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Journal of Nuclear Medicine

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Research ArticleClinical Investigation

Deep Learning–Enabled Quantification of 99mTc-Pyrophosphate SPECT/CT for Cardiac Amyloidosis

Robert J.H. Miller, Aakash Shanbhag, Anna M. Michalowska, Paul Kavanagh, Joanna X. Liang, Valerie Builoff, Nowell M. Fine, Damini Dey, Daniel S. Berman and Piotr J. Slomka
Journal of Nuclear Medicine July 2024, 65 (7) 1144-1150; DOI: https://doi.org/10.2967/jnumed.124.267542
Robert J.H. Miller
1Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada;
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Aakash Shanbhag
2Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California; and
3Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California
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Anna M. Michalowska
2Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California; and
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Paul Kavanagh
2Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California; and
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Joanna X. Liang
2Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California; and
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Valerie Builoff
2Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California; and
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Nowell M. Fine
1Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada;
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Damini Dey
2Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California; and
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Daniel S. Berman
2Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California; and
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Piotr J. Slomka
2Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California; and
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Journal of Nuclear Medicine: 65 (7)
Journal of Nuclear Medicine
Vol. 65, Issue 7
July 1, 2024
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Deep Learning–Enabled Quantification of 99mTc-Pyrophosphate SPECT/CT for Cardiac Amyloidosis
Robert J.H. Miller, Aakash Shanbhag, Anna M. Michalowska, Paul Kavanagh, Joanna X. Liang, Valerie Builoff, Nowell M. Fine, Damini Dey, Daniel S. Berman, Piotr J. Slomka
Journal of Nuclear Medicine Jul 2024, 65 (7) 1144-1150; DOI: 10.2967/jnumed.124.267542

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Deep Learning–Enabled Quantification of 99mTc-Pyrophosphate SPECT/CT for Cardiac Amyloidosis
Robert J.H. Miller, Aakash Shanbhag, Anna M. Michalowska, Paul Kavanagh, Joanna X. Liang, Valerie Builoff, Nowell M. Fine, Damini Dey, Daniel S. Berman, Piotr J. Slomka
Journal of Nuclear Medicine Jul 2024, 65 (7) 1144-1150; DOI: 10.2967/jnumed.124.267542
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Keywords

  • cardiac amyloidosis
  • technetium pyrophosphate
  • quantification
  • diagnostic accuracy
  • biomarker
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