Interstitial Lung Disease (ILD)
Conditions
Brief summary
This project aimed to: 1) construct a cohort of no less than 10000 cases of f-ILD (including pneumoconiosis ≥3000 cases) with continuous regular follow-up to reveal the clinical phenotypes closely related to the development, progression and prognosis of pulmonary fibrosis; 2) systematically evaluate the safety and effectiveness of frozen lung biopsy, surgical lung biopsy/thoracoscopic lung biopsy and other techniques, and to optimize the histological diagnosis method of f-ILD; 3) construct a set of artificial intelligence (AI) evaluation system for quantitative evaluation of pulmonary fibrosis and its severity, and develop application software; 4) excavate and verify important molecular targets for the formation of pulmonary fibrosis and identify biomarkers; 5) combined with clinical phenotype, imaging, pathology and biomarkers to establish f-ILD early recognition and progress model, intervention strategies, guidelines and consensus, and applicated nationwide.
Interventions
None listed
Sponsors
The First Affiliated Hospital of Guangzhou Medical University
Nankai University
Jilin University
Shanghai Pulmonary Hospital, Shanghai, China
Shanghai Chest Hospital
Institute of Basic Medical Sciences CAMS
Tongji Hospital
National Institute for Occupational Health and Poison Control
Infervision Medical Technology Company Limited
Dai Huaping
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Diagnosed as ILD
Exclusion criteria
* Lack of chest CT * Patients refused to participant
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Clinical diagnostic protocol of ILD tissue biopsy | 3 years | Report on the reliability and safety assessment of TBLC and SLB diagnostics. |
| Predict model | 3 years | The contents were based on the f-ILD cohort, combined with clinical, imaging, pathological, lung function and biomarker analysis, and constructed a multidimensional model for the early recognition and progression of f-ILD. |
| Severity of fibrosis in HRCT assessed by AI system in patients with ILD | 3 years | Explore the diversity of abnormal image performance in patients with f-ILD, and extract multidimensional information based on deep learning and other methods. Realize the intelligent quantitative analysis of the severity of fibrosis. |
| F-ILD cohort | 6 years | The researchers used inclusion/exclusion criteria for screening, and collected the demographic information, clinical symptoms and signs, laboratory tests, treatment, survival and other conditions of the patients who agreed to participate in the program and signed the informed consent, and collected biological specimens. |
| Important molecular targets and biomarkers identified by multi-omics | 3 years | Single cell map of lung tissue in the early stage of ILD, key molecular targets and biomarkers for the development and progression of pulmonary fibrosis. |
Countries
China
Contacts
Primary ContactHuaping Dai, M.D. Ph.D.
Outcome results
None listed