Secure-DICOM-Uploader: A platform for anonymising and transferring imaging data from hospital sites to remote repositories
Deborah Beasley, Björn Eiben, Steven Doran, Jeff Darcy, James Petts, Reeya Patel, Matthew T. White, Emily Miles, Jamie R. McClelland · UCL Discovery (University College London) · 2019
For a large multi-site project, imaging (DICOM and other formats) and non-imaging data from different hospitals are anonymised and sent to a central repository for analysis. To provide secure data transfer from different hospital sites to a central repository, we have developed a user-friendly solution based on software components designed for and established in large-scale clinical trials. This was designed with the primary purpose of Quality Assurance for radiotherapy clinical trials, however it can be used for general multi-center clinical trials and research projects. XNAT is a platform that provides for easy data management, image viewing and synchronisation of data. We have developed a customised XNAT-based workflow and placed this within a Docker service for easy distribution, reliability and control. The Uploader consists of two separate XNAT servers running within the same Docker service, one hosting non-anonymised data, the other anonymised. DICOM images are pushed from PACS or placed in a network folder which is then automatically imported into the non-anonymised XNAT server. The local user can log into the XNAT server and view session details and visualise the images via the OHIF (Open Health Imaging Foundation) viewer. Data is anonymised either automatically, where subject and session IDs are generated using hashing, or manually assigned for clinical trials. Clinical Trial protocols are used to ensure data conforms to expectations (ROI labels, structures) before anonymisation. When data is anonymised, a link is created between anonymised and identifiable data to ensure all data can be identified by the clinical trial management. The Secure DICOM Uploader greatly improves the experience and reliability of data transfer for clinical research. The user-friendly software requires minimal training while providing a number of checks to prevent identifiable information being transferred. It is planned to distribute the software for upcoming clinical trials.