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AI could uncover hidden lung disease in routine chest X-Rays

NCT ID NCT07686562

Diagnosis Sponsor: Chung-Ang University Hospital Source: ClinicalTrials.gov ↗

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jul 07, 2026 · Last updated Jul 08, 2026 · Updated 1 time

Summary

This study evaluates an artificial intelligence (AI) software that analyzes chest X-rays to detect signs of interstitial lung disease (ILD), a group of conditions that scar the lungs. Researchers are checking how often the AI's flags for lung abnormalities turn out to be real disease, using follow-up CT scans as the gold standard. The study looks back at records of over 1,200 adults who had chest X-rays for other reasons, to see if the AI can incidentally catch ILD early.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
VUNO Med®-Chest X-ray™ (AI software)
What this could lead to
If successful, this AI tool could help doctors catch interstitial lung disease earlier from routine chest X-rays, potentially leading to faster diagnosis and treatment.
What could go wrong
This is a retrospective study using existing records, not a controlled trial. The AI may flag false positives, and results may not apply to other hospitals or populations.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

1,293 people

The number who actually took part.

Started

Feb 2022

Finished

Dec 2024

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Adults aged ≥19 years attending the pulmonology and allergy clinics of Chung-Ang University Hospital (Seoul and Gwangmyeong, Republic of Korea) who underwent chest radiography between January 2022 and December 2024.

Ages

19 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Adults aged 19 years or older * Visited the pulmonology and allergy clinic (outpatient or inpatient) at Chung-Ang University Hospital (Seoul or Gwangmyeong) and underwent chest radiography from January 2022 to December 2024 * A follow-up CT performed after the index chest radiograph * Reticular/interstitial opacity detected on the index radiograph by VUNO Med®-Chest X-ray™ Exclusion Criteria: * Prior history of ILD or ILD-related disease before the index chest radiograph, or a CT report containing terms related to interstitial opacity * Non-frontal (non-posteroanterior/anteroposterior \[PA/AP\]) chest radiograph view position * Missing CT report or final clinical diagnosis

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Conditions

The condition(s) this trial relates to.

idiopathic pulmonary fibrosis interstitial lung disease

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Chest X-ray for clinical evaluation Idiopathic pulmonary fibrosis (IPF) Incidental findings Interstitial lung disease (ILD) Lung disease, interstitial

Contacts and locations

Locations

  • Chung-Ang University Hospital

    Seoul, Seoul, 06973, South Korea

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