Comparing AI and human interpretation for lung cancer screening
Evaluation of AI-Assisted Versus Conventional Human Reading for Lung Cancer Screening in Community-Based Settings: A Randomized Controlled Trial
This study tests whether an AI system can read CT scans for lung cancer as well as human doctors do in community health centers.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 7294 (estimated) |
| Ages | 40 Years to 74 Years |
| Sex | All |
| Sponsor | The First Affiliated Hospital of Guangzhou Medical University Academic / other |
| Locations | 1 site (Guangzhou, Guangdong) |
| Trial ID | NCT06988579 on ClinicalTrials.gov |
What this trial studies
This clinical trial evaluates the effectiveness of an AI diagnostic system compared to human radiologists in interpreting CT scans for lung cancer screening in community health centers. The study involves randomized controlled methods where expert radiologists set reference standards, and an independent committee assesses cases from both AI-assisted and manual interpretations. Key metrics include diagnostic accuracy, operational efficiency, and cost-effectiveness, with discrepancies resolved by blinded analysts to ensure reliable results.
Who should consider this trial
Good fit: Ideal candidates are individuals aged 45-74 years who are permanent residents of the participating communities and have no prior history of lung cancer.
Not a fit: Patients with a confirmed diagnosis of lung cancer or severe comorbidities that contraindicate CT imaging will not benefit from this study.
Why it matters
Potential benefit: If successful, this study could enhance lung cancer detection rates and improve screening processes in community healthcare settings.
How similar studies have performed: Other studies have shown promise in using AI for medical imaging, but this specific evaluation in community health settings is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Aged 45-74 years 2. Permanent resident of participating study communities 3. No prior history of lung cancer and no lung cancer screening within the past 3 months 4. Able to comprehend and voluntarily sign informed consent, with willingness to participate in long-term follow-up Exclusion Criteria: 1. Individuals with a confirmed diagnosis of lung cancer 2. Those with severe comorbidities contraindicating CT imaging 3. Inability to understand study protocols or provide informed consent due to cognitive impairment 4. Concurrent participation in other clinical trials that may interfere with study outcomes 5. Unable to comply with follow-up requirements
Where this trial is running
Guangzhou, Guangdong
- the First Affiliated Hospital of Guangzhou Medical University, — Guangzhou, Guangdong, China (Recruiting)
Study contacts
- Study coordinator: Jianxing He
- Email: drjianxing.he@gmail.com
- Phone: +8618320729913
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.