XNAT Repository at the Institute of Cancer Research and the Royal Marsden

XNAT study setup meeting
The Royal Marsden's new Oak Cancer Centre
XNAT-OHIF viewer
PyCharm code editor
XNAT in MRI research
PET-CT image rendered in 3-D
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Connecting researchers to their data

We help cancer researchers curate, annotate and share clinical data with security and peace of mind.
We can deliver image processing at scale to power high-profile research studies.


What we do

What is XNAT?

Find out more about the XNAT platform and what it can do.

Clinical studies

Information about the studies the Repository supports

Our technology

Details about the cutting edge tools and technology we use

Repository docs

Information about how to use XNAT for one of your own studies

What we do for the NHS

Find out how XNAT is helping the Royal Marsden

The ICR/RM XNAT Repository works in close partnership with the Radiology Department of the Royal Marsden Hospital and its AI Imaging Hub to help deliver improvements to standard-of-care NHS imaging. We help clinical scientists investigate new imaging methodologies that have the potential to change the scans that are given to patients, in order to deliver better information to radiologists in the clinic.

Future work is likely to include image processing based on “deep learning”, a type of artificial intelligence, that can substantially reduce scan times.


Learn about the high-profile research studies powered by XNAT


Our Team Members

Simon Doran

XNAT project lead

[email protected]

James Darcy

Senior Software Engineer

[email protected]

Thesha Thavaraja

Data Manager (XNAT)

[email protected]

Alex Michie

Senior Software Engineer

[email protected]



Ensuring that patients trust us to put their interests at the heart of everything we do and to use their data safely is of paramount importance.
XNAT allows me to do just that.

Prof Christina Messiou

Consultant Radiologist, Royal Marsden; Team Leader, Institute of Cancer Research

Just saw your update on the XNAT discussion group. Thank you for taking the time to identify the issue – I really appreciate all the hard work you and your team are doing to integrate the OHIF viewer into XNAT. It has become incredibly integral to our workflow as I am sure for many other sites. I cannot stress strongly enough how grateful we are to have this feature available in XNAT.

Unsolicited message from XNAT user not previously connected to ICR/RMH or NCITA

Chidi Ugonna

Research Specialist,

Department of Biomedical Engineering, University of Arizona

We have been working with the outstanding XNAT development team at ICR since 2010 and their contribution to image viewing in XNAT has been transformative for the platform. Their expertise on all aspects of oncology imaging workflows has enabled XNAT to become a cornerstone application of the cancer research community.

Prof Dan Marcus

Co-creator of XNAT

CSO Flywheel LLC

Professor of Radiology, Washington University

We are here to support CIs.

Multicentre imaging trials

Connecting researchers to their data