To develop and validate a CT-based nomogram to predict the occurrence of loculated pneumothorax due to hook wire placement.

Patients (n = 177) were divided into pneumothorax (n = 72) and non-pneumothorax (n = 105) groups. Multivariable logistic regression analysis was applied to build a clinical prediction model using significant predictors identified by univariate analysis of imaging features and clinical factors. Receiver operating characteristic (ROC) was applied to evaluate the discrimination of the nomogram, which was calibrated using calibration curve.

Based on the results of multivariable regression analysis, transfissure approach [odds ratio (OR): 757.94; 95% confidence interval CI (21.20–27099.30) p < 0.0001], transemphysema [OR: 116.73; 95% CI (12.34–1104.04) p < 0.0001], localization of multiple nodules [OR: 8.04; 95% CI (2.09–30.89) p = 0.002], and depth of nodule [OR: 0.77; 95% CI (0.71–0.85) p < 0.0001] were independent risk factors for pneumothorax and were included in the predictive model (p < 0.05). The area under the ROC curve value for the nomogram was 0.95 [95% CI (0.92–0.98)] and the calibration curve indicated good consistency between risk predicted using the model and actual risk.

A CT-based nomogram combining imaging features and clinical factors can predict the probability of pneumothorax before localization of ground-glass nodules. The nomogram is a decision-making tool to prevent pneumothorax and determine whether to proceed with further treatment.

A nomogram composed of transfissure, transemphysema, multiple nodule localization, and depth of nodule has been developed to predict the probability of pneumothorax before localization of GGNs.