Biphasic quantitative CT to classify a residual volume-defined subclinical gas-trapping phenotype: development and internal validation of a multivariable model
Year: 2025
Type: article
Study design: Observational Study
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: percentile lung density (Perc15) were not significant (P>0.05). RV%pred correlated moderately with VI-856, MLD_ex/in, MLD_ex-in (|r|≈0.44-0.49), and weakly with VI-950 (r≈0.25). The qCT model achieved an area under the receiver operating characteristic curve (AUC) =0.862 (training) and 0.788 (internal validation), with good calibration and decision-analytic net benefit; feature contributions were dominated by VI-856, MLD_ex/in, and MLD_ex-in. 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.
Source: Journal of Thoracic Disease
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7117796655
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