General Purpose Deep Learning Attenuation Correction Improves Diagnostic Accuracy of SPECT MPI: A Multicenter Study.

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Title: General Purpose Deep Learning Attenuation Correction Improves Diagnostic Accuracy of SPECT MPI: A Multicenter Study.
Authors: Shanbhag AD; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA., Miller RJH; Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada., Lemley M; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA., Kavanagh P; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA., Liang JX; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA., Marcinkiewicz AM; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA; Center of Radiological Diagnostics, National Medical Institute of the Ministry of the Interior and Administration, Warsaw, Poland., Builoff V; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA., Van Kriekinge S; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA., Ruddy TD; Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada., Fish MB; Oregon Heart and Vascular Institute, Sacred Heart Medical Center, Springfield, Oregon, USA., Einstein AJ; Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, New York, USA; Department of Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, New York, USA., Martins M; Swansea University Medical School, Swansea University, Swansea, United Kingdom., Halcox JP; Swansea University Medical School, Swansea University, Swansea, United Kingdom., Kaufmann PA; Division of Cardiac Imaging, Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland., Buckley C; GE HealthCare, Pollards Wood, United Kingdom., Bateman TM; Cardiovascular Imaging Technologies, LLC, Kansas City, Missouri, USA; Saint Luke's Health System, Kansas City, Missouri, USA., Berman DS; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA., Dey D; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA., Slomka PJ; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA. Electronic address: piotr.slomka@cshs.org.
Source: JACC. Cardiovascular imaging [JACC Cardiovasc Imaging] 2025 Nov; Vol. 18 (11), pp. 1235-1246. Date of Electronic Publication: 2025 Aug 08.
Publication Type: Journal Article; Multicenter Study; Clinical Trial, Phase III
Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 101467978 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1876-7591 (Electronic) Linking ISSN: 18767591 NLM ISO Abbreviation: JACC Cardiovasc Imaging Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1876-7591
DOI:10.1016/j.jcmg.2025.06.010