The scope of this project remains flexible, but initially we plan a literature review. The types of image files will be reviewed (X-rays, (f)MRIs, CT scans, etc.), their formats (DICOM, NIfTI, etc.), their positions (limbs, heads, organs, etc.) and all associated metadata. There will also be a discussion on data handling, storage and transfer. Any existing guidance and repositories will be reviewed. We will then focus on use cases that will have the most impact based on interest and complexity. Any use cases being presented will be in the context of a request alongside clinical data, in keeping with the main drivers behind the Data Transparency Working Group. There will be a strong focus on processing metadata associated with images as that is where the strengths of the Working Group lie (processing and anonymising data) and where most of the risk lies in the sharing of images.
In recent years, there has been a growing demand for different data types beyond clinical trial data; the scope of data sharing requests has expanded to reflect this. In particular, we have seen more requests for sharing images and related metadata. One of the major challenges to image sharing is the complexity of medical images, which can include a range of modalities (X-rays, MRIs, CT scans, etc.) in a variety of formats (DICOM, NIfTI, etc.) and their associated metadata containing sensitive information.
This subgroup aims to review the current literature for image sharing and work together with stakeholders across the industry to provide data transparency guidance for the data types most in demand.
This project will provide a forum to discuss image data in the context of data transparency. Currently there is limited guidance available and companies across the industry approach requests for image data on an ad hoc basis. This project will summarise the available literature and identify gaps that will be addressed by future phases of this project.
Objectives & Deliverables
|Project kick off
|Complete a review of the image data sharing domain
|Focus on use cases (e.g. X-rays, DICOM) thereafter and spawn sub-projects subject to demand
|Have guidance on how to de-identify images and associated data in the context of data transparency