Association between automatic AI-based quantification of airway-occlusive mucus plugs and all-cause mortality in patients with COPD

Thorax. 2025 Jan 17;80(2):105-108. doi: 10.1136/thorax-2024-221928.

Abstract

In this cohort study involving 9399 current and former smokers from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease study, we assessed the relationship between artificial intelligence-quantified mucus plugs on chest CTs and all-cause mortality. Our results revealed a significant positive association, particularly for those with COPD GOLD stages 1-4, with HRs of 1.18 for 1-2 mucus-obstructed bronchial segments and 1.27 for ≥3 obstructed segments. This corroborates previous visual mucus plug counting research and demonstrates the relevance of mucus plugs in COPD pathology and as a marker for risk assessment. Automated mucus plug quantification methods may provide an efficient tool for both clinical evaluations and research.

Trial registration: ClinicalTrials.gov NCT00608764.

Keywords: COPD epidemiology; Imaging/CT MRI etc; Smoking.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Artificial Intelligence*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Mucus* / diagnostic imaging
  • Pulmonary Disease, Chronic Obstructive* / diagnostic imaging
  • Pulmonary Disease, Chronic Obstructive* / mortality
  • Pulmonary Disease, Chronic Obstructive* / physiopathology
  • Risk Assessment
  • Tomography, X-Ray Computed

Associated data

  • ClinicalTrials.gov/NCT00608764