Vascular Biomarkers for Pulmonary Nodule Malignancy: Arteries vs. Veins.

Simple Summary: The prevalence of indeterminate pulmonary nodule (IPN) findings in early lung cancer screening settings highlights the need for novel imaging biomarkers to assist clinicians in making informed therapeutic decisions. The surrounding vasculature of pulmonary nodules, termed "macro-vasculature", has been identified as a potential biomarker for evaluating nodule malignancy. However, the relationship between the macro-vasculature's arteries and veins surrounding an IPN and its malignancy remains unclear. This study aimed to investigate this association. Our findings indicate that arterial characteristics significantly outweigh venous characteristics in distinguishing malignant from benign nodules. Additionally, incorporating arterial information surrounding a nodule enhances the performance in differentiating malignant from benign nodules. Clarifying the relationship between macro-vasculature arteries and nodule malignancy may facilitate clinical follow-up procedures for screen-detected pulmonary nodules. Objective: This study aims to investigate the association between the arteries and veins surrounding a pulmonary nodule and its malignancy. Methods: A dataset of 146 subjects from a LDCT lung cancer screening program was used in this study. AI algorithms were used to automatically segment and quantify nodules and their surrounding macro-vasculature. The macro-vasculature was differentiated into arteries and veins. Vessel branch count, volume, and tortuosity were quantified for arteries and veins at different distances from the nodule surface. Univariate and multivariate logistic regression (LR) analyses were performed, with a special emphasis on the nodules with diameters ranging from 8 to 20 mm. ROC-AUC was used to assess the performance based on the k-fold cross-validation method. Average feature importance was evaluated in several machine learning models. Results: The LR models using macro-vasculature features achieved an AUC of 0.78 (95% CI: 0.71–0.86) for all nodules and an AUC of 0.67 (95% CI: 0.54–0.80) for nodules between 8–20 mm. Models including macro-vasculature features, demographics, and CT-derived nodule features yielded an AUC of 0.91 (95% CI: 0.87–0.96) for all nodules and an AUC of 0.82 (95% CI: 0.71–0.92) for nodules between 8–20 mm. In terms of feature importance, arteries within 5.0 mm from the nodule surface were the highest-ranked among macro-vasculature features and retained their significance even with the inclusion of demographics and CT-derived nodule features. Conclusions: Arteries within 5.0 mm from the nodule surface emerged as a potential biomarker for effectively discriminating between malignant and benign nodules. [ABSTRACT FROM AUTHOR]