Biphasic quantitative CT to classify a residual volume-defined subclinical gas-trapping phenotype: development and internal validation of a multivariable model.

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

SUBMITTER: Li F 

PROVIDER: S-EPMC12780376 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature