Artificial Intelligence–Enhanced Perfusion Scoring Improves the Diagnostic Accuracy of Myocardial Perfusion Imaging

Robert J.H. Miller; Paul Kavanagh; Mark Lemley; Joanna X. Liang; Tali Sharir; Andrew J. Einstein; Mathews B. Fish; Terrence D. Ruddy; Philipp A. Kaufmann; Albert J. Sinusas; Edward J. Miller; Timothy M. Bateman; Sharmila Dorbala; Marcelo Di Carli; Sean Hayes; John Friedman; Daniel S. Berman; Damini Dey; Piotr J. Slomka

doi:10.2967/jnumed.124.268079

Research ArticleClinical Investigation

Artificial Intelligence–Enhanced Perfusion Scoring Improves the Diagnostic Accuracy of Myocardial Perfusion Imaging

Robert J.H. Miller, Paul Kavanagh, Mark Lemley, Joanna X. Liang, Tali Sharir, Andrew J. Einstein, Mathews B. Fish, Terrence D. Ruddy, Philipp A. Kaufmann, Albert J. Sinusas, Edward J. Miller, Timothy M. Bateman, Sharmila Dorbala, Marcelo Di Carli, Sean Hayes, John Friedman, Daniel S. Berman, Damini Dey and Piotr J. Slomka

Journal of Nuclear Medicine February 2025, jnumed.124.268079; DOI: https://doi.org/10.2967/jnumed.124.268079

Robert J.H. Miller

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

2Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada;

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Paul Kavanagh

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

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Mark Lemley

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

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Joanna X. Liang

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

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Tali Sharir

3Department of Nuclear Cardiology, Assuta Medical Centers, Tel Aviv, Israel, and Ben Gurion University of the Negev, Beer Sheba, Israel;

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Andrew J. Einstein

4Division of Cardiology, Departments of Medicine, and Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, New York;

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Mathews B. Fish

5Oregon Heart and Vascular Institute, Sacred Heart Medical Center, Springfield, Oregon;

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Terrence D. Ruddy

6Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada;

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Philipp A. Kaufmann

7Cardiac Imaging, Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland;

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Albert J. Sinusas

8Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut;

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Edward J. Miller

8Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut;

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Timothy M. Bateman

9Cardiovascular Imaging Technologies LLC, Kansas City, Missouri; and

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Sharmila Dorbala

10Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Brigham and Women’s Hospital, Boston, Massachusetts

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Marcelo Di Carli

10Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Brigham and Women’s Hospital, Boston, Massachusetts

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Sean Hayes

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

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John Friedman

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

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Daniel S. Berman

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

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Damini Dey

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

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Piotr J. Slomka

1Division of Artificial Intelligence in Medicine, Departments of Medicine, Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;

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Journal of Nuclear Medicine

Vol. 66, Issue 5

May 1, 2025

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Artificial Intelligence–Enhanced Perfusion Scoring Improves the Diagnostic Accuracy of Myocardial Perfusion Imaging

Journal of Nuclear Medicine Feb 2025, jnumed.124.268079; DOI: 10.2967/jnumed.124.268079

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Artificial Intelligence–Enhanced Perfusion Scoring Improves the Diagnostic Accuracy of Myocardial Perfusion Imaging

Journal of Nuclear Medicine Feb 2025, jnumed.124.268079; DOI: 10.2967/jnumed.124.268079

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Keywords

deep learning
myocardial perfusion imaging
quantification
artificial intelligence
diagnostic accuracy

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