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The scalable architecture of XNAT and its ability to support imaging research protocols in ways that simple PACS databases cannot have led institutions to use our platform in a number of different ways. Here are four prime examples:
XNAT is the foundation for the collection and dissemination of data for the Human Connectome Project, powering the ConnectomeDB application. Users of ConnectomeDB are downloading more than two petabytes of HCP data each year. Moving forward, XNAT will be the backbone of the Connectome Coordination Facility, distributing data for a series of related connectome research studies around the world.
David Gutman at the Center for Comprehensive Informatics at Emory University is running XNAT inside a virtual machine with a desktop RAID system for file storage.
This simple but powerful implementation of XNAT empowers Dr. Gutman and his research assistants to explore brain connectivity as it relates to a number of clinically diagnosed conditions, such as PTSD, across hundreds of subjects.
Mark Scully at the Institute for Clinical and Translational Science at the University of Iowa is part of a team of people using XNAT to be the centralized, canonical data store for the PREDICT-HD project.
This project, which studies the effects of Huntington's Disease, has been ongoing for nearly a decade, but is only now benefitting from having a formal system for each site to collect, store or organize their study data. Using XNAT has allowed project managers to create and enforce data management policies that have become integral to their project management workflows. It has also provided new capabilities for searching and reporting across the entire project that frankly did not exist before this XNAT was installed.
Adam Harding at the Institute for Clinical and Translational Science at the University of Iowa is a part of the team that helps manage the University's institution-wide repository for imaging research projects. This large-scale implementation currently supports more than 125 projects, 3,900 stored image sessions, and 2.5 terabytes of data. And the ICTS-managed enterprise-class storage system is configured to scale economically to support ever-growing demand.
Unlike the PREDICT-HD project, which wields its power as a centralized repository to enforce strict data management policies, this XNAT functions as a centralized provider of secure data access and widely-used research tools. Each investigator has access to XNAT's research services, while being able to create and enforce policies and data organization on a per-project basis.