ArticleJournal of thoracic disease2025
Biphasic quantitative CT to classify a residual volume-defined subclinical gas-trapping phenotype: development and internal validation of a multivariable model.
Article in Journal of thoracic disease, 2025. 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
Background: Subclinical gas-trapping correlates with small-airway dysfunction but is not reliably detected by conventional spirometry. We aimed to develop and internally validate a multivariable biphasic quantitative computed tomography (qCT) model to discriminate a residual volume (RV)-defined gas-trapping phenotype [RV expressed as percent predicted (RV%pred) ≥120%]. Methods: In a single-center cross-sectional cohort (n=71), low-dose inspiratory/expiratory CT and pulmonary function testing were obtained within 1 week. RV was measured by single-breath (SB) gas dilution and RV%pred. Participants were stratified as RV-elevated (≥120%) or RV-normal (<120%); qCT metrics were compared between groups, correlations with RV%pred were examined, and a five-fold cross-validated logistic model was built with calibration and decision-curve analyses. Results: Twenty-three of 71 (32.4%) met the RV-elevated criterion. Compared with RV-normal, the RV-elevated group showed higher mean lung density ratio (MLD_ex/in) (P=0.005), lower mean lung density difference (MLD_ex-in) (P=0.007), and higher low-attenuation fractions (VI-856, VI-950, VI-910) (P≤0.03); lung volume ratio (LV), volume decrease ratio (VDR), relative volume change (RVC), 15 Conclusions: Biphasic qCT-especially VI-856, MLD_ex/in, MLD_ex-in-captures a subclinical gas-trapping phenotype aligned with an RV-based operational definition and may aid early risk stratification and monitoring.
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