Quantifying Structural Airway Remodeling in Severe Asthma
Addressing current challenges
Severe asthma is a heterogeneous disease with distinct clinical phenotypes that respond differently to targeted therapies. Beyond airway inflammation, structural changes, particularly in the small airways, play a central role in disease persistence, progression, and treatment resistance.
Inflammation and remodelling in these peripheral airways often remain undetected by conventional lung function testing until advanced stages, contributing to airway wall thickening, lumen narrowing, mucus plugging, and air trapping.
Traditional endpoints such as spirometry, FeNO, and symptom scores provide indirect insight into these processes and lack sensitivity to regional and subtle structural change. As a result, robust phenotyping, monitoring of disease progression, and objective assessment of treatment effects over time remain challenging.
3%-10%
variation of severe diagnosis
Advancing treatment strategies with AI
To address these challenges, Thirona’s AI-based analyses enable sensitive quantification of airway remodelling and mucus-related abnormalities across the bronchial tree, including small-airway involvement that is difficult to assess with conventional methods, supporting:
- Objective quantification of airway remodeling, including wall thickening, lumen narrowing, mucus plugging, and air trapping
- Quantitative assessment of small-airway involvement, capturing extent and regional distribution of structural change
- Improved patient phenotyping, integrating structural airway patterns with inflammatory markers
- Reproducible longitudinal monitoring of treatment response, enabling objective evaluation of structural effects over time
In patients with severe or uncontrolled asthma, chest CT imaging is an essential tool to uncover comorbidities and structural changes that impact management decisions. With AI-driven analysis, CT interpretation will evolve from diagnostic support to enabling earlier, more personalized treatments across asthma and other complex lung diseases.
Prof. Dr. Arnaud Bourdin, MD
Hôpital Arnaud de Villeneuve, University of Montpellier France
Use cases accelerating precision medicine
Phenotyping of structural abnormalities in severe paediatric patients
Severe asthma is characterized by airway inflammation, mucus plugs and structural abnormalities especially within small airways. While these changes have been identified in adult populations, the extent and prevalence have remained unowned in the pediatric population.
By leveraging LungQ® analyses, the presence of airway abnormalities were quantified in CT scans of children with severe asthma. The AI enabled analyses provided a precise quantification of key structural changes including bronchiectasis, bronchial wall thickening and mucus plugs. In addition, small airway disease was also found to be related with bronchial wall thickening.
Validation studies
European Respiratory Journal
| January 2026
Automatic detection of mucus plugs on computed tomography scans in severe paediatric asthma
American Thoracic Society Conference
| May 2023
Automatic and Manual Quantification of Small Airways Disease on Chest CT of Children With Severe Asthma
ERJ Open Research
| August 2023
Children with severe asthma have substantial structural airway changes on computed tomography
European Respiratory Journal (ERS Congress)
| October 2024
Airway Thickening, Mucus Plugs and Eosinophilia in Bronchiectasis and Asthma
ERJ Open Research
| August 2025
Automated computed tomographic analysis of bronchial thickness and mucus plugs in bronchiectasis with asthma
Longitudinal structural assessment of treatment response in severe asthma
Benralizumab, an anti-interleukin-5 receptor α monoclonal antibody, is designed to reduces eosinophilic inflammation in severe asthma, however, its effects on lung structural remodeling has not been fully understood or easily quantified.
By leveraging LungQ® analyses, the treatment effect of Benralizumab were captured and quantified over 48 weeks. The AI-driven quantitative CT analysis provided a longitudinal assessment, demonstrating a sustained reduction of mucus plugs and borderline improvement in bronchial wall thickening. The analyses provided definitive evidence of structural reversibility in response to the therapy.
