596 adult patients who underwent 2–3 cm GGN resection, between 2018 and 2022, in the Department of Thoracic Surgery, Second Affiliated Hospital of the Air Force Medical University. Based on single factor analysis, the regression method was used to analyze multiple factors, and a nomogram prediction model for 2–3 cm GGN was established.Results(1) The risk factors for the development of 2–3 cm GGN during the invasion stage of the lung adenocarcinoma were pleural depression sign (OR = 1.687, 95%CI: 1.010–2.820), vacuole (OR = 2.334, 95%CI: 1.222–4.460), burr sign (OR = 2.617, 95%CI: 1.008–6.795), lobulated sign (OR = 3.006, 95%CI: 1.098–8.227), bronchial sign (OR = 3.134, 95%CI: 1.556–6.310), diameter of GGN (OR = 3.118, 95%CI: 1.151–8.445), and CTR (OR = 172.517, 95%CI: 48.023–619.745). (2) The 2–3 cm GGN risk prediction model was developed based on the risk factors with an AUC of 0.839; the calibration curve Y was close to the X-line, and the decision curve was drawn in the range of 0.0–1.0.ConclusionWe analyzed the risk factors for the development of 2–3  cm GGN during the invasion stage of the lung adenocarcinoma. The predictive model developed based on the above factors had some clinical significance.