LEGACY: Lung Cancer Screening in Individuals With a Lung Cancer Family History-Protocol B
Start Date
6/17/2026
Completion Date
12/31/2035
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.
Detailed Description
This is a non-therapeutic study that will enroll individuals who have a family history of lung cancer. During the study, participants will provide questionnaire responses regarding their personal medical history, family lung cancer history, and exposures along with contributing images from at least one previously obtained CT chest scan. The images and data collected will be analyzed by an image-based deep learning model (Sybil). Sybil is a type of artificial intelligence model that has been shown to accurately predict individuals' future risk of lung cancer based solely on images from a CT Chest scan, but it is unknown if it works well in people with a family history of lung cancer. It is expected that 2,250 will take part in this research study.
Eligibility Criteria
Age Range: 18 years to No maximum
Interventions
CT scan
Sybil
Conditions
Locations
Massachusetts General Hospital
Boston, Massachusetts 02114
United States