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To investigate whether the pleurae, airways and vessels surrounding a noduleon non-contrast computed tomography (CT) can discriminate benign and malignantpulmonary nodules. The LIDC-IDRI dataset, one of the largest publicly availableCT database, was exploited for study. A total of 1556 nodules from 694 patientswere involved in statistical analysis, where nodules with average scorings <3and >3 were respectively denoted as benign and malignant. Besides, 339 nodulesfrom 113 patients with diagnosis ground-truth were independently evaluated.Computer algorithms were developed to segment pulmonary structures and quantifythe distances to pleural surface, airways and vessels, as well as the countingnumber and normalized volume of airways and vessels near a nodule. Odds ratio(OR) and Chi-square (\chi^2) testing were performed to demonstrate thecorrelation between features of surrounding structures and nodule malignancy. Anon-parametric receiver operating characteristic (ROC) analysis was conductedin logistic regression to evaluate discrimination ability of each structure.For benign and malignant groups, the average distances from nodules to pleuralsurface, airways and vessels are respectively (6.56, 5.19), (37.08, 26.43) and(1.42, 1.07) mm. The correlation between nodules and the counting number ofairways and vessels that contact or project towards nodules are respectively(OR=22.96, \chi^2=105.04) and (OR=7.06, \chi^2=290.11). The correlation betweennodules and the volume of airways and vessels are (OR=9.19, \chi^2=159.02) and(OR=2.29, \chi^2=55.89). The areas-under-curves (AUCs) for pleurae, airways andvessels are respectively 0.5202, 0.6943 and 0.6529. Our results show thatmalignant nodules are often surrounded by more pulmonary structures comparedwith benign ones, suggesting that features of these structures could be viewedas lung cancer biomarkers.

Relationship between pulmonary nodule malignancy and surrounding  pleurae, airways and vessels: a quantitative study using the public LIDC-IDRI  dataset