An observational study in Asthma (Diagnosis) and COPD (Chronic Obstructive Pulmonary Disease), sponsored by Korea University Guro Hospital. Recruiting at 2 sites in South Korea. Open to participants aged 19 Years and older. Per ClinicalTrials.gov, last updated 2026-07-07.
Sponsored by Korea University Guro Hospital · Observational
This study aims to improve the diagnosis and treatment prediction of asthma and chronic obstructive pulmonary disease (COPD) by combining quantitative chest computed tomography (CT) imaging with multi-omics data.
Adults with asthma or COPD will be enrolled and undergo routine clinical evaluations, pulmonary function tests, blood tests, and chest CT scans. Additional samples, such as sputum and microbiome specimens, may also be collected. No experimental drugs or devices will be administered as part of this study.
Researchers will analyze CT imaging features together with clinical, laboratory, and biological data to better distinguish asthma from COPD and to identify factors that may predict treatment response. The findings are expected to contribute to more precise and personalized management of chronic airway diseases.
This is a prospective, observational, multi-center cohort study designed to integrate quantitative chest CT imaging with multi-omics data to improve differentiation between asthma and chronic obstructive pulmonary disease (COPD) and to identify biomarkers associated with treatment response.
Eligible participants will include adults diagnosed with asthma or COPD who agree to participate in longitudinal clinical follow-up. At baseline and during follow-up, participants will undergo standard clinical assessments, including symptom questionnaires, pulmonary function testing, blood sampling, and chest CT imaging. Additional biological samples, such as sputum and microbiome specimens, may be collected when clinically feasible.
Quantitative CT metrics (e.g., low attenuation area percentage, parametric response mapping features, airway wall measurements, and mucus plug scores) will be extracted from imaging data. These imaging biomarkers will be integrated with clinical variables, laboratory parameters (including inflammatory markers and immunoglobulin profiles), and microbiome data.
The primary objectives are: (1) to identify imaging and biological signatures that distinguish asthma from COPD, and (2) to determine whether these signatures can predict response to standard clinical treatments. No investigational drugs or medical devices are involved, and all procedures reflect routine clinical care.
Data will be analyzed using advanced statistical and computational methods to explore associations between imaging, biological markers, and clinical outcomes. Results are expected to enhance understanding of disease mechanisms and support the development of personalized treatment strategies for chronic airway diseases.
Adults aged 19 years or older with clinically diagnosed asthma or COPD who are receiving routine care at participating centers and consent to participate in a prospective observational cohort study involving clinical assessments, pulmonary function testing, and chest CT imaging.
Exclusion Criteria:
This cohort includes adults with physician-diagnosed asthma or chronic obstructive pulmonary disease (COPD) who are enrolled in a prospective, observational study. Participants undergo routine clinical assessments, pulmonary function testing, blood sampling, and chest computed tomography (CT) imaging as part of standard care and study-related data collection. No investigational drugs or medical devices are administered. Data from clinical evaluations, imaging, and biospecimens (e.g., blood and sputum) will be analyzed to characterize disease features and predict treatment response.
Imaging and multi-omic signatures that differentiate asthma from COPD and predict treatment response
Composite signatures derived from quantitative chest CT metrics (e.g., low attenuation area percentage, parametric response mapping features, airway measurements, and mucus plug score) integrated with clinical variables, pulmonary function indices, blood-based inflammatory markers, and sputum/microbiome profiles. These integrated features will be evaluated for their ability to (1) distinguish asthma from COPD and (2) predict clinical treatment response.
Time frame: From baseline to last follow-up visit (anticipated up to 12 months after enrollment)
Change in Lung Function (FEV1)
Change in pre-bronchodilator and/or post-bronchodilator FEV1 (mL) from baseline to last follow-up visit.
Time frame: Baseline to 12 months
Frequency of acute exacerbations
Number of moderate or severe exacerbations during follow-up.
Time frame: Up to 12 months after enrollment
Changes in Quantitative Chest CT Imaging Biomarkers (LAA-950, PRMfSAD, Pi10, BV5/TBV)
Changes in chest CT-derived quantitative imaging biomarkers including parametric response mapping of functional low attenuation area at -950 HU (LAA-950), small airway disease (PRMfSAD), airway wall thickness (Pi10), and small vessel fraction (BV5/TBV) from baseline to last follow-up visit.
Time frame: Baseline to last follow-up visit (up to 12 months)
Plan to share: Yes — De-identified individual participant data (IPD), including clinical variables, pulmonary function data, and quantitative chest CT metrics, may be shared with qualified investigators upon reasonable request. Data sharing will be subject to approval by the Institutional Review Board and execution of a data use agreement to ensure appropriate use, confidentiality, and protection of participant privacy. Requests may be submitted after publication of primary study results.
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Korea University Guro Hospital