LEGACY: Lung Cancer Screening in Individuals With a Lung Cancer Family History-Protocol B
This research is being done to determine if an image-based deep learning model (Sybil) can accurately predict the likelihood of future lung cancer based on chest computed tomography (CT) imaging from individuals with a family history of lung cancer.
Checked against the public recordLast updated Aug 25, 2026 · Source: ClinicalTrials.gov
What this study is about
- Purpose
- Not specified
- Study type
- Observational
- Phase
- Not applicable
- Sponsor
- Massachusetts General Hospital
- Interventions being studied
- Diagnostic Test: CT scan; Other: Sybil
How this study is categorized
These labels come from structured fields and exact terms in the public record.
Who may be able to participate
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
Important: This is the sponsor’s public criteria, not a determination of eligibility. The study team must review your individual situation.
U.S. locations
- Massachusetts General HospitalBoston, Massachusetts
Source and freshness
Processed from ClinicalTrials.gov. Last public update: Aug 25, 2026. Always confirm current availability with the study team.