  To investigate whether the pleurae, airways and vessels surrounding a nodule
on non-contrast computed tomography (CT) can discriminate benign and malignant
pulmonary nodules. The LIDC-IDRI dataset, one of the largest publicly available
CT database, was exploited for study. A total of 1556 nodules from 694 patients
were involved in statistical analysis, where nodules with average scorings <3
and >3 were respectively denoted as benign and malignant. Besides, 339 nodules
from 113 patients with diagnosis ground-truth were independently evaluated.
Computer algorithms were developed to segment pulmonary structures and quantify
the distances to pleural surface, airways and vessels, as well as the counting
number and normalized volume of airways and vessels near a nodule. Odds ratio
(OR) and Chi-square (\chi^2) testing were performed to demonstrate the
correlation between features of surrounding structures and nodule malignancy. A
non-parametric receiver operating characteristic (ROC) analysis was conducted
in logistic regression to evaluate discrimination ability of each structure.
For benign and malignant groups, the average distances from nodules to pleural
surface, 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 of
airways 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 between
nodules 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 and
vessels are respectively 0.5202, 0.6943 and 0.6529. Our results show that
malignant nodules are often surrounded by more pulmonary structures compared
with benign ones, suggesting that features of these structures could be viewed
as lung cancer biomarkers.
