Pulmonary FibrosisACCUPULMO-FIBRNCT07761377
Retrospective Validation of AccuPulmo CT Portal for Detecting Pulmonary Fibrosis on Chest CT
An observational study of Pulmonary Fibrosis and Interstitial Lung Disease, run by Taichung Veterans General Hospital at 1 site in Taiwan.
Trial 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. Read more about this study
- Who is it for?
- Ages 20 years and older
- Conditions the study is for
- Pulmonary Fibrosis, Interstitial Lung Disease
- What is being tested?
- AccuPulmo CT Portal
- Type of treatment
- Medical device
- How many people
- 900 participants
- Where
- 1 siteTaiwan
- Study dates
- 15 Oct 2025to 31 Dec 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The study population consists of adults who underwent clinically indicated chest computed tomography examinations for pulmonary disease at Taichung Veterans General Hospital between January 1, 2020, and December 31, 2024. Participants will be retrospectively identified from existing institutional radiology and clinical information systems. Only pre-existing chest computed tomography images, radiology records, and study-related clinical information will be used.
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site, 1 recruiting
- Recruiting
Taichung Veterans General Hospital City: Taichung
Taichung, 407219
Pin-Kuei Fu, MD, 886 4 2359 2525, yetquen@gmail.com
About this study
Official title: Evaluation of the Accuracy and Effectiveness of the AccuPulmo CT Portal AI-Assisted Interpretation System for the Diagnosis of Pulmonary Fibrosis
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.
Read more
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.
Read the detailed description
This is a single-center, retrospective, non-interventional diagnostic performance study using pre-existing chest computed tomography images and associated clinical information from Taichung Veterans General Hospital.
Eligible participants are adults aged 20 years or older who underwent chest computed tomography for pulmonary disease between January 1, 2020, and December 31, 2024. The study plans to include 900 chest computed tomography examinations, comprising approximately 300 pulmonary fibrosis-positive examinations and 600 pulmonary fibrosis-negative examinations.
Potentially eligible examinations will initially be identified from existing institutional radiology records. Images with missing data or image characteristics that substantially interfere with lung texture assessment, including cardiac implants, extensive pneumonia, or pleural effusion, will be excluded according to the prespecified eligibility criteria.
Before specialist review, positive and negative samples will be combined, de-identified, assigned blinded study codes, and randomly allocated for review. Three qualified specialists holding board certification in pulmonology or radiology will independently evaluate all study images. The specialists will not have access to participant identifiers, the original radiology reports, or the AccuPulmo CT Portal results. Each specialist will estimate the proportion of pulmonary fibrosis and classify each examination as pulmonary fibrosis positive or negative. The reference standard will be determined by majority agreement, defined as concordant classification by at least two of the three specialists.
All coded images will subsequently be analyzed by AccuPulmo CT Portal. According to the prespecified classification rule, a pulmonary fibrosis area greater than 10 percent will be classified as positive, designated as Critical Risk, whereas a pulmonary fibrosis area of 10 percent or less will be classified as negative, designated as Low Risk.
After completion of the blinded assessments, the database will be unblinded for statistical analysis. The AccuPulmo CT Portal classifications will be compared with the specialist-derived reference standard. The primary endpoints are sensitivity and specificity. Secondary endpoints are accuracy, positive predictive value, negative predictive value, and performance consistency across relevant clinical subgroups.
The study uses only pre-existing images and records. AccuPulmo CT Portal will be operated in an offline research environment, and its outputs will not be returned to treating physicians or used for clinical decision-making. No additional imaging examination, clinical procedure, treatment assignment, or participant contact will occur as part of this study.
- Conditions
- Pulmonary Fibrosis, Interstitial Lung Disease
- Being tested
- AccuPulmo CT Portal
- Keywords
- Artificial Intelligence, Medical Device Software, Chest Computed Tomography, Pulmonary Fibrosis, Interstitial Lung Disease, Computer-Aided Detection, Computer-Aided Triage, Diagnostic Performance, Image Analysis, Deep Learning
- Medical subject headings
- Pulmonary Fibrosis, Lung Diseases, Interstitial
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AccuPulmo CT PortalDevice
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.
| Study group | Role | What they receive |
|---|---|---|
| Pulmonary Fibrosis-Positive Cases | Participants with pre-existing chest computed tomography examinations selected as potentially positive for pulmonary fibrosis based on available institutional radiology records. Final pulmonary fibrosis status for the performance analysis will be determined by majority agreement of at least two of three blinded specialists in pulmonology or radiology. Receives: Device: AccuPulmo CT Portal | |
| Pulmonary Fibrosis-Negative Controls | Participants with pre-existing chest computed tomography examinations selected as potentially negative for pulmonary fibrosis based on available institutional radiology records. Final pulmonary fibrosis status for the performance analysis will be determined by majority agreement of at least two of three blinded specialists in pulmonology or radiology. Receives: Device: AccuPulmo CT Portal |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity of AccuPulmo CT Portal for Detecting Pulmonary Fibrosis
Sensitivity is defined as the proportion of pulmonary fibrosis-positive examinations according to the specialist-derived reference standard that are correctly classified as positive by AccuPulmo CT Portal. The reference standard is determined by majority agreement of at least two of three blinded specialists. A pulmonary fibrosis area greater than 10 percent generated by AccuPulmo CT Portal is classified as positive. Sensitivity will be reported with a 95 percent confidence interval and evaluated against the prespecified performance threshold of 0.80 using a one-sided binomial test.
Measured: Baseline
Specificity of AccuPulmo CT Portal for Detecting Pulmonary Fibrosis
Specificity is defined as the proportion of pulmonary fibrosis-negative examinations according to the specialist-derived reference standard that are correctly classified as negative by AccuPulmo CT Portal. The reference standard is determined by majority agreement of at least two of three blinded specialists. A pulmonary fibrosis area of 10 percent or less generated by AccuPulmo CT Portal is classified as negative. Specificity will be reported with a 95 percent confidence interval and evaluated against the prespecified performance threshold of 0.80 using a one-sided binomial test.
Measured: Baseline
Secondary outcomes (4)
Diagnostic Accuracy of AccuPulmo CT Portal
Diagnostic accuracy is defined as the proportion of all evaluated examinations that are correctly classified by AccuPulmo CT Portal as pulmonary fibrosis positive or pulmonary fibrosis negative compared with the specialist-derived reference standard. Accuracy will be reported with a 95 percent confidence interval and evaluated relative to the prespecified threshold of 0.80.
Measured: Baseline
Positive Predictive Value of AccuPulmo CT Portal
Positive predictive value is defined as the proportion of examinations classified as positive by AccuPulmo CT Portal that are pulmonary fibrosis positive according to the specialist-derived reference standard. Positive predictive value will be reported with a 95 percent confidence interval and evaluated relative to the prespecified threshold of 0.80.
Measured: Baseline
Negative Predictive Value of AccuPulmo CT Portal
Negative predictive value is defined as the proportion of examinations classified as negative by AccuPulmo CT Portal that are pulmonary fibrosis negative according to the specialist-derived reference standard. Negative predictive value will be reported with a 95 percent confidence interval and evaluated relative to the prespecified threshold of 0.80.
Measured: Baseline
Sensitivity and Specificity Across Prespecified Clinical Subgroups
The sensitivity and specificity of AccuPulmo CT Portal will be descriptively evaluated across prespecified clinically relevant subgroups, subject to the availability of corresponding retrospective data. Subgroups may include age, sex, computed tomography acquisition characteristics, and other clinical categories defined in the statistical analysis plan. Estimates will be reported with 95 percent confidence intervals.
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Aug 2026
- Study start15 Oct 2025
- Primary completion31 Dec 2026 (estimated)
- Study completion31 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pulmonary FibrosisStudies of the same condition, open and under way.
- More trials run by Taichung Veterans General HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 900 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Taichung Veterans General Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- V5med Inc.
- Responsible party
- Principal investigator, Pin-Kuei Fu, MD, PhD, Taichung Veterans General Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07761377
- Sponsor's protocol ID
- SE25732C
- Other IDs
- IGA11402
- Acronym
- ACCUPULMO-FIBR
- Status last verified
- Aug 2026
- First submitted
- 6 Aug 2026
- Last updated
- 12 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be made publicly available because the study uses medical images and associated clinical information that are subject to participant privacy requirements, institutional data governance policies, contractual restrictions, and applicable regulations. Aggregate and de-identified study results may be reported in scientific publications or regulatory submissions.
Study at a glance
From the registry record, last updated by the sponsor on 12 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of the Accuracy and Effectiveness of the AccuPulmo CT Portal AI-Assisted Interpretation System for the Diagnosis of Pulmonary Fibrosis
- ClinicalTrials.gov ID
- NCT07761377
- Acronym / sponsor ID
- ACCUPULMO-FIBR / SE25732C
- Conditions
- Pulmonary Fibrosis, Interstitial Lung Disease
- Keywords
- Artificial Intelligence, Medical Device Software, Chest Computed Tomography, Pulmonary Fibrosis, Interstitial Lung Disease, Computer-Aided Detection, Computer-Aided Triage, Diagnostic Performance
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 900 participants (estimated)
- Lead sponsor
- Taichung Veterans General HospitalUniversity, hospital or other
- Collaborators
- V5med Inc.
- Study start
- 15 Oct 2025 (actual)
- Primary completion
- 31 Dec 2026 (estimated)
- Study completion
- 31 Dec 2026 (estimated)
- First posted
- 12 Aug 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This is a single-center, retrospective, non-interventional diagnostic performance study using pre-existing chest computed tomography images and associated clinical information from Taichung Veterans General Hospital.
Eligible participants are adults aged 20 years or older who underwent chest computed tomography for pulmonary disease between January 1, 2020, and December 31, 2024. The study plans to include 900 chest computed tomography examinations, comprising approximately 300 pulmonary fibrosis-positive examinations and 600 pulmonary fibrosis-negative examinations.
Potentially eligible examinations will initially be identified from existing institutional radiology records. Images with missing data or image characteristics that substantially interfere with lung texture assessment, including cardiac implants, extensive pneumonia, or pleural effusion, will be excluded according to the prespecified eligibility criteria.
Before specialist review, positive and negative samples will be combined, de-identified, assigned blinded study codes, and randomly allocated for review. Three qualified specialists holding board certification in pulmonology or radiology will independently evaluate all study images. The specialists will not have access to participant identifiers, the original radiology reports, or the AccuPulmo CT Portal results. Each specialist will estimate the proportion of pulmonary fibrosis and classify each examination as pulmonary fibrosis positive or negative. The reference standard will be determined by majority agreement, defined as concordant classification by at least two of the three specialists.
All coded images will subsequently be analyzed by AccuPulmo CT Portal. According to the prespecified classification rule, a pulmonary fibrosis area greater than 10 percent will be classified as positive, designated as Critical Risk, whereas a pulmonary fibrosis area of 10 percent or less will be classified as negative, designated as Low Risk.
After completion of the blinded assessments, the database will be unblinded for statistical analysis. The AccuPulmo CT Portal classifications will be compared with the specialist-derived reference standard. The primary endpoints are sensitivity and specificity. Secondary endpoints are accuracy, positive predictive value, negative predictive value, and performance consistency across relevant clinical subgroups.
The study uses only pre-existing images and records. AccuPulmo CT Portal will be operated in an offline research environment, and its outputs will not be returned to treating physicians or used for clinical decision-making. No additional imaging examination, clinical procedure, treatment assignment, or participant contact will occur as part of this study.
Study design
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Pulmonary Fibrosis-Positive Cases | – | Device: AccuPulmo CT PortalParticipants with pre-existing chest computed tomography examinations selected as potentially positive for pulmonary fibrosis based on available institutional radiology records. Final pulmonary fibrosis status for the performance analysis will be determined by majority agreement of at least two of three blinded specialists in pulmonology or radiology. |
| Pulmonary Fibrosis-Negative Controls | – | Device: AccuPulmo CT PortalParticipants with pre-existing chest computed tomography examinations selected as potentially negative for pulmonary fibrosis based on available institutional radiology records. Final pulmonary fibrosis status for the performance analysis will be determined by majority agreement of at least two of three blinded specialists in pulmonology or radiology. |
Who may qualify
- Ages
- 20 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study population consists of adults who underwent clinically indicated chest computed tomography examinations for pulmonary disease at Taichung Veterans General Hospital between January 1, 2020, and December 31, 2024. Participants will be retrospectively identified from existing institutional radiology and clinical information systems. Only pre-existing chest computed tomography images, radiology records, and study-related clinical information will be used.
Key inclusion criteria (5 listed)
- 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
Key exclusion criteria (6 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AccuPulmo CT PortalAccuPulmo 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. | Device | Pulmonary Fibrosis-Negative Controls, Pulmonary Fibrosis-Positive Cases |
Primary outcome
Sensitivity of AccuPulmo CT Portal for Detecting Pulmonary Fibrosis
Time frame: Baseline
Sensitivity is defined as the proportion of pulmonary fibrosis-positive examinations according to the specialist-derived reference standard that are correctly classified as positive by AccuPulmo CT Portal. The reference standard is determined by majority agreement of at least two of three blinded specialists. A pulmonary fibrosis area greater than 10 percent generated by AccuPulmo CT Portal is classified as positive. Sensitivity will be reported with a 95 percent confidence interval and evaluated against the prespecified performance threshold of 0.80 using a one-sided binomial test.
Specificity of AccuPulmo CT Portal for Detecting Pulmonary Fibrosis
Time frame: Baseline
Specificity is defined as the proportion of pulmonary fibrosis-negative examinations according to the specialist-derived reference standard that are correctly classified as negative by AccuPulmo CT Portal. The reference standard is determined by majority agreement of at least two of three blinded specialists. A pulmonary fibrosis area of 10 percent or less generated by AccuPulmo CT Portal is classified as negative. Specificity will be reported with a 95 percent confidence interval and evaluated against the prespecified performance threshold of 0.80 using a one-sided binomial test.
4 secondary outcomes
Diagnostic Accuracy of AccuPulmo CT Portal
Time frame: Baseline
Positive Predictive Value of AccuPulmo CT Portal
Time frame: Baseline
Negative Predictive Value of AccuPulmo CT Portal
Time frame: Baseline
Sensitivity and Specificity Across Prespecified Clinical Subgroups
Time frame: Baseline
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Aug 2026.
- Individual participant dataSharing planned: No. Individual participant data will not be made publicly available because the study uses medical images and associated clinical information that are subject to participant privacy requirements, institutional data governance policies, contractual restrictions, and applicable regulations. Aggregate and de-identified study results may be reported in scientific publications or regulatory submissions.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pulmonary Fibrosis and Interstitial Lung Disease, run by Taichung Veterans General Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 12 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Pin-Kuei Fu, MD (886 4 2359 2525, yetquen@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensitivity of AccuPulmo CT Portal for Detecting Pulmonary Fibrosis (time frame: Baseline). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Aug 2026.