Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem

Babak Saboury; Tyler Bradshaw; Ronald Boellaard; Irène Buvat; Joyita Dutta; Mathieu Hatt; Abhinav K Jha; Quanzheng Li; Chi Liu; Helena McMeekin; Michael A Morris; Neeta Pandit-Taskar; Peter J H Scott; Eliot Siegel; John J Sunderland; Richard L Wahl; Sven Zuehlsdorff; Arman Rahmim

doi:10.2967/jnumed.121.263703

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Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem

Journal article

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Peer reviewed

Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem

Babak Saboury, Tyler Bradshaw, Ronald Boellaard, Irène Buvat, Joyita Dutta, Mathieu Hatt, Abhinav K Jha, Quanzheng Li, Chi Liu, Helena McMeekin, …

The Journal of nuclear medicine (1978), Vol.64(2), pp.188-196

02/2023

DOI: 10.2967/jnumed.121.263703

PMCID: PMC9902852

PMID: 36522184

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Abstract

Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a dyad to a broader ecosystem of healthcare. With the emergence of artificial intelligence (AI) in medicine, the elements of trust must be revisited. We envision a roadmap for the establishment of trustworthy AI ecosystems in nuclear medicine. In this report, AI is contextualized in the history of technological revolutions. Opportunities for AI applications in nuclear medicine related to diagnosis, therapy and workflow efficiency, as well as emerging challenges and critical responsibilities are discussed. Establishing and maintaining leadership in AI requires a concerted effort to promote the rational and safe deployment of this innovative technology by engaging patients, nuclear medicine physicians, scientists, technologists, referring providers, among other stakeholders, while protecting our patients and society. This strategic plan is prepared by the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging (SNMMI).

Nuclear Medicine

Theranostic Digital Twin

Trustworthy

Ecosystem

Artificial intelligence

Computer/PACS

Other

Details

Title: Subtitle: Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem
Creators: Babak Saboury - National Institutes of Health
Tyler Bradshaw - University of Wisconsin–Madison
Ronald Boellaard - Dept of Radiology & Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centres
Irène Buvat - Université Paris Sciences et Lettres
Joyita Dutta - University of Massachusetts Lowell
Mathieu Hatt - Inserm
Abhinav K Jha - Washington University in St. Louis
Quanzheng Li - Harvard Medical School
Chi Liu - Yale University
Helena McMeekin - Barts Health NHS Trust
Michael A Morris - National Institutes of Health
Neeta Pandit-Taskar - Department of Radiology, Memorial Sloan Kettering Cancer, United States
Peter J H Scott - University of Michigan Medical School
Eliot Siegel - University of Maryland Medical Center
John J Sunderland - University of Iowa
Richard L Wahl - Washington University in St. Louis
Sven Zuehlsdorff - Siemens Medical Solutions USA, Inc., United States
Arman Rahmim - University of British Columbia
Resource Type: Journal article
Publication Details: The Journal of nuclear medicine (1978), Vol.64(2), pp.188-196
DOI: 10.2967/jnumed.121.263703
PMID: 36522184
PMCID: PMC9902852
NLM abbreviation: J Nucl Med
ISSN: 0161-5505
eISSN: 1535-5667
Language: English
Electronic publication date: 12/15/2022
Date published: 02/2023
Academic Unit: Radiology; Physics and Astronomy; Radiation Oncology
Record Identifier: 9984339150902771

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