CClinicalTrials.gg
Active, not recruitingNCT04760548NOVAAUpdated Jan 5, 2024

Segmentation of Structural Abnormalities in Chronic Lung Diseases

An observational study in Cystic Fibrosis, Asthma and COPD, sponsored by Hôpital Haut Lévêque. Active, not recruiting at 1 site in France. Open to participants aged 3 Years to 70 Years. Per ClinicalTrials.gov, last updated 2024-01-05.

Sponsored by Hôpital Haut Lévêque · Observational

From the registry’s dates

  • Primary completion was expected by Feb 2024, 2 years 7 months ago, but the record still lists the study as active, not recruiting.
Study type
Observational
Model
Other
Time perspective
Other
Enrollment
800
Ages
3 Years to 70 Years
Sex
All
01

Study 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.

Read the 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.

02

Conditions studied

  • Cystic Fibrosis
  • Asthma
  • COPD
  • Interstitial Lung Disease
03

In context

Cystic Fibrosis

1,581 studies on the registry are indexed under Cystic Fibrosis; 190 are open to participants now.

This study's planned enrollment of 800 is above the median of 85 across 482 observational studies indexed under Cystic Fibrosis.

Browse Cystic Fibrosis studies →

Lead sponsor

Hôpital Haut Lévêque is the lead sponsor of 2 studies on the registry; none are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
3 Years to 70 Years
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

Patients with chronic lung disease and a Clinical examination, pulmonary function test, and CT acquired during an annual routine follow-up

Eligibility criteria

Inclusion Criteria:

  • Patients with chronic lung disease and clinical examination, pulmonary function test, and CT acquired during a routine follow-up
05

Study design

Observational model
Other
Time perspective
Other
Enrollment
800 participants (estimated)
Patient registry
No

Groups and cohorts

  • Train dataset

    This group is dedicated to developing an automated algorithm

    Other: Observational study

  • Test dataset

    This group is dedicated to testing the semantic performance of an automated algorithm

    Other: Observational study

  • Clinical Validations

    Patients groups are dedicated to assessing the clinical validity of the measurement in independent validation cohorts, with or without longitudinal evaluations such as monitoring of a treatment effect

    Other: Observational study

Interventions

  • OtherObservational study
06

What researchers measure

Primary outcomes

  1. Validity of automated measurement

    Correlations and comparisons with other biomarker of the disease severity

    Time frame: From date of inclusion until the date of final quantification, assessed up to 12 months

Secondary outcomes

  1. Correlation with pulmonary function test

    Correlation of quantitative measurement with pulmonary function

    Time frame: From date of inclusion until the date of final quantification, assessed up to 12 months

  2. Longitudinal variation over time

    Comparison of quantitative measurement at two time points

    Time frame: From date of inclusion until the date of final quantification, assessed up to 12 months

  3. Reproducibility

    Evaluation of measurements when performed twice

    Time frame: From date of inclusion until the date of final quantification, assessed up to 12 months

07

Study locations

1 site
  • Hopital Haut Leveque
    Pessac, France
08

References and documents

Publications

  • Dournes G, Hall CS, Willmering MM, Brody AS, Macey J, Bui S, Denis de Senneville B, Berger P, Laurent F, Benlala I, Woods JC. Artificial intelligence in computed tomography for quantifying lung changes in the era of CFTR modulators. Eur Respir J. 2022 Mar 3;59(3):2100844. doi: 10.1183/13993003.00844-2021. Print 2022 Mar. PubMed 34266943 ↗

Individual participant data

Plan to share: Undecided — Automated software measurements

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jan 5, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT04760548
Lead sponsor
Hôpital Haut Lévêque
Collaborators
Institut National de la Santé Et de la Recherche Médicale, France, Collaborative NOVAA study group
Responsible party
Hôpital Haut Lévêque (Director, Hôpital Haut-Lévêque) — Sponsor-investigator
First posted
Feb 18, 2021
Start date
Jan 1, 2008
Primary completion
Feb 17, 2024 (estimated)
Completion
Feb 17, 2024 (estimated)
Last update
Jan 5, 2024

Study contacts

Patrick Berger, Pr
study chair · Hopital Haut Leveque

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is active, not recruiting, as verified in Sep 2023. You cannot join it, but the record below documents what was studied.

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