Abstract
Purpose: To evaluate the diagnostic performance of CT radiomic features extracted from tumor and peritumoral regions in identifying pathological subtypes of T1-stage lung adenocarcinoma presenting as pure ground-glass nodules (pGGNs). Methods: A retrospective analysis was conducted on the data of T1-stage lung adenocarcinoma patients who underwent surgical resection and whose preoperative CT scans revealed pGGNs from June 2020 to June 2023 in our hospital. 3D Slicer was used to extract radiomic features of the intratumoral (VOI entire) and peritumoral regions (VOI +2 mm), and Rad-scores were calculated from the coefficients of features obtained after dimensionality reduction with LASSO regression. Results: A total of 131 patients with T1-stage lung adenocarcinoma presenting as pGGNs were included in this study; of these, 84 were pathologically diagnosed with the lepidic-predominant (LPA) subtype, and 47 were diagnosed with non-LPA. The diagnostic performance of the VOI entire and VOI +2 mm features for the pathological subtype of pGGN was superior to that of conventional features, with the VOI +2 mm features showing the best performance: the area under the curve, sensitivity, specificity, and accuracy in the training set were 0.883, 0.964, 0.667, and 0.761, respectively. Conclusion: Intra- and especially peritumoral-based radiomic features have high diagnostic performance for the pathological subtype of T1-stage lung adenocarcinoma presenting as pGGNs.