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Using FastFile as a large file sharing, management and replication hub for PET/CT scans for the PREDICT study (a global TB treatment research protocol)

Wednesday, September 13, 2017 — Poster Session I

12:00 p.m. – 1:30 p.m.
FAES Terrace
NIAID
RSCHSUPP-14

Authors

  • D Ireland
  • M Duvenhage
  • M Hurst
  • M Holdsworth
  • F Appiah
  • R Chen
  • C Whalen
  • M Tartakovsky

Abstract

The Office of Cyber Infrastructure and Computational Biology at the National Institute of Allergy and Infectious Diseases is working on a protocol leveraging new medical and informatics technologies in ways that are shifting data managers into the role of systems integrators. The Tuberculosis Research Section of the NIAID challenged our international clinical data management program with a multi-country study that required a method to control the many different data flows specifically with regard to large PET/CT scans. This study involved collecting data from clinical research sites around the world, and redistributing that data for review. One challenge presented by the protocol was ensuring efficient transfers of large PET/CT files from the sites local PET/CT scanning hub to various Image reviewers situated around the world. Requirements sought to create a central repository for PET/CT scans, automate the upload transfer procedure for the study team, replicate the PET/CT scans to various Image reviewers based on a randomization schema as well as ensuring the PET/CT scans are automatically downloaded to the local Image reviewers machines. The solution not only eliminated the process of manually transferring files to various image reviewers by automation, but also eliminated the manual upload of PET/CT scans for the study team as well as ensuring automated assignment of PET/CT scans to the Image reviewers based on a randomization schema. Overall, FastFile allowed the automation of the PET/CT data transfer from the study team member’s local machines, via the NIID FastFile network to various local machines of the Image reviewers.

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