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Research ArticleClinical Investigation

Machine Learning with 18F-Sodium Fluoride PET and Quantitative Plaque Analysis on CT Angiography for the Future Risk of Myocardial Infarction

Jacek Kwiecinski, Evangelos Tzolos, Mohammed N. Meah, Sebastien Cadet, Philip D. Adamson, Kajetan Grodecki, Nikhil V. Joshi, Alastair J. Moss, Michelle C. Williams, Edwin J.R. van Beek, Daniel S. Berman, David E. Newby, Damini Dey, Marc R. Dweck and Piotr J. Slomka
Journal of Nuclear Medicine January 2022, 63 (1) 158-165; DOI: https://doi.org/10.2967/jnumed.121.262283
Jacek Kwiecinski
1Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California;
1Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California;
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Evangelos Tzolos
1Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California;
4BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom;
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Mohammed N. Meah
4BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom;
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Sebastien Cadet
3Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California;
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Philip D. Adamson
5Christchurch Heart Institute, University of Otago, Christchurch, New Zealand;
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Kajetan Grodecki
6Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;
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Nikhil V. Joshi
7Bristol Heart Institute, University of Bristol, United Kingdom; and
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Alastair J. Moss
4BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom;
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Michelle C. Williams
4BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom;
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Edwin J.R. van Beek
4BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom;
8Edinburgh Imaging, Queens Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
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Daniel S. Berman
3Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California;
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David E. Newby
4BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom;
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Damini Dey
6Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;
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Marc R. Dweck
4BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom;
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Piotr J. Slomka
1Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California;
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Article Information

vol. 63 no. 1 158-165
DOI 
https://doi.org/10.2967/jnumed.121.262283
PubMed 
33893193

Published By 
Society of Nuclear Medicine
Print ISSN 
0161-5505
Online ISSN 
2159-662X
History 
  • Received for publication March 11, 2021
  • Revision received April 1, 2021
  • Published online January 3, 2022.

Article Versions

  • previous version (April 23, 2021 - 13:46).
  • You are viewing the most recent version of this article.
Copyright & Usage 
© 2022 by the Society of Nuclear Medicine and Molecular Imaging.

Author Information

  1. Jacek Kwiecinski1,2,
  2. Evangelos Tzolos3,4,
  3. Mohammed N. Meah4,
  4. Sebastien Cadet3,
  5. Philip D. Adamson5,
  6. Kajetan Grodecki6,
  7. Nikhil V. Joshi7,
  8. Alastair J. Moss4,
  9. Michelle C. Williams4,
  10. Edwin J.R. van Beek4,8,
  11. Daniel S. Berman3,
  12. David E. Newby4,
  13. Damini Dey6,
  14. Marc R. Dweck4 and
  15. Piotr J. Slomka1
  1. 1Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California;
  2. 2Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland;
  3. 3Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California;
  4. 4BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom;
  5. 5Christchurch Heart Institute, University of Otago, Christchurch, New Zealand;
  6. 6Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;
  7. 7Bristol Heart Institute, University of Bristol, United Kingdom; and
  8. 8Edinburgh Imaging, Queens Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
  1. For correspondence or reprints, contact Piotr J. Slomka (piotr.slomka{at}cshs.org).
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Journal of Nuclear Medicine: 63 (1)
Journal of Nuclear Medicine
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January 1, 2022
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Machine Learning with 18F-Sodium Fluoride PET and Quantitative Plaque Analysis on CT Angiography for the Future Risk of Myocardial Infarction
Jacek Kwiecinski, Evangelos Tzolos, Mohammed N. Meah, Sebastien Cadet, Philip D. Adamson, Kajetan Grodecki, Nikhil V. Joshi, Alastair J. Moss, Michelle C. Williams, Edwin J.R. van Beek, Daniel S. Berman, David E. Newby, Damini Dey, Marc R. Dweck, Piotr J. Slomka
Journal of Nuclear Medicine Jan 2022, 63 (1) 158-165; DOI: 10.2967/jnumed.121.262283

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Machine Learning with 18F-Sodium Fluoride PET and Quantitative Plaque Analysis on CT Angiography for the Future Risk of Myocardial Infarction
Jacek Kwiecinski, Evangelos Tzolos, Mohammed N. Meah, Sebastien Cadet, Philip D. Adamson, Kajetan Grodecki, Nikhil V. Joshi, Alastair J. Moss, Michelle C. Williams, Edwin J.R. van Beek, Daniel S. Berman, David E. Newby, Damini Dey, Marc R. Dweck, Piotr J. Slomka
Journal of Nuclear Medicine Jan 2022, 63 (1) 158-165; DOI: 10.2967/jnumed.121.262283
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