Deep Learning Estimation of Small Airways Disease from Inspiratory Chest CT is Associated with FEV₁ Decline in COPD.

ABSTRACT:

Rationale

Quantifying functional small airways disease (fSAD) requires additional expiratory computed tomography (CT) scan, limiting clinical applicability. Artificial intelligence (AI) could enable fSAD quantification from chest CT scan at total lung capacity (TLC) alone (fSAD^TLC).

Objectives

To evaluate an AI model for estimating fSAD^TLC and study its clinical associations in chronic obstructive pulmonary disease (COPD).

Methods

We analyzed 2513 participants from the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS). Using a subset (n = 1055), we developed a generative model to produce virtual expiratory CTs for estimating fSAD^TLC in the remaining 1458 SPIROMICS participants. We compared fSAD^TLC</

SUBMITTER: Chaudhary MFA 

PROVIDER: S-EPMC11419202 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature