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Multi-task generative artificial intelligence for the early warning of chronic obstructive pulmonary disease with low-dose chest CT

Multi-task generative artificial intelligence for the early warning of chronic obstructive pulmonary disease with low-dose chest CT

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600127021
Enrollment
Unknown
Registered
2026-06-23
Start date
2025-11-01
Completion date
Unknown
Last updated
2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Chronic obstructive pulmonary disease

Interventions

COPD group:None
Prism group:None
Individuals with normal lung function:None

Sponsors

The Second Affiliated Hospital of Naval Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. COPD patients with a definitive clinical diagnosis ( diagnostic criteria: predicted forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC0.7, FEV1=0.7, FEV1>= predicted value of 0.8); 2. Complete CT images; 3. Pulmonary function data.

Exclusion criteria

Exclusion criteria: 1. Obvious respiratory motion or metal artifacts on chest CT imaging; 2. Absence of original thin-slice (1mm) images; 3. Severe pulmonary tuberculosis, extensive pulmonary infection, acute pulmonary embolism or pulmonary infarction; significant pleural adhesions; 4. Thoracic deformity; 5. Pleural effusion or pneumothorax; 6. History of thoracic surgery; 7. Other conditions affecting data analysis.

Design outcomes

Primary

MeasureTime frame
FEV1/FVC;FEV1;FVC;FEV1%;Emphysema;Airway;Lung Vessel;—

Countries

China

Contacts

Public ContactLi Fan

Naval Medical University/The Second Affiliated Hospital of Naval Medical University, Shanghai Changzheng Hospital

fanli0930@163.com+86 135 6468 4699

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jul 3, 2026