AI reads CT scans to predict lung cancer years before it starts
NCT ID NCT07685028
First seen Jul 06, 2026 · Last updated Jul 07, 2026 · Updated 1 time
Summary
This study tests whether an artificial intelligence (AI) model called Sybil can predict a person's risk of developing lung cancer based on a CT scan of the chest. The study enrolls people aged 18 to 80 who have a family history of lung cancer. Participants receive a CT scan, and the AI analyzes the images to estimate the risk of lung cancer over the next several years. The goal is to see if this AI tool can accurately identify who is most likely to develop lung cancer, potentially leading to earlier detection and better outcomes.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- Active substance
- CT scan and Sybil AI model
- What this could lead to
- If successful, this AI tool could help identify people at high risk for lung cancer earlier, potentially improving survival through earlier detection.
- What could go wrong
- This is a relatively small study, and the AI model may not perform as well in this specific population as hoped. It is a prediction tool, not a cure or treatment.
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.
- Phase
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Not a phased trial
Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.
- Participants
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About 250 people
The number the study aims to enrol. It can still change while the study runs.
- Expected to start
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Oct 2026
An estimate. Start dates often move.
- Expected to finish
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Dec 2035
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.
- Ages
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18 to 80 years
- 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.
Inclusion Criteria: * Age: Must meet both the upper and lower age limit criteria. * Upper age limit: ≤80 years of age * Lower age limit: * ≥40 years of age OR * ≥18 years of age AND ≤10 years of youngest relative's age at time of lung cancer diagnosis (e.g., if a relative was diagnosed at 35 years of age, participant can enroll at ≥25 years of age) * Positive family history of lung cancer (defined as): * Has ≥1 first-degree relative, OR * Has ≥2 second-degree relatives with a diagnosis of non-small cell lung cancer or small cell lung cancer (NB: a first-degree relative = parent, sibling, or child, a second-degree relative = grandparent, blood-related aunt or uncle, grandchild, blood-related niece or nephew, half-sibling) Exclusion Criteria: * Must not have a personal history of lung cancer at the time of enrollment. * Must not have a personal history of stage IV cancer of any type at the time of enrollment. * Must not have had surgical removal of any portion of the lung, excluding needle or core lung biopsy at the time of enrollment. * Must not have had a chest CT within 12 months prior to trial enrollment.
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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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Massachusetts General Hospital
Boston, Massachusetts, 02114, United States
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