Objectively Measured Chronic Lung Injury on Chest CT.

ABSTRACT:

Background

Tobacco smoke exposure is associated with emphysema and pulmonary fibrosis, both of which are irreversible. We have developed a new objective CT analysis tool that combines densitometry with machine learning to detect high attenuation changes in visually normal appearing lung (Norm_HA) that may precede these diseases.

Methods

We trained the classification tool by placing 34,528 training points in chest CT scans from 297 COPDGene participants. The tool was then used to classify lung tissue in 9,038 participants as normal, emphysema, fibrotic/interstitial, or Norm_HA. Associations between the quartile of Norm_HA and plasma-based biomarkers, clinical severity, and mortality were evaluated using Jonckheere-Terpstra, pairwise Wilcoxon rank

SUBMITTER: Harmouche R 

PROVIDER: S-EPMC6904856 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature