NCT07280559

Evaluation of AI-assisted LDCT Screening in Lung Cancer

Evaluation of AI Medical Software-assisted LDCT Interpretation in Lung Cancer Screening and Prognosis: a Randomized Controlled Trial

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 1,120 (estimated)
• Sponsor: Taipei Veterans General Hospital, Taiwan · Other Government
• Sex: All
• Age: 40 Years – 74 Years
• Healthy volunteers: Accepted

Summary

This multicenter pragmatic randomized controlled trial evaluates whether AI-assisted interpretation of low-dose CT (LDCT) improves lung cancer screening performance compared with standard reading. Eligible participants are randomized to AI-assisted or conventional interpretation. The study assesses diagnostic accuracy, efficiency, lung cancer incidence, mortality, recurrence, and smoking cessation outcomes. Results will inform the clinical utility and potential implementation of AI-assisted LDCT in routine screening practice.

Detailed description

Lung cancer is a leading cause of cancer-related mortality worldwide, and early detection is essential for improving survival. Low-dose computed tomography (LDCT) has been shown to reduce lung cancer mortality in high-risk populations, but image interpretation is time-consuming and may lead to overdiagnosis. Artificial intelligence (AI)-assisted diagnostic tools offer the potential to improve accuracy and efficiency in LDCT-based lung cancer screening, though challenges related to model adaptability, data heterogeneity, user trust, and regulatory compliance remain. This multicenter pragmatic randomized controlled trial evaluates the effectiveness of AI-assisted LDCT interpretation compared with standard interpretation. Eligible participants will be randomized to an AI-assisted arm or a standard-reading arm. Outcomes include diagnostic accuracy, efficiency, lung cancer incidence, lung cancer mortality, recurrence, and smoking cessation. The findings will provide evidence on the clinical utility of AI-assisted LDCT screening and support future implementation in routine practice and policy development.

Conditions

• Lung Cancer

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	AI-assisted Low-Dose CT Interpretation	Participants undergo low-dose computed tomography (LDCT) lung cancer screening. The images are first interpreted by AI-assisted software, which highlights suspicious nodules. Radiologists then review the AI outputs and generate the final report.

Timeline

• Start date: 2025-12-11
• Primary completion: 2027-12-31
• Completion: 2031-12-31
• First posted: 2025-12-12
• Last updated: 2025-12-12

Locations

1 site across 1 country: Taiwan