Deep Learning Integration of Chest Computed Tomography Imaging and Gene Expression Identifies Novel Aspects of COPD.

ABSTRACT:

Rationale

Chronic obstructive pulmonary disease (COPD) is characterized by pathologic changes in the airways, lung parenchyma, and persistent inflammation, but the links between lung structural changes and blood transcriptome patterns have not been fully described.

Objections

The objective of this study was to identify novel relationships between lung structural changes measured by chest computed tomography (CT) and blood transcriptome patterns measured by blood RNA sequencing (RNA-seq).

Methods

CT scan images and blood RNA-seq gene expression from 1223 participants in the COPD Genetic Epidemiology (COPDGene^®) study were jointly analyzed using deep learning to identify shared aspects of inflammation and lung structural changes that we labeled image-expressi

SUBMITTER: Chen J 

PROVIDER: S-EPMC10699487 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature