Quantitative computed tomography predicts outcomes in idiopathic pulmonary fibrosis.

ABSTRACT:

Background and objective

Prediction of disease course in patients with progressive pulmonary fibrosis remains challenging. The purpose of this study was to assess the prognostic value of lung fibrosis extent quantified at computed tomography (CT) using data-driven texture analysis (DTA) in a large cohort of well-characterized patients with idiopathic pulmonary fibrosis (IPF) enrolled in a national registry.

Methods

This retrospective analysis included participants in the Australian IPF Registry with available CT between 2007 and 2016. CT scans were analysed using the DTA method to quantify the extent of lung fibrosis. Demographics, longitudinal pulmonary function and quantitative CT metrics were compared using descriptive statistics. Linear mixed models, and Cox analyses adj

SUBMITTER: Humphries SM 

PROVIDER: S-EPMC9796832 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature