Relationship between pulmonary nodule malignancy and surrounding pleurae, airways and vessels: a quantitative study using the public LIDC-IDRI dataset
Yulei Qin, Yun Gu, Hanxiao Zhang, Jie Yang, Lihui Wang, Zhexin Wang,, Feng Yao, Yue-Min Zhu

TL;DR
This study uses a large public CT dataset to analyze how surrounding pulmonary structures relate to nodule malignancy, identifying potential structural biomarkers for lung cancer diagnosis.
Contribution
It introduces a quantitative method to assess surrounding structures of pulmonary nodules and demonstrates their correlation with malignancy, advancing non-invasive diagnostic approaches.
Findings
Malignant nodules are closer to pleurae, airways, and vessels.
Higher contact and volume of surrounding structures correlate with malignancy.
Features of surrounding structures can serve as potential lung cancer biomarkers.
Abstract
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…
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Taxonomy
TopicsLung Cancer Diagnosis and Treatment · Radiomics and Machine Learning in Medical Imaging · Medical Imaging Techniques and Applications
MethodsLogistic Regression
