Dynamic consent framework for low-dose CT scan lung cancer screening: autonomy, privacy, ethical data management.

Abstract

To develop and implement a blockchain-based dynamic consent framework integrated with artificial intelligence (AI) to support Low-Dose Computed Tomography (LDCT) lung cancer screening and biobank data utilization in Taoyuan, Taiwan. We designed a Web 3.0-based dynamic consent platform that enables participants in the Taoyuan Expanded Lung Cancer Screening Program to manage and update their consent preferences digitally. Consent records are secured via blockchain hash registration, while de-identified imaging and biobank data are stored in ISO 27001-compliant infrastructure. The framework incorporates AI-assisted risk assessment and governance mechanisms to ensure compliance with Taiwan's Personal Data Protection Act (PDPA). This paper presents a conceptual framework and implementation design for a blockchain-based dynamic consent system. The proposed architecture enables real-time consent modification, strengthens data traceability through blockchain hash registration, and improves transparency in data use. The framework is currently being piloted within the Taoyuan Expanded Lung Cancer Screening Program, targeting 15,000 enrolled participants. A blockchain-enabled dynamic consent system can address legal, ethical, and governance challenges in LDCT-based lung cancer screening programs. This model supports precision health initiatives and provides a scalable pathway for integrating AI and biobank data into public health programs.