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AI eye on lung cancer: new study tests smart screening for High-Risk families

NCT ID NCT07600801

Diagnosis Sponsor: Massachusetts General Hospital Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 25, 2026 · Last updated Aug 26, 2026 · Updated 3 times

Summary

This study will enroll 2,250 adults with a family history of lung cancer to see if an AI model called Sybil can accurately predict future lung cancer from chest CT scans. Participants will provide previously taken CT images, and the AI will analyze them to estimate risk. The goal is to improve early detection in this high-risk group.

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 could lead to a more accurate, AI-based screening tool to catch lung cancer earlier in high-risk individuals.
What could go wrong
This is an early-stage study (not yet recruiting) that only tests the AI's prediction accuracy, not whether it improves health outcomes. The AI may not work as well in this specific group.

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 2,250 people

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

Started

Jun 2026

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.

Who is studied

This study will enroll individuals who have a family history of lung cancer (≥1 first-degree relative or ≥2 second-degree relatives).

Ages

18 years and older

Sex

Anyone

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: * ≥18 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) * Willing to provide images from at least one previously obtained CT Chest scan, if available. Exclusion Criteria: \- None

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Conditions

The condition(s) this trial relates to.

lung neoplasm

As listed by the trial registrant

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

Family history of lung cancer

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

    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

  • Massachusetts General Hospital

    RECRUITING

    Boston, Massachusetts, 02114, United States

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