Asthma, COPD, Cystic Fibrosis, Interstitial Lung Disease
Conditions
Brief summary
Lung structural abnormalities are complex, time-consuming, and may lack reproducibility to evaluate visually on CT scans. The study's aim is to perform automated recognition of structural abnormalities in CT scans of patients with chronic lung diseases by using dedicated software.
Detailed description
Three chronic lung diseases will constitute the target of the study, by using retrospective data from each lung disease: * Cystic fibrosis * Asthma and COPD * Interstitial lung diseases Dedicated algorithms will be developped for each disease condition.
Interventions
OTHERObservational study
Sponsors
Institut National de la Santé Et de la Recherche Médicale, France
Collaborative NOVAA study group
Hôpital Haut Lévêque
Study design
Observational model
OTHER
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
3 Years to 70 Years
Healthy volunteers
No
Inclusion criteria
* Patients with chronic lung disease and clinical examination, pulmonary function test, and CT acquired during a routine follow-up
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Validity of automated measurement | From date of inclusion until the date of final quantification, assessed up to 12 months | Correlations and comparisons with other biomarker of the disease severity |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Correlation with pulmonary function test | From date of inclusion until the date of final quantification, assessed up to 12 months | Correlation of quantitative measurement with pulmonary function |
| Longitudinal variation over time | From date of inclusion until the date of final quantification, assessed up to 12 months | Comparison of quantitative measurement at two time points |
| Reproducibility | From date of inclusion until the date of final quantification, assessed up to 12 months | Evaluation of measurements when performed twice |
Countries
France
Outcome results
None listed