Dynamic consent framework for low-dose CT scan lung cancer screening: autonomy, privacy, ethical data management
Jui-Chu Lin1,2, Wesley Wei-Wen Hsiao3, Jen-Wei Hu4
1Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC.
Frontiers in Digital Health
|June 26, 2026
Summary
This study introduces a blockchain-based dynamic consent system for lung cancer screening, enhancing data security and participant control. The AI-integrated framework supports precision health and biobank data use in Taiwan.
Area of Science:
- Health Informatics
- Blockchain Technology
- Artificial Intelligence
Background:
- Lung cancer screening programs generate sensitive data requiring robust consent management.
- Traditional consent models struggle with dynamic data use and participant engagement.
- Integrating AI and biobank data necessitates secure and transparent data governance.
Purpose of the Study:
- To develop and implement a blockchain-based dynamic consent framework.
- To support Low-Dose Computed Tomography (LDCT) lung cancer screening and biobank data utilization.
- To enhance participant control and data governance in Taoyuan, Taiwan.
Main Methods:
- Designed a Web 3.0 dynamic consent platform for digital preference management.
- Secured consent records via blockchain hash registration.
- Stored de-identified data in ISO 27001-compliant infrastructure with AI-assisted governance.
Main Results:
- Presented a conceptual framework and implementation design for blockchain-based dynamic consent.
- Enabled real-time consent modification and strengthened data traceability.
- Piloting the framework within the Taoyuan Expanded Lung Cancer Screening Program for 15,000 participants.
Conclusions:
- Blockchain-enabled dynamic consent addresses legal, ethical, and governance challenges in LDCT screening.
- The model supports precision health initiatives.
- Provides a scalable pathway for integrating AI and biobank data into public health programs.
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