The results clearly show that DL improves MPI interpretation over current methods.
"These findings were demonstrated for the first time in a rigorous, repeated external validation," points out Piotr J. Slomka, PhD, at Cedars-Sinai Medical Center, affirming that "the latest developments in artificial intelligence can be efficiently leveraged to enhance the accuracy of existing nuclear medicine techniques."
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The focus is always on advancing patient care, and Slomka says, "Patients will benefit from increased diagnostic accuracy and reproducibility of SPECT myocardial perfusion imaging when such systems are deployed clinically."
Authors of "Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study" include Julian Betancur, Lien-Hsin Hu, Frederic Commandeur, Guido Germano, Yuka Otaki, Joanna X. Liang, Balaji K. Tamarappoo, Damini Dey, Daniel S. Berman, and Piotr J. Slomka, Cedars-Sinai Medical Center, Los Angeles, California; Tali Sharir, Assuta Medical Centers, Tel Aviv, and Ben Gurion University of the Negev, Beer Sheba, Israel; Andrew J. Einstein, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, New York; Mathews B. Fish, Sacred Heart Medical Center, Springfield, Oregon; Terrence D. Ruddy, University of Ottawa Heart Institute, Ottawa, Canada; Philipp A. Kaufmann, University Hospital Zurich, Zurich, Switzerland; Albert J. Sinusas and Edward J. Miller, Yale University School of Medicine, New Haven, Connecticut; Timothy M. Bateman, Cardiovascular Imaging Technologies LLC, Kansas City, Missouri; and Marcelo Di Carli and Sharmila Dorbala, Brigham and Women's Hospital, Boston, Massachusetts.
This study was made available online in September 2018 ahead of final publication in print in May 2019.
This research was supported in part by a grant from the National Heart, Lung, and Blood Institute of the National Institutes of Health.
About the Society of Nuclear Medicine and Molecular Imaging
The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and medical organization dedicated to advancing nuclear medicine and molecular imaging, vital elements of precision medicine that allow diagnosis and treatment to be tailored to individual patients in order to achieve the best possible outcomes.
SNMMI's more than 17,000 members set the standard for molecular imaging and nuclear medicine practice by creating guidelines, sharing information through journals and meetings and leading advocacy on key issues that affect molecular imaging and therapy research and practice.
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