Abstract DICOM image pseudonymization is an effective measure to protect patient privacy and ensure compliance with the GDPR. However, no standardized methods guarantee the irreversible anonymization of DICOM images or provide evidence on the robustness of these procedures. Organizations such as NEMA propose pseudonymization profiles for DICOM metadata, but the risk to data protection is assumed by the entity responsible for pseudonymization, as the potential privacy risks associated with their use cannot be accurately assessed. In the Re-identification Challenge, the selected 68 participants were tasked with re-identifying 38 pseudonymized DICOM studies from multiple European acquisition sites, modalities and anatomical regions. The data were pseudonymized using the pseudonymization profiles developed in ChAImeleon1 and ProCancer-I2 European AI4HI projects. No participants were able to trace back the identity of the patients, demonstrating the effectiveness of these pseudonymization profiles. Despite minor vulnerabilities identified in areas such as free-text metadata, 3D reconstructions, and usability limitations, no successful re-identification occurred—even with monetary rewards offered to participants. Similar content being viewed by others Data availability The dataset used in this study is publicly available in Zenodo with https://doi.org/10.5281/zenodo.170346748. Code availability Several software tools were used during the Re-identification Challenge. The dataset8 was pseudonymized using the CTP app (version released on 2023-11-04) with project-specific configurations. The CTP app is available in https://github.com/johnperry/CTP/raw/master/products/CTP-installer.jar and its documentation in https://mircwiki.rsna.org/index.php?title=MIRC_CTP. Moreover, the software used to apply de-facing in the dataset8 is available in https://www.nitrc.org/projects/mri_reface. References Bonmatí, L. M. et al. CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools. Front. Oncol. 12, 742701. https://doi.org/10.3389/fonc.2022.742701 (2022). ProCancer-I Project. An AI Platform integrating imaging data and health records for precision medicine in cancer management. https://www.procancer-i.eu/ (2025). Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the