Background Pattern of emphysema at chest CT, scored visually by using the Fleischner
Society system, is associated with physiologic impairment and mortality risk. Purpose To …

Purpose To develop a deep learning–based algorithm to stage the severity of chronic
obstructive pulmonary disease (COPD) through quantification of emphysema and air …

Background Multiple studies have identified COPD subtypes by using visual or quantitative
evaluation of CT images. However, there has been no systematic assessment of a combined …

Rationale: Although studies have evaluated emphysema and fibrotic interstitial lung
abnormality individually, less is known about their combined progression. Objectives: To …

Purpose To determine whether visually assessed patterns of emphysema at CT might
provide a simple assessment of mortality risk among cigarette smokers. Materials and …

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there
is not yet consensus on how many COPD subtypes there are and how they should be …

Background Approximately half of adults with chronic obstructive pulmonary disease
(COPD) remain undiagnosed. Chest CT scans are frequently acquired in clinical practice …

Background COPD is a leading cause of mortality. Research Question We hypothesized that
applying machine learning to clinical and quantitative CT imaging features would improve …

Background Pulmonary emphysema is divided into 3 major subtypes at autopsy:
centrilobular, paraseptal, and panlobular emphysema. These subtypes can be defined by …

Background Emphysema is a key contributor to airflow limitation in chronic obstructive
pulmonary disease (COPD) and can be quantified using CT scanning. We investigated the …