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Artificial Intelligence (AI) Detection of Incidental Interstitial Opacity on Chest Radiography

NCT07686562 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1293

Last updated 2026-07-07

No results posted yet for this study

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.

Conditions

  • Lung Disease, Interstitial
  • Idiopathic Pulmonary Fibrosis (IPF)
  • Incidental Findings
  • Interstitial Lung Disease (ILD)
  • Chest X-ray for Clinical Evaluation

Interventions

DEVICE

VUNO Med®-Chest X-ray™

VUNO Med®-Chest X-ray™ is artificial intelligence (AI)-based software that supports the detection and diagnosis of abnormal findings on chest radiographs. It automatically identifies abnormal findings and provides information on their type and location to aid clinical decision-making.

Sponsors & Collaborators

  • VUNO Inc.

    collaborator INDUSTRY

  • Chung-Ang University Hospital

    lead OTHER

Eligibility

Min Age
19 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-02-01
Primary Completion
2024-12-31
Completion
2024-12-31

Countries

  • South Korea

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07686562 on ClinicalTrials.gov