Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-24 @ 2:38 PM
Ignite Modification Date:
2025-12-24 @ 2:38 PM
NCT ID:
NCT07280559
Brief 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.
Study:
NCT07280559
Study Brief:
Protocol Section:
NCT07280559