The REgistry of Flow and Perfusion Imaging for Artificial INtelligEnce with PET(REFINE PET): Rationale and Design.
Authors
Affiliations (22)
Affiliations (22)
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA.
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland.
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada.
- Cardiology Division, Montefiore Health System/Albert Einstein College of Medicine, NY, USA.
- Department of Radiology (Nuclear Medicine), Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Nuclear Cardiology, Ignacio Chavez National Institute of Cardiology, Mexico City, Mexico; Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico.
- Department of Nuclear Cardiology, Ignacio Chavez National Institute of Cardiology, Mexico City, Mexico.
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA; West Los Angeles Veterans Affairs Medical Center, Los Angeles, CA, USA.
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Academic Institute, Houston, TX, USA.
- Division of Cardiology, Department of Medicine, and Department of Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, USA.
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.
- Intermountain Medical Center Heart Institute, Intermountain Healthcare, Murray, UT, USA; Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA.
- Intermountain Medical Center Heart Institute, Intermountain Healthcare, Murray, UT, USA.
- Section of Cardiology, Department of Medicine, Rush University Medical Center, Chicago, IL, USA.
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
- Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Zurich, Switzerland.
- Department of Cardiovascular Medicine, The University of Kansas Medical Center, Kansas City, KS, USA.
- Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, ON, Canada.
- Cardiovascular Imaging Program, Departments of Radiology and Medicine; Division of Nuclear Medicine and Molecular Imaging, Department of Radiology; and Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Electronic address: [email protected].
Abstract
The REgistry of Flow and Perfusion Imaging for Artificial Intelligence with PET (REFINE PET) was established to collect multicenter PET and associated computed tomography (CT) images, together with clinical data and outcomes, into a comprehensive research resource. REFINE PET will enable validation and development of both standard and novel cardiac PET/CT processing methods. REFINE PET is a multicenter, international registry that contains both clinical and imaging data. The PET scans were processed using QPET software (Cedars-Sinai Medical Center, Los Angeles, CA), while the CT scans were processed using deep learning (DL) to detect coronary artery calcium (CAC). Patients were followed up for the occurrence of major adverse cardiovascular events (MACE), which include death, myocardial infarction, unstable angina, and late revascularization (>90 days from PET). The REFINE PET registry currently contains data for 35,588 patients from 14 sites, with additional patient data and sites anticipated. Comprehensive clinical data (including demographics, medical history, and stress test results) were integrated with more than 2200 imaging variables across 42 categories. The registry is poised to address a broad range of clinical questions, supported by correlating invasive angiography (within 6 months of MPI) in 5972 patients and a total of 9252 major adverse cardiovascular events during a median follow-up of 4.2 years. The REFINE PET registry leverages the integration of clinical, multimodality imaging, and novel quantitative and AI tools to advance the role of PET/CT MPI in diagnosis and risk stratification.