Quantification of Myocardial Blood Flow in€Absolute Terms Using 82Rb PET Imaging

Fro Ev xR {S **C Mi Nu Ca Un Fin Tu Mi 17) QP rec ser an IN OBJECTIVES The purpose of this study was to compare myocardial blood flow (MBF) and myocardial flow reserve (MFR) estimates from rubidium-82 positron emission tomography (Rb PET) data using 10 software packages (SPs) based on 8 tracer kinetic models. BACKGROUND It is unknown how MBF and MFR values from existing SPs agree for Rb PET. METHODS Rest and stress Rb PET scans of 48 patients with suspected or known coronary artery disease were analyzed in 10 centers. Each center used 1 of 10 SPs to analyze global and regional MBF using the different kinetic models implemented. Values were considered to agree if they simultaneously had an intraclass correlation coefficient >0.75 and a difference <20% of the median across all programs. RESULTS The most common model evaluated was the Ottawa Heart Institute 1-tissue compartment model (OHI-1-TCM). MBF values from 7 of 8 SPs implementing this model agreed best. Values from 2 other models (alternative 1-TCM and Axially distributed) also agreed well, with occasional differences. The MBF results from other models (e.g., 2-TCM and retention) were less in agreement with values from OHI-1-TCM. CONCLUSIONS SPs using the most common kinetic model—OHI-1-TCM—provided consistent results in measuring global and regional MBF values, suggesting that they may be used interchangeably to process data acquired with a common imaging protocol. (J AmColl Cardiol Img2014;7:1119–27)©2014by the American College of Cardiology Foundation. m the *Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland; yIM Sechenov Institute of olutionary Physiology and Biochemistry RAS, St. Petersburg, Russia; zLausanne University Hospital, Lausanne, Switzerland; egional Cancer Institute of Montpellier (ICM)—Val d’Aurelle, Montpellier, France; kUniversity of Florence, Florence, Italy; iemens Molecular Imaging, Oxford, United Kingdom; #Hokkaido University Graduate School of Medicine, Sapporo, Japan; edars-Sinai Medical Center, Los Angeles, California; yyUniversity of Washington, Seattle, Washington; zzUniversity of chigan Health Systems, Ann Arbor, Michigan; xxINVIA Medical Imaging Solutions, Ann Arbor, Michigan; kkDepartment of clear Medicine, Technical University, Munich, Germany; {{Advanced Analytics LLC, Gaithersburg, Maryland; ##National rdiac PET Center, University of Ottawa Heart Institute, Ottawa, Ontario, Canada; ***University College London, London, ited Kingdom; and yyyCardiovascular Imaging Technologies, Kansas City, Missouri. This study was conducted within the nish Centre of Excellence in Cardiovascular and Metabolic Diseases supported by the Academy of Finland, University of rku, Turku University Hospital, and Åbo Akademi University; and was supported in part by grants from the Japanese nistry of Education, Science and Culture (No. 1959135), Northern Advancement Center for Science & Technology (H23-S2, and the U.S. National Institutes of Health grant K25-HL086713. Cedars-Sinai receives royalties from the licensing of ET software, a minority of which is shared with developers, including Drs. Slomka and Germano. Dr. Slomka has eived grant support from Siemens Healthcare. Dr. Alessio has received a research grant from GE Healthcare; and has ved as a consultant for Lantheus Medical Imaging. Dr. Ficaro has received revenue shares from the sale of Corridor4DM d is the owner of INVIA Medical Imaging Solutions. Dr. Lee has received financial support from and is an employee of VIA Medical Imaging Solutions. Drs. deKemp and Klein have received revenue shares from the sale of FlowQuant; and have ABBR EV I A T I ON S