AI reads CT scans to predict lung cancer years before it starts

NCT ID NCT07685028

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
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 Results may not be published yet.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)
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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

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Status unknown
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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

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

About 250 people

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

Expected to start

Oct 2026

An estimate. Start dates often move.

Expected to finish

Dec 2035

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.

Ages

18 to 80 years

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.

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

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  1. The places running it

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

  2. The official record

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  3. A doctor treating you

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Contacts and locations

Locations

  • Massachusetts General Hospital

    Boston, Massachusetts, 02114, United States

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