Artificial Intelligence in Medical Imaging and its Impact on the Rare Disease Community: Threats, Challenges and Opportunities.

Journal: PET clinics
Published Date: Jan 1, 2022

Abstract

Almost 1 in 10 individuals can suffer from one of many rare diseases (RDs). The average time to diagnosis for an RD patient is as high as 7 years. Artificial intelligence (AI)-based positron emission tomography (PET), if implemented appropriately, has tremendous potential to advance the diagnosis of RDs. Patient advocacy groups must be active stakeholders in the AI ecosystem if we are to avoid potential issues related to the implementation of AI into health care. AI medical devices must not only be RD-aware at each stage of their conceptualization and life cycle but also should be trained on diverse and augmented datasets representative of the end-user population including RDs. Inability to do so leads to potential harm and unsustainable deployment of AI-based medical devices (AIMDs) into clinical practice.

Authors

  • Navid Hasani
    Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA; University of Queensland Faculty of Medicine, Ochsner Clinical School, New Orleans, LA 70121, USA.
  • Faraz Farhadi
    Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD.
  • Michael A Morris
    Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD, USA; Institute for Data Science, Department of Diagnostic Radiology and Nuclear Medicine - University of Miami Miller School of Medicine, Miami, FL, USA.
  • Moozhan Nikpanah
    Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10, 9000 Rockville Pike, Bethesda, MD 20892, USA.
  • Arman Rhamim
    Department of Radiology, BC Cancer Research Institute, University of British Columbia, 675 West 10th Avenue, Vancouver, British Columbia, V5Z 1L3, Canada; Department of Physics, BC cancer Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.
  • Yanji Xu
    Office of Rare Diseases Research, National Center for Advancing Translational Sciences, National Institutes of Health (NIH), Bethesda, MD 20892, USA.
  • Anne Pariser
    Office of Rare Disease Research, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Bethesda, MD, 20892, USA.
  • Michael T Collins
  • Ronald M Summers
    National Institutes of Health, Clinical Center, Radiology and Imaging Sciences, 10 Center Drive, Bethesda, MD 20892, USA.
  • Elizabeth Jones
    Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.
  • Eliot Siegel
    University of Maryland School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, 504 E. Fort Ave Baltimore, MD 21230.
  • Babak Saboury
    IBM Research, Almaden, San Jose, California.

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