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Recruiting NCT07602192

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

Observational Asthma (Diagnosis) COPD (Chronic Obstructive Pulmonary Disease)

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
This is an observational study: the protocol does not assign a study treatment.
Who it may be relevant to
Registry conditions: Asthma (Diagnosis), COPD (Chronic Obstructive Pulmonary Disease). Basic parameters: from 19 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
South Korea
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

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

Overview

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.

Detailed description

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.

Primary outcome measures

  • 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)]
Secondary outcome measures (3)
  • Change in Lung Function (FEV1) [Time frame: Baseline to 12 months]
  • Frequency of acute exacerbations [Time frame: Up to 12 months after enrollment]
  • 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)]

Eligibility criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Cohort

Study locations

South Korea · 2 centers
  • SMG-SNU Boramae Medical Center — Seoul
  • Korea University Guro Hospital — Seoul

Publications

  • Chaudhary MFA, Bhatt SP. Imaging Endpoints for Biologic Therapy in Chronic Obstructive Pulmonary Disease. Br J Radiol. 2025 Jul 31:tqaf179. doi: 10.1093/bjr/tqaf179. Online ahead of print. PMID 40742322
  • Trivedi A, Hall C, Hoffman EA, Woods JC, Gierada DS, Castro M. Using imaging as a biomarker for asthma. J Allergy Clin Immunol. 2017 Jan;139(1):1-10. doi: 10.1016/j.jaci.2016.11.009. PMID 28065276
  • Bhatt SP, Han MK. Developing and Implementing Biomarkers and Novel Imaging in COPD. Chronic Obstr Pulm Dis. 2016 Jan 15;3(1):485-490. doi: 10.15326/jcopdf.3.1.2015.0170. PMID 28848871
  • Kim SH, Yang Z, Chang SW, Sim JK, Oh JY, Min KH, Hur GY, Lee SY, Shim JJ, Choi J, Yong HS. Airway Quantification Using Ultra-Low-Dose Computed Tomography Correlates With Pulmonary Function Indices in Patients With Asthma. J Korean Med Sci. 2026 Feb 2;41(5):e56. doi: 10.3346/jkms.2026.41.e56. PMID 41633329

Identifiers

NCT: NCT07602192 · CTOMICS1 · 2025GR0637

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗