ArticleCurrent medical imaging2026
Association of AI-Derived Quantitative CT Parameters of Airway, Emphysema, and Pulmonary Vasculature with Lung Cancer: A Cross-Sectional Analysis
Article in Current medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundGiven multiple risk factors for lung cancer, this study explored associations between lung cancer and AI-derived quantitative chest computed tomography (CT) parameters of emphysema, airways, and pulmonary vasculature.
methodsThis retrospective single-center study (December 2020-February 2023) analyzed relevant parameters of the left upper lobe (LUL) and right upper lobe (RUL) in 170 lung cancer patients and 126 healthy individuals. Subgroups were defined by cancer-free lobes (129 patients/126 controls for LUL; 120 patients/126 controls for RUL). Univariate and multivariate binary logistic regression analyses were used for analysis.
resultsThe emphysema-related 15th percentile of CT attenuation values (PI-15) was significantly associated with lung cancer, with lower values in patients’ LUL. Pulmonary vascular parameters (diameter, count, area at 6 mm/24 mm from the lung surface) differed significantly; the patients had smaller diameters, higher counts, and larger areas at 6 mm in the LUL. Airway parameters (Awt-Pi10, level 6 wall thickness) were higher in patients’ LUL. Multivariate regression identified PI-15 and vascular diameters (6 mm/24 mm) in LUL [area under the curve (AUC) = 0.841, 95% confidence interval (95% CI): 0.789–0.892] and vascular diameters (6 mm/24 mm) and vascular count at 24 mm from the lung surface in RUL (AUC=0.819, 95% CI:0.766–0.872) as significant predictors (all P<0.001).
conclusionAI-derived quantitative CT parameters of emphysema, vasculature, and airways are associated with lung cancer and may serve as complementary tools for clinical risk assessment.
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