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Deep Learning Using Chest X-Rays to Identify High Risk Patients for Lung Cancer Screening CT

Recruiting

Deep Learning Using Routine Chest X-Rays and Electronic Medical Record Data to Identify High Risk Patients for Lung Cancer Screening CT

Who can join

Ages 50 to 77 · All sexes

Full eligibility criteria
Major 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.

About the study

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. Intervention and non-intervention arms will be compared to determine if lung cancer screening CT participation increases.

Individuals who are considered high-risk by the tool, but who do not meet the Medicare/USPSTF pack-year or quit-date lung screening eligibility criteria may be offered research lung screening CT.

What is being tested

Sponsor: Massachusetts General Hospital · Participants: 1,500 · Started: May 20, 2025

Contact the study team

Official record on ClinicalTrials.gov — NCT06910956

Locations in the U.S.

MassachusettsMassachusetts General Hospital, Boston

Conditions

From ClinicalTrials.gov, data retrieved Sep 30, 2026. Each study sets its own eligibility; the study team decides who can join.