AI reads lung scans to predict who will get worse
NCT ID NCT06162884
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
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About 200 people
The number the study aims to enrol. It can still change while the study runs.
- Started
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Nov 2024
- Expected to finish
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Aug 2029
An estimate. End dates often move.
- Lead sponsor
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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
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18 years and older
- Sex
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Anyone
- Healthy volunteers
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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 Hide 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.
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The places running it
1 site. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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A doctor treating you
A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.
Contacts and locations
Locations
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UCLA
RECRUITINGLos Angeles, California, 90024, United States
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Other studies related to the condition(s) this trial covers.
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- Can a thousand patient records unlock better care for a rare lung disease?
- Sharper CT scans may solve a lung disease diagnostic puzzle