Skip to main content

Main menu

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Journal of Nuclear Medicine
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Journal of Nuclear Medicine

Advanced Search

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • View or Listen to JNM Podcast
  • Visit JNM on Facebook
  • Join JNM on LinkedIn
  • Follow JNM on Twitter
  • Subscribe to our RSS feeds
OtherState-of-the-Art (Invitation Only)

Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE guidelines)

Abhinav K. Jha, Tyler J. Bradshaw, Irène Buvat, Mathieu Hatt, Prabhat KC, Chi Liu, Nancy F. Obuchowski, Babak Saboury, Piotr J. Slomka, John J. Sunderland, Richard L. Wahl, Zitong Yu, Sven Zuehlsdorff, Arman Rahmim and Ronald Boellaard
Journal of Nuclear Medicine May 2022, jnumed.121.263239; DOI: https://doi.org/10.2967/jnumed.121.263239
Abhinav K. Jha
1 Mallinckrodt Institute of Radiology, Washington University in St. Louis, United States;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tyler J. Bradshaw
2 Department of Radiology, University of Wisconsin-Madison;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Irène Buvat
3 LITO, Institut Curie, Université PSL, U1288 Inserm;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mathieu Hatt
4 LaTiM, INSERM, UMR 1101, Univ Brest;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Prabhat KC
5 Center for Devices and Radiological Health, Food and Drug Administration;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chi Liu
6 Department of Radiology and Biomedical Imaging, Yale University;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nancy F. Obuchowski
7 Quantitative Health Sciences, Cleveland Clinic;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Babak Saboury
8 Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Piotr J. Slomka
9 Department of Imaging, Medicine, and Cardiology, Cedars-Sinai Medical Center;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John J. Sunderland
10 Departments of Radiology and Physics, University of Iowa;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Richard L. Wahl
1 Mallinckrodt Institute of Radiology, Washington University in St. Louis, United States;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zitong Yu
11 Department of Biomedical Engineering, Washington University in St. Louis;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sven Zuehlsdorff
12 Siemens Medical Solutions USA, Inc., Hoffman Estates;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Arman Rahmim
13 Departments of Radiology and Physics, University of British Columbia;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ronald Boellaard
14 Dept of Radiology & Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centers
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF
Loading

Article Information

jnumed.121.263239
DOI 
https://doi.org/10.2967/jnumed.121.263239
PubMed 
35618476

Published By 
Society of Nuclear Medicine
Print ISSN 
0161-5505
Online ISSN 
2159-662X
History 
  • Published online May 26, 2022.

Article Versions

  • You are currently viewing a previous version of this article (May 26, 2022 - 12:58).
  • View the most recent version of this article
Copyright & Usage 
Copyright © 2022 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Author Information

  1. Abhinav K. Jha1,
  2. Tyler J. Bradshaw2,
  3. Irène Buvat3,
  4. Mathieu Hatt4,
  5. Prabhat KC5,
  6. Chi Liu6,
  7. Nancy F. Obuchowski7,
  8. Babak Saboury8,
  9. Piotr J. Slomka9,
  10. John J. Sunderland10,
  11. Richard L. Wahl1,
  12. Zitong Yu11,
  13. Sven Zuehlsdorff12,
  14. Arman Rahmim13 and
  15. Ronald Boellaard14
  1. 1 Mallinckrodt Institute of Radiology, Washington University in St. Louis, United States;
  2. 2 Department of Radiology, University of Wisconsin-Madison;
  3. 3 LITO, Institut Curie, Université PSL, U1288 Inserm;
  4. 4 LaTiM, INSERM, UMR 1101, Univ Brest;
  5. 5 Center for Devices and Radiological Health, Food and Drug Administration;
  6. 6 Department of Radiology and Biomedical Imaging, Yale University;
  7. 7 Quantitative Health Sciences, Cleveland Clinic;
  8. 8 Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health;
  9. 9 Department of Imaging, Medicine, and Cardiology, Cedars-Sinai Medical Center;
  10. 10 Departments of Radiology and Physics, University of Iowa;
  11. 11 Department of Biomedical Engineering, Washington University in St. Louis;
  12. 12 Siemens Medical Solutions USA, Inc., Hoffman Estates;
  13. 13 Departments of Radiology and Physics, University of British Columbia;
  14. 14 Dept of Radiology & Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centers
  1. For correspondence or reprints contact: Abhinav K. Jha, Mallinckrodt Institute of Radiology, Washington University in St. Louis, 510 South Kingshighway Boulevard,, St. Louis, Missouri 63110, United States. E-mail: a.jha@wustl.edu

Statistics from Altmetric.com

Cited By...

  • 52 Citations
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII
    Burak Kocak, Bettina Baessler, Spyridon Bakas, Renato Cuocolo, Andrey Fedorov, Lena Maier-Hein, Nathaniel Mercaldo, Henning Müller, Fanny Orlhac, Daniel Pinto dos Santos, Arnaldo Stanzione, Lorenzo Ugga, Alex Zwanenburg
    Insights into Imaging 2023 14 1
  • METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
    Burak Kocak, Tugba Akinci D’Antonoli, Nathaniel Mercaldo, Angel Alberich-Bayarri, Bettina Baessler, Ilaria Ambrosini, Anna E. Andreychenko, Spyridon Bakas, Regina G. H. Beets-Tan, Keno Bressem, Irene Buvat, Roberto Cannella, Luca Alessandro Cappellini, Armando Ugo Cavallo, Leonid L. Chepelev, Linda Chi Hang Chu, Aydin Demircioglu, Nandita M. deSouza, Matthias Dietzel, Salvatore Claudio Fanni, Andrey Fedorov, Laure S. Fournier, Valentina Giannini, Rossano Girometti, Kevin B. W. Groot Lipman, Georgios Kalarakis, Brendan S. Kelly, Michail E. Klontzas, Dow-Mu Koh, Elmar Kotter, Ho Yun Lee, Mario Maas, Luis Marti-Bonmati, Henning Müller, Nancy Obuchowski, Fanny Orlhac, Nikolaos Papanikolaou, Ekaterina Petrash, Elisabeth Pfaehler, Daniel Pinto dos Santos, Andrea Ponsiglione, Sebastià Sabater, Francesco Sardanelli, Philipp Seeböck, Nanna M. Sijtsema, Arnaldo Stanzione, Alberto Traverso, Lorenzo Ugga, Martin Vallières, Lisanne V. van Dijk, Joost J. M. van Griethuysen, Robbert W. van Hamersvelt, Peter van Ooijen, Federica Vernuccio, Alan Wang, Stuart Williams, Jan Witowski, Zhongyi Zhang, Alex Zwanenburg, Renato Cuocolo
    Insights into Imaging 2024 15 1
  • Joint EANM/SNMMI guideline on radiomics in nuclear medicine
    M. Hatt, A. K. Krizsan, A. Rahmim, T. J. Bradshaw, P. F. Costa, A. Forgacs, R. Seifert, A. Zwanenburg, I. El Naqa, P. E. Kinahan, F. Tixier, A. K. Jha, D. Visvikis
    European Journal of Nuclear Medicine and Molecular Imaging 2023 50 2
  • A Guide to Cross-Validation for Artificial Intelligence in Medical Imaging
    Tyler J. Bradshaw, Zachary Huemann, Junjie Hu, Arman Rahmim
    Radiology: Artificial Intelligence 2023 5 4
  • 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, Peter J.H. Scott, Eliot Siegel, John J. Sunderland, Neeta Pandit-Taskar, Richard L. Wahl, Sven Zuehlsdorff, Arman Rahmim
    Journal of Nuclear Medicine 2023 64 2
  • Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review
    Yue Cai, Yu-Qing Cai, Li-Ying Tang, Yi-Han Wang, Mengchun Gong, Tian-Ci Jing, Hui-Jun Li, Jesse Li-Ling, Wei Hu, Zhihua Yin, Da-Xin Gong, Guang-Wei Zhang
    BMC Medicine 2024 22 1
  • Generative Adversarial Networks for Anomaly Detection in Biomedical Imaging: A Study on Seven Medical Image Datasets
    Marzieh Esmaeili, Amirhosein Toosi, Arash Roshanpoor, Vahid Changizi, Marjan Ghazisaeedi, Arman Rahmim, Mohammad Sabokrou
    IEEE Access 2023 11
  • Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance
    Jonathan Herington, Melissa D. McCradden, Kathleen Creel, Ronald Boellaard, Elizabeth C. Jones, Abhinav K. Jha, Arman Rahmim, Peter J.H. Scott, John J. Sunderland, Richard L. Wahl, Sven Zuehlsdorff, Babak Saboury
    Journal of Nuclear Medicine 2023 64 10
  • Need for objective task‐based evaluation of deep learning‐based denoising methods: A study in the context of myocardial perfusion SPECT
    Zitong Yu, Md Ashequr Rahman, Richard Laforest, Thomas H. Schindler, Robert J. Gropler, Richard L. Wahl, Barry A. Siegel, Abhinav K. Jha
    Medical Physics 2023 50 7
  • TMTV-Net: fully automated total metabolic tumor volume segmentation in lymphoma PET/CT images — a multi-center generalizability analysis
    Fereshteh Yousefirizi, Ivan S. Klyuzhin, Joo Hyun O, Sara Harsini, Xin Tie, Isaac Shiri, Muheon Shin, Changhee Lee, Steve Y. Cho, Tyler J. Bradshaw, Habib Zaidi, François Bénard, Laurie H. Sehn, Kerry J. Savage, Christian Steidl, Carlos F. Uribe, Arman Rahmim
    European Journal of Nuclear Medicine and Molecular Imaging 2024 51 7

Article usage

Article usage: May 2022 to April 2025

AbstractFullPdf
May 2022896052
Jun 202219010227
Jul 2022497088
Aug 2022347088
Sep 202212371088322
Oct 2022357380105
Nov 2022228172153
Dec 20226801252
Jan 20236953082
Feb 20236362562
Mar 202314440187
Apr 202315129182
May 202310224972
Jun 2023193308110
Jul 2023110302111
Aug 202394364100
Sep 202390310110
Oct 20238519499
Nov 202312422494
Dec 2023174124102
Jan 202412525996
Feb 202411926981
Mar 202410520798
Apr 202413737697
May 202417020798
Jun 202412818977
Jul 2024210253133
Aug 202416278797
Sep 20247617599
Oct 202490192139
Nov 202480152121
Dec 20246612693
Jan 202576150111
Feb 202510044895
Mar 202584201121
Apr 2025178349179
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine: 66 (5)
Journal of Nuclear Medicine
Vol. 66, Issue 5
May 1, 2025
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Complete Issue (PDF)
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Journal of Nuclear Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE guidelines)
(Your Name) has sent you a message from Journal of Nuclear Medicine
(Your Name) thought you would like to see the Journal of Nuclear Medicine web site.
Citation Tools
Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE guidelines)
Abhinav K. Jha, Tyler J. Bradshaw, Irène Buvat, Mathieu Hatt, Prabhat KC, Chi Liu, Nancy F. Obuchowski, Babak Saboury, Piotr J. Slomka, John J. Sunderland, Richard L. Wahl, Zitong Yu, Sven Zuehlsdorff, Arman Rahmim, Ronald Boellaard
Journal of Nuclear Medicine May 2022, jnumed.121.263239; DOI: 10.2967/jnumed.121.263239

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE guidelines)
Abhinav K. Jha, Tyler J. Bradshaw, Irène Buvat, Mathieu Hatt, Prabhat KC, Chi Liu, Nancy F. Obuchowski, Babak Saboury, Piotr J. Slomka, John J. Sunderland, Richard L. Wahl, Zitong Yu, Sven Zuehlsdorff, Arman Rahmim, Ronald Boellaard
Journal of Nuclear Medicine May 2022, jnumed.121.263239; DOI: 10.2967/jnumed.121.263239
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • Artificial Intelligence-Enhanced Perfusion Scoring Improves the Diagnostic Accuracy of Myocardial Perfusion Imaging
  • Is the Clinical Implementation of In-House Artificial Intelligence-Developed Algorithms Happening?
  • Large Language Models and Large Multimodal Models in Medical Imaging: A Primer for Physicians
  • Navigating the Future of Prostate Cancer Care: AI-Driven Imaging and Theranostics Through the Lens of RELAINCE
  • Is Automatic Tumor Segmentation on Whole-Body 18F-FDG PET Images a Clinical Reality?
  • Need for Objective Task-Based Evaluation of Image Segmentation Algorithms for Quantitative PET: A Study with ACRIN 6668/RTOG 0235 Multicenter Clinical Trial Data
  • Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation
  • Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance
  • An Investigation of Lesion Detection Accuracy for Artificial Intelligence-Based Denoising of Low-Dose 64Cu-DOTATATE PET Imaging in Patients with Neuroendocrine Neoplasms
  • An Investigation of Lesion Detection Accuracy for Artificial Intelligence-Based Denoising of Low-Dose 64Cu-DOTATATE PET Imaging in Patients with Neuroendocrine Neoplasms
  • Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem
  • Google Scholar

Similar Articles

Keywords

  • Image Processing
  • Image Reconstruction
  • PET
  • research methods
  • SPECT
  • artificial intelligence
  • Clinical task-based evaluation
  • Clinical utility
  • generalizability
  • Post-deployment monitoring
SNMMI

© 2025 SNMMI

Powered by HighWire