Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development

Tyler J Bradshaw; Ronald Boellaard; Joyita Dutta; Abhinav K Jha; Paul Jacobs; Quanzheng Li; Chi Liu; Arkadiusz Sitek; Babak Saboury; Peter J H Scott; Piotr J Slomka; John J Sunderland; Richard L Wahl; Fereshteh Yousefirizi; Sven Zuehlsdorff; Arman Rahmim; Irène Buvat

doi:10.2967/jnumed.121.262567

Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development

J Nucl Med. 2022 Apr;63(4):500-510. doi: 10.2967/jnumed.121.262567. Epub 2021 Nov 5.

Authors

Tyler J Bradshaw¹, Ronald Boellaard², Joyita Dutta³, Abhinav K Jha⁴, Paul Jacobs⁵, Quanzheng Li⁶, Chi Liu⁷, Arkadiusz Sitek⁸, Babak Saboury⁹, Peter J H Scott¹⁰, Piotr J Slomka¹¹, John J Sunderland¹², Richard L Wahl¹³, Fereshteh Yousefirizi¹⁴, Sven Zuehlsdorff¹⁵, Arman Rahmim¹⁶, Irène Buvat¹⁷

Affiliations

¹ Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin; tbradshaw@wisc.edu.
² Department of Radiology and Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, The Netherlands.
³ Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, Massachusetts.
⁴ Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri.
⁵ MIM Software Inc., Cleveland, Ohio.
⁶ Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
⁷ Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut.
⁸ Sano Centre for Computational Medicine, Kraków, Poland.
⁹ Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland.
¹⁰ Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan.
¹¹ Department of Imaging, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, California.
¹² Departments of Radiology and Physics, University of Iowa, Iowa City, Iowa.
¹³ Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri.
¹⁴ Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, British Columbia, Canada.
¹⁵ Siemens Medical Solutions USA, Inc., Hoffman Estates, Illinois.
¹⁶ Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada; and.
¹⁷ Institut Curie, Université PSL, INSERM, Université Paris-Saclay, Orsay, France.

Abstract

The nuclear medicine field has seen a rapid expansion of academic and commercial interest in developing artificial intelligence (AI) algorithms. Users and developers can avoid some of the pitfalls of AI by recognizing and following best practices in AI algorithm development. In this article, recommendations on technical best practices for developing AI algorithms in nuclear medicine are provided, beginning with general recommendations and then continuing with descriptions of how one might practice these principles for specific topics within nuclear medicine. This report was produced by the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging.

Keywords: algorithm; artificial intelligence; best practices; computer/PACS; research methods; statistics.

MeSH terms

Algorithms
Artificial Intelligence*
Molecular Imaging
Nuclear Medicine*
Radionuclide Imaging

Abstract

MeSH terms

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