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AI reads lung scans to predict who will get worse

NCT ID NCT06162884

What the study statuses mean

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Recruitment status, easiest to join first

Recruiting now This study
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study looks at whether an artificial intelligence (AI) tool can predict if lung scarring (pulmonary fibrosis) will get worse over time. Researchers will analyze CT scans from 200 people with either idiopathic pulmonary fibrosis (IPF) or other types of interstitial lung disease. The goal is to see if a score from the AI can tell who is at higher risk of worsening, which could help doctors make better treatment decisions.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this could lead to a reliable way to predict which patients with pulmonary fibrosis will worsen, helping doctors plan better care.
What could go wrong
This is an observational study, not a treatment trial. The AI prediction tool may not prove accurate enough for routine use, and results may not apply to all patients.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 200 people

The number the study aims to enrol. It can still change while the study runs.

Started

Nov 2024

Expected to finish

Aug 2029

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Primary objective is to predict early for progression in both IPF and non-IPF ILD population using a new artificial intelligence machine learning (AI/ML) algorithm of Single Timepoint Prediction (STP) score from HRCT. The primary interest is to validate STP score in identifying cohort early for the candidate of anti-fibrotic treatment.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

IPF Inclusion Criteria: * Established a diagnosis (within 5 years) of IPF by enrolling center as defined by ATS/ERS/JRS/ALAT criteria * Age over or equal to 40 years old * No history of lung transplant * FVC % predicted \>= 45% * DLCO % predicted \>=25% * Women of childbearing potential (WOCBP) must be ready and able to use highly effective methods of birth control. WOCBP taking oral contraceptives (OCs) also have to use one barrier method. Non-IPF ILD Inclusion Criteria: * Established a diagnosis (within 5 years) of non-IPF ILD by enrolling center. * Age over or equal to 18 years old * Presence of chronic fibrosis ILD defined as architectural distortions with reticulation and the presence of traction bronchiectasis by visual assessment: (1) estimating visually \>5% in whole lung, or (2) mild pulmonary fibrosis and \<5% in whole lung (i.e., early non-IPF-ILD identified by a pulmonologist). * Patients treated with immunosuppressive agents (other than corticosteroids) for an underlying systemic disease need to be on a stable treatment for at least 12 weeks prior to screening * FVC % predicted \>= 45% * DLCO % predicted \>=25% * Women of childbearing potential (WOCBP) must be ready and able to use highly effective methods of birth control. WOCBP taking oral contraceptives (OCs) also have to use one barrier method Exclusion Criteria: * Planned to participate in an intervention trial within the next 6 months * Currently listed for lung transplantation at the time of enrollment * Malignancy, treated or untreated, other than malignancy unlikely to affect prognosis in the next 3 years such as skin cancer or non-metastatic prostate cancer within the past 5 years * Any clinically significant co-morbidity, which in the view of investigator, is likely to contribute to mortality or ability to perform PFT's in the next 2 years * Prebronchodilator Forced Expiratory Volume in 1 second (FEV1)/Forced vital capacity (FVC) \<0.7 at as screening * Exclusion of co-morbidities: congestive heart failure (stroke, deep vein thrombosis, pulmonary embolism, myocardial infarction), current virus-associated community acquired pneumonia, smoking-related chronic obstructive lung disease with FEV1 \<70%, history of lung cancer, history of other cancer treated within the past 4 years for IPF and 5 years for non-IPF ILD (excluding basal cell carcinoma of skin). HRCT data from subjects with combined pulmonary fibrosis and emphysema (CPFE) can be collected. Major Discontinuing Criteria in this study * lung transplant after baseline or death * withdraw of consent or transition to another care center

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Conditions

The condition(s) this trial relates to.

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

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Contacts and locations

Locations

  • UCLA

    RECRUITING

    Los Angeles, California, 90024, United States

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