Artificial Intelligence (AI) Detection of Incidental Interstitial Opacity on Chest Radiography (NCT07686562) | Clinical Trial Compass
CompletedNot Applicable
Artificial Intelligence (AI) Detection of Incidental Interstitial Opacity on Chest Radiography
South Korea1,293 participantsStarted 2022-02-01
Plain-language summary
The goal of this observational study is to learn how well an artificial intelligence (AI)-based chest X-ray analysis software can incidentally detect interstitial lung disease (ILD), which appears as interstitial opacity, on chest X-rays taken for other reasons, and whether these AI-flagged findings represent true interstitial opacity.
The main question it aims to answer is: How often does an AI-flagged interstitial opacity correspond to true ILD?
This retrospective study uses existing records: researchers review each participant's follow-up computed tomography(CT), CT report, and final diagnosis to confirm true ILD and reticular opacity.
Who can participate
Age range
19 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
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
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
Positive predictive value (PPV) of AI-detected interstitial opacity
Timeframe: From the index chest radiograph to the reference standard confirmation (the first follow-up CT after the index chest radiograph and/or final clinical diagnosis), up to 3.5 years