Economic and Environmental Costs of Cloud Technologies for Medical Imaging and Radiology Artificial Intelligence.

Journal: Journal of the American College of Radiology : JACR
PMID: 38072221

Abstract

Radiology is on the verge of a technological revolution driven by artificial intelligence (including large language models), which requires robust computing and storage capabilities, often beyond the capacity of current non-cloud-based informatics systems. The cloud presents a potential solution for radiology, and we should weigh its economic and environmental implications. Recently, cloud technologies have become a cost-effective strategy by providing necessary infrastructure while reducing expenditures associated with hardware ownership, maintenance, and upgrades. Simultaneously, given the optimized energy consumption in modern cloud data centers, this transition is expected to reduce the environmental footprint of radiologic operations. The path to cloud integration comes with its own challenges, and radiology informatics leaders must consider elements such as cloud architectural choices, pricing, data security, uptime service agreements, user training and support, and broader interoperability. With the increasing importance of data-driven tools in radiology, understanding and navigating the cloud landscape will be essential for the future of radiology and its various stakeholders.

Authors

  • Florence X Doo
    Department of Radiology, Mount Sinai Health System, New York, New York.
  • Pranav Kulkarni
    Bioinformatics Facility, CECAD Research Center, University of Cologne, Cologne, Germany.
  • Eliot L Siegel
    University of Maryland School of Medicine, Baltimore, MD, USA. esiegel@umaryland.edu.
  • Michael Toland
    Senior Director of IT, Department of Diagnostic Imaging and Nuclear Medicine, University of Maryland Medical System, Baltimore, Maryland.
  • Paul H Yi
    The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland. Electronic address: Pyi10@jhmi.edu.
  • Ruth C Carlos
    Department of Radiology, University of Michigan, Ann Arbor, Michigan. Electronic address: rcarlos@med.umich.edu.
  • Vishwa S Parekh
    The Russell H. Morgan Department of Radiology and Radiological Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.

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