Purpose: Lung cancer is one of the most common forms of cancer.It is therefore highly desirable to develop methods that can give an early warning signal.The aim of this study was to explore the heterogeneous nature of textural features between malignant and benign pulmonary nodules in CT images and their correlations with pulmonary nodules prognosis.Methods: 4372 benign or malignant pulmonary nodule CT images acquired from 502patients (152 benign cases with 1343 pulmonary nodules; 350 malignant cases with 3399pulmonary nodules) were collected.The propensity score method was used to balance observed covariates to ensure that the benign and malignant groups were balanced and comparable.By using contourlets, every pulmonary nodule can be decomposed into four scales with 48 directions,14 texture features were thus calculated.The least absolute shrinkage and selection operator(LASSO), a type of variable selection method, was used to rank the contourlets textural features according to standardised coefficients of the LASSO regression.The first ten most important variables were evaluated for the performance of correlation with pulmonary nodule prognosis at =0.005 based on longitudinal cases.Results: Based on 502 cases, 146 cases (73 pairs of benign and malignant cases with 1619 pulmonary nodules) were matched by their propensity score.Among the first ten most important textural features, sum entropy at scale 4, direction 6 (Spearman correlation coefficient =-1.000, P < 0.0001)and sum entropy at scale 4, direction 15 (Spearman correlation coefficient =-0.791, P < 0.0001) were significantly different for the analysis of correlation with pulmonary nodules prognosis at =0.005.Conclusions: The study provided preliminary evidence that analysis of pulmonary nodules texture on CT images is potentially a superior predictor for patients with pulmonary nodules.