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Artificial Intelligence-Enabled One-Stop Chest CT: Unifying High-Resolution Anatomic Quantification with Low-Dose Functional Prediction in COPD

Artificial Intelligence-Enabled One-Stop Chest CT: Unifying High-Resolution Anatomic Quantification with Low-Dose Functional Prediction in COPD

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600116307
Enrollment
Unknown
Registered
2026-01-08
Start date
2026-02-01
Completion date
Unknown
Last updated
2026-01-12

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

Conditions

Chronic Obstructive Pulmonary Disease (COPD)

Interventions

Adaptive Statistical Iterative Reconstruction-V at 50% strength (ASiR-V50%) group:None
Deep Learning Image Reconstruction at Medium Level (DLIR-M) group:None
Filtered back projection (FBP) group:None
Deep Learning Image Reconstruction at Low Level (DLIR-L) group:None

Sponsors

The First Affiliated Hospital of Henan University of Science and Technology
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Adults aged >=18 years with a diagnosis of COPD, confirmed according to the 2025 GOLD guidelines. 2. Completion of both pulmonary function tests (PFT) and biphasic (inspiratory/expiratory) non-contrast chest CT scans on a GE Healthcare 256-slice CT scanner during the same clinical visit. 3. Availability of complete imaging and clinical data suitable for paired analysis.

Exclusion criteria

Exclusion criteria: 1. Patients with images exhibiting significant motion artifacts, severe metal artifacts, or other artifacts that compromise the quality of quantitative analysis and diagnostic interpretation. 2. Patients unable to cooperate with breathing instructions during the CT scan. 3. Patients with concurrent severe pulmonary diseases, such as pulmonary fibrosis or active tuberculosis.

Design outcomes

Primary

MeasureTime frame
Pulmonary function parameters;CT quantitative parameters;

Secondary

MeasureTime frame
CT quantitative parameters;

Countries

China

Contacts

Public ContactQiang Jun

The First Affiliated Hospital of Henan University of Science and Technology

15838815301@163.com+86 379 6483 0870

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026