CT-based lung function imaging to predict COPD worsening

CT-Derived Functional Imaging for Predicting Disease Progression in COPD

['FUNDING_R01'] · UNIVERSITY OF TEXAS AT AUSTIN · NIH-11330624

This project uses paired inhale and exhale CT scans to create ventilation images that aim to find early lung changes and predict worsening in people with COPD or at risk for it.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF TEXAS AT AUSTIN (nih funded)
Locations1 site (AUSTIN, UNITED STATES)
Trial IDNIH-11330624 on ClinicalTrials.gov

What this research studies

You would have paired inhale and exhale CT scans used to make detailed maps of how air moves through your lungs. The team uses a computerized CT-derived ventilation (CTV) method that measures breathing-related volume changes rather than relying on raw CT density numbers. Their CTV approach has shown stronger agreement with nuclear medicine ventilation scans than earlier CT methods and is designed to be more stable across different breath levels. The goal is to use these images and measurements to identify people likely to get worse earlier than current staging systems can tell.

Who could benefit from this research

Good fit: Ideal candidates are people with diagnosed COPD, early-stage disease, or those at high risk for COPD (for example current or former smokers) who can undergo chest CT scans.

Not a fit: People who cannot safely have chest CTs (for example pregnant individuals or those with other contraindications) or those with very advanced, end-stage COPD where progression is already apparent may not benefit.

Why it matters

Potential benefit: If successful, this could help spot COPD progression earlier so treatments or lifestyle changes can start sooner to slow decline and improve quality of life.

How similar studies have performed: Other CT-based methods using density measures showed moderate links to disease, while this group's CTV method has already shown better agreement with nuclear ventilation scans, though using CTV to predict long-term progression is a newer application.

Where this research is happening

AUSTIN, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.