Deep Learning Using Chest X-Rays to Identify High Risk Patients for Lung Cancer Screening CT
Purpose
The goal of this clinical trial is to evaluate whether an AI tool that alerts providers to patients at high 6-year risk of lung cancer based on their chest x-ray images will improve lung cancer screening CT participation. The main question it aims to answer is: Does the AI tool improve lung cancer screening CT participation at 6 months after the baseline outpatient visit The intervention is an alert to the provider to discuss lung cancer screening CT eligibility, for patients considered at high risk of lung cancer based on CXR-LC AI tool. If there is a comparison group: Researchers will compare intervention and non-intervention arms to determine if lung cancer screen CT participation increases.
Conditions
- Lung Cancer
- Health Screening
- Early Cancer Detection
- Deep Learning
Eligibility
- Eligible Ages
- Between 50 Years and 77 Years
- Eligible Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- Scheduled outpatient appointment with participating provider. - 50- to 77-year-old who currently or formerly smoked, to include persons potentially eligible for lung screening based on Medicare guidelines. - Recent (within 2 years) PA chest radiograph.
Exclusion Criteria
• History or signs/symptoms of lung cancer. Recent (within 2 years) chest CT. Clinical indication for chest CT beyond lung cancer screening.
Study Design
- Phase
- N/A
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Parallel Assignment
- Primary Purpose
- Screening
- Masking
- Double (Participant, Care Provider)
Arm Groups
| Arm | Description | Assigned Intervention |
|---|---|---|
|
Experimental Intervention |
|
|
|
No Intervention Non-Intervention |
|
Recruiting Locations
Boston, Massachusetts 02114
More Details
- Status
- Recruiting
- Sponsor
- Massachusetts General Hospital