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Retrospective Validation of AccuPulmo CT Portal for Detecting Pulmonary Fibrosis on Chest CT

NCT07761377 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 900

Last updated 2026-08-12

No results posted yet for this study

Summary

This retrospective observational study evaluates the diagnostic performance of AccuPulmo CT Portal, an artificial intelligence-assisted medical imaging software, for detecting pulmonary fibrosis on pre-existing chest computed tomography images.

A total of 900 chest computed tomography examinations obtained at Taichung Veterans General Hospital between January 1, 2020, and December 31, 2024, will be retrospectively selected. The planned sample includes 300 examinations with pulmonary fibrosis and 600 examinations without pulmonary fibrosis.

All study images will be de-identified and coded before evaluation. Three qualified specialists in pulmonology or radiology will independently review each image without access to the original radiology report or the artificial intelligence output. The reference standard will be established by majority agreement of at least two of the three specialists.

AccuPulmo CT Portal will retrospectively analyze the coded images. An artificial intelligence-derived pulmonary fibrosis area greater than 10 percent will be classified as positive, and an area of 10 percent or less will be classified as negative. The primary performance measures are sensitivity and specificity. Secondary measures include accuracy, positive predictive value, negative predictive value, and performance across clinically relevant subgroups.

The software results will not be returned to treating physicians and will not affect participant diagnosis, treatment, or clinical management.

Conditions

Interventions

DEVICE

AccuPulmo CT Portal

AccuPulmo CT Portal is an artificial intelligence-assisted medical imaging software intended to analyze chest computed tomography images and identify imaging findings associated with pulmonary fibrosis. The software estimates the proportion of pulmonary fibrosis within the lung. In this study, a pulmonary fibrosis area greater than 10 percent is classified as positive, and a pulmonary fibrosis area of 10 percent or less is classified as negative. The software will be applied retrospectively to de-identified pre-existing chest computed tomography images in an offline research environment. Its output will not be returned to treating physicians and will not affect participant diagnosis, treatment, or clinical management.

Sponsors & Collaborators

  • V5med Inc.

    collaborator INDUSTRY

  • Taichung Veterans General Hospital

    lead OTHER

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-10-15
Primary Completion
2026-12-31
Completion
2026-12-31

Countries

  • Taiwan

Study Locations

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Entities

Diseases

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 NCT07761377 on ClinicalTrials.gov