Checking consistency of automated ILD extent measurements on chest CT

Evaluation of the Reproducibility of the Automated Measurement of the Extent of Interstitial Lung Disease on Chest CT

Not applicable Interventional Assistance Publique - Hôpitaux de Paris · NCT06743022

We will test whether automated software gives consistent measurements of how much interstitial lung disease an adult has on same-day chest CT scans for people with idiopathic pulmonary fibrosis or connective tissue disease–related ILD.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment150 (estimated)
Ages18 Years and up
SexAll
SponsorAssistance Publique - Hôpitaux de Paris Academic / other
Locations6 sites (Paris, IDF and 5 other locations)
Trial IDNCT06743022 on ClinicalTrials.gov

What this trial studies

This interventional protocol obtains two chest CT scans on the same day from patients with known ILD at two Paris hospitals and runs multiple automated quantification tools on the images. The study compares the automated extent-of-disease measurements and lung volumes between the paired scans and across different software packages. It examines whether factors such as degree of inspiration, reconstruction settings, or ILD subtype (IPF versus CTD-related ILD) affect measurement variability. The goal is to characterize the real-world reproducibility of automated ILD quantification methods.

Who should consider this trial

Good fit: Adults (≥18) with known ILD due to idiopathic pulmonary fibrosis or connective tissue disease who are followed at the participating hospitals, scheduled for a routine chest CT, covered by French social security, and able to give informed consent.

Not a fit: Patients with an acute ILD exacerbation, pregnant patients, those unable to hold a 10-second breath, or those requiring extra positional or expiratory imaging are unlikely to benefit from participation.

Why it matters

Potential benefit: If successful, this work could make automated CT measurements reliable enough to help doctors track disease progression and support treatment decisions.

How similar studies have performed: Several texture-analysis and deep-learning tools have shown promising accuracy for quantifying ILD on single CT scans, but reproducibility across repeated same-day scans and different software has not been firmly established.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Age ≥ 18 years
* Known interstitial lung disease as part of idiopathic pulmonary fibrosis or connective tissue disease
* Followed in one of the participating hospitals
* Requiring a chest CT as part of a scheduled assessment
* Affiliated to a French national social security
* Informed consent

Exclusion Criteria:

* Acute exacerbation of ILD
* Pregnancy
* Inability to hold an apnea for 10 seconds
* Patients in the exclusion period after a previous research
* Need for additional procubitus or expiratory images

Where this trial is running

Paris, IDF and 5 other locations

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Interstitial Lung DiseaseLung DiseasesMultidetector Computed TomographyDeep Learning
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.