AccuPulmo CT Portal for Detecting Pulmonary Fibrosis on Chest CT
Official title: Evaluation of the Accuracy and Effectiveness of the AccuPulmo CT Portal AI-Assisted Interpretation System for the Diagnosis of Pulmonary Fibrosis
Run by Taichung Veterans General Hospital · NCT07761377 · Data updated 2026-11-12
This study tests how well the AccuPulmo CT Portal can identify pulmonary fibrosis on existing chest CT scans from adults at Taichung Veterans General Hospital.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 20 Years and up |
| Sex | All |
| Enrollment | 900 (estimated) |
| Sponsor | Taichung Veterans General Hospital Academic / other |
| Locations | 1 site (Taichung) |
| Status | Recruiting |
| Started | October 15, 2025 |
| Main results expected | December 31, 2026 |
| Study ends | December 31, 2026 |
| Registry record updated | August 12, 2026 |
| Trial ID | NCT07761377 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults aged 20 years or older who had chest CT scans for pulmonary disease at Taichung Veterans General Hospital between 2020 and 2024 with available de-identifiable images and radiology reports.
✕Probably not a fit
Patients whose scans are not interpretable or do not show fibrosis may not benefit from this diagnostic tool.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is a single-center, retrospective study using pre-existing chest CT images to test the performance of an AI-assisted imaging software. Three blinded specialists will independently judge each image for pulmonary fibrosis, with a majority agreement used as the reference standard. The AI tool will be applied to the de-identified images to compare its outputs with expert consensus. Approximately 900 CT exams (about 300 with fibrosis and 600 without) collected between 2020 and 2024 will be analyzed. Exclusions include poor image quality or data that interfere with lung texture assessment.
Why it matters
Potential benefit: If successful, the AI portal could help radiologists more quickly and consistently identify pulmonary fibrosis on CT scans.
How similar studies have gone: Similar AI-based imaging tools have shown promise in detecting lung fibrosis, but this is a retrospective performance study focused on a specific portal.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Participants aged 20 years or older at the time of the chest computed tomography examination * Participants who underwent chest computed tomography for pulmonary disease at Taichung Veterans General Hospital between January 1, 2020, and December 31, 2024 * Availability of a completed clinical radiology report * Availability of chest computed tomography images suitable for de-identification and analysis by AccuPulmo CT Portal * Availability of sufficient image information to permit blinded specialist assessment of pulmonary fibrosis Exclusion Criteria: * Missing or incomplete chest computed tomography images * Image quality insufficient for pulmonary fibrosis assessment * Cardiac implants or other devices that substantially interfere with lung texture assessment * Extensive pneumonia that substantially interferes with lung texture assessment * Pleural effusion that substantially interferes with lung texture assessment * Other image abnormalities or artifacts that preclude reliable evaluation of pulmonary fibrosis
Where it's running
-
Taichung Veterans General Hospital City: Taichung
Taichung, Taiwan Recruiting
Study contacts
- Study coordinator: Pin-Kuei Fu, MD
- Email: yetquen@gmail.com
- Phone: 886 4 2359 2525
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.