Artificial Intelligence and Positron Emission Tomography Imaging Workflow:: Technologists' Perspective

Cheryl Beegle; Navid Hasani; Roberto Maass-Moreno; Babak Saboury; Eliot Siegel

doi:10.1016/j.cpet.2021.09.008

Artificial Intelligence and Positron Emission Tomography Imaging Workflow:: Technologists' Perspective

PET Clin. 2022 Jan;17(1):31-39. doi: 10.1016/j.cpet.2021.09.008.

Authors

Cheryl Beegle¹, Navid Hasani², Roberto Maass-Moreno¹, Babak Saboury³, Eliot Siegel⁴

Affiliations

¹ Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA.
² 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.
³ Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore Country, Baltimore, MD, USA; Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA. Electronic address: babak.saboury@nih.gov.
⁴ Department of Radiology and Nuclear Medicine, University of Maryland Medical Center, 655 W. Baltimore Street, Baltimore, MD 21201, USA. Electronic address: Esiegel@umaryland.edu.

Abstract

Artificial intelligence (AI) can enhance the efficiency of medical imaging quality control and clinical documentation, provide clinical decision support, and increase image acquisition and processing quality. A clear understanding of the basic tenets of these technologies and their impact will enable nuclear medicine technologists to train for performing advanced imaging tasks. AI-enabled medical devices' anticipated role and impact on routine nuclear medicine workflow (scheduling, quality control, check-in, radiotracer injection, waiting room, image planning, image acquisition, image post-processing) is reviewed in this article. With the assistance of AI, newly compiled patient imaging data can be customized to encompass personalized risk assessments of patients' disease burden, along with the development of individualized treatment plans. Nuclear medicine technologists will continue to play a crucial role on the medical team, collaborating with patients and radiologists to improve each patient's imaging experience and supervising the performance of integrated AI applications.

Keywords: Artificial intelligence; Imaging workflow; Medical imaging; Nuclear medicine technologists.

Publication types

Review

MeSH terms

Artificial Intelligence*
Humans
Nuclear Medicine*
Positron-Emission Tomography
Workflow

Grants and funding

Z99 CL999999/ImNIH/Intramural NIH HHS/United States