AIM: This study aimed to systematically evaluate the independent predictive value and diagnostic performance of quantitative indices derived from early postoperative computed tomography (CT) imaging for predicting major complications (Clavien-Dindo grade ≥II) within 30 days after pulmonary segmentectomy.

METHODS: A total of 231 patients who underwent Video-Assisted Thoracoscopic Surgery (VATS) segmentectomy were retrospectively enrolled. On CT images obtained within 2–3 days postoperatively, the depth of pleural effusion, pneumothorax rate, lung re-expansion ratio, and maximum subcutaneous air thickness were measured. The primary outcome was the occurrence of Clavien-Dindo grade ≥II complications within 30 days. Univariate and multivariate logistic regression analyses were performed, and predictive performance was evaluated using the area under the curve (AUC).

RESULTS: Major complications occurred in 42 patients (18.2%). Multivariate analysis identified depth of pleural effusion (odds ratio [OR] = 1.213, 95% confidence interval [CI]: 1.107–1.329, p < 0.001), pneumothorax rate (OR = 1.201, 95% CI: 1.081–1.333, p < 0.001), lung re-expansion ratio (OR = 0.872, 95% CI: 0.809–0.940, p < 0.001), and maximum subcutaneous air thickness (OR = 1.438, 95% CI: 1.248–1.656, p < 0.001) as independent predictors. Receiver operating characteristic (ROC) analysis demonstrated that maximum subcutaneous air thickness had the highest predictive performance (AUC = 0.850), followed by pneumothorax rate (AUC = 0.831), lung re-expansion ratio (AUC = 0.785), and depth of pleural effusion (AUC = 0.783).

CONCLUSIONS: Quantitative indices derived from early postoperative CT scans may serve as reliable imaging biomarkers for predicting major complications after pulmonary segmentectomy, thereby facilitating early identification of high-risk patients and guiding individualized postoperative management.