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NCT Number: NCT07602192

Quantitative Chest CT and Multi-Omics to Distinguish Asthma From COPD and Predict Treatment Response

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.

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Key information

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age ≥19 years
  • COPD group: post-bronchodilator FEV1/FVC < 0.70
  • Asthma group: clinically confirmed diagnosis of asthma by a physician
  • Able to provide voluntary written informed consent

Exclusion criteria

  • Acute exacerbation or active lower respiratory tract infection (e.g., pneumonia) within the past 4 weeks
  • Pregnancy or breastfeeding
  • Inability to undergo chest CT (e.g., poor cooperation or severe medical condition)
  • Refusal to consent to study procedures

Treatment and study plan

Primary outcomes

  1. Imaging and multi-omic signatures that differentiate asthma from COPD and predict treatment response

    Time frame: From baseline to last follow-up visit (anticipated up to 12 months after enrollment)

    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.

Secondary outcomes

  1. Change in Lung Function (FEV1)

    Time frame: Baseline to 12 months

    Change in pre-bronchodilator and/or post-bronchodilator FEV1 (mL) from baseline to last follow-up visit.

  2. Frequency of acute exacerbations

    Time frame: Up to 12 months after enrollment

    Number of moderate or severe exacerbations during follow-up.

  3. Changes in Quantitative Chest CT Imaging Biomarkers (LAA-950, PRMfSAD, Pi10, BV5/TBV)

    Time frame: Baseline to last follow-up visit (up to 12 months)

    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.

Study contacts

Contact information is provided by the study sponsor or research team.

Clinical Research Office Korea University Guro Hospital

CONTACT

[email protected]

+82-2-2626-1659

Sang Hyuk Kim, MD

CONTACT

[email protected]

+82-2-2626-1659

Sponsors and collaborators

Lead sponsor

Korea University Guro Hospital

Other

Collaborators

  • Seoul National University Boramae Hospital
  • The Korean Academy of Tuberculosis and Respiratory Diseases

Registry information

Official study title

Prospective Multicenter Cohort to Discriminate Asthma Versus Chronic Obstructive Pulmonary Disease and Predict Treatment Response Using Quantitative Chest CT and Multi-Omics

Acronym: CTOMICS

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
May 22, 2026
Registry last updated
Jul 7, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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