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…
Conditions studied
Asthma (Diagnosis), COPD (Chronic Obstructive Pulmonary Disease)
About this study
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.
Primary outcomes
- Imaging and multi-omic signatures that differentiate asthma from COPD and predict treatment response (From baseline to last follow-up visit (anticipated up to 12 months after enrollment))
Eligibility information
Study locations
- SMG-SNU Boramae Medical Center, Seoul, Dongjak-gu 07061 South Korea
- Korea University Guro Hospital, Seoul, Guro-gu 08308 South Korea
Source: ClinicalTrials.gov. Record last refreshed by Varda Clinical: 2026-09-27.