LEGACY: Lung Cancer Screening in Individuals With a Lung Cancer Family History-Protocol B
Status: Recruiting
Location: See location...
Intervention Type: Diagnostic test, Other
Study Type: Observational
SUMMARY
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.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
View:
• ≥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.
Locations
United States
Massachusetts
Massachusetts General Hospital
RECRUITING
Boston
Contact Information
Primary
Allison Chang, MD
aechang@mgb.org
617-724-4000
Time Frame
Start Date: 2026-06-17
Estimated Completion Date: 2035-12-31
Participants
Target number of participants: 2250
Treatments
Retrospective CT scan
Participants will contribute images and corresponding radiology reports from at least one retrospective CT chest scan.
Related Therapeutic Areas
Sponsors
Leads: Massachusetts General Hospital