Privacy Risks in Radiology AI
https://www.rsna.org/news/2026/may/privacy-risks-in-radiology-ai
Publish Date: 2026-05-20 10:34:00
Source Domain: www.rsna.org
Practical Steps for Mitigating Privacy Risks
In his article, Dr. Klontzas and colleagues outline practical steps that radiologists and clinical institutions can take to mitigate privacy risks when using AI in medical imaging. “The first step is to carefully de-identify imaging data before sharing,” he said. “This includes removing patient identifiers from DICOM metadata and all potentially identifiable image features.”
Dr. Klontzas further recommends that data sharing follow established regulatory frameworks, such as the GDPR or HIPAA, and be supported by appropriate ethical approvals and data governance procedures. Institutions should also implement secure data management practices and carefully evaluate AI models for potential privacy risks before deployment.
“In essence, any models used in clinical settings need to be rigorously vetted in terms of privacy-related risk,” Dr. Klontzas noted.
Part of the Solution Too
Despite their potential to aggravate privacy concerns, AI models can serve as effective mitigation tools when deployed with appropriate safeguards. “AI can be an important part of the solution for detecting, monitoring and mitigating the privacy risks it creates,” Dr. Xiong said.
For instance, AI-based techniques can support the automated de-identification of imaging data by detecting and removing identifiable features such as facial structures in brain MRI scans. Likewise, generative models can create synthetic medical images, allowing researchers to develop and validate AI systems without directly sharing real patient data.
Privacy-preserving training strategies such as federated learning can support collaborative model development while limiting the transfer of sensitive data across institutions. Approaches like differential privacy and encryption-based methods have also been proposed to prevent models from revealing information about their training data.
Dr. Klontzas is quick to remind radiologists of…
