title: Quantitative dynamic cardiac 82Rb PET using generalized factor and compartment analyses.
abstract: We have addressed 2 major challenges of (82)Rb cardiac PET, noninvasive estimation of an accurate input function and absolute quantitation of myocardial perfusion, using a generalized form of least-squares factor analysis of dynamic sequences (GFADS) and a novel compartment analysis approach.
  
  
  METHODS
  Left and right ventricular (LV + RV) time-activity curves (TACs) were generated from 10 rest/stress studies, and 30 myocardial TACs were modeled to cover a range of clinical values. Two-dimensional PET Monte Carlo simulations of the LV, RV, myocardium, and other organs were generated separately and combined using the above TACs to form 30 realistic dynamic (82)Rb studies. LV and RV TACs were estimated by GFADS and used as input to a 2-compartment kinetic analysis that estimates parametric maps of myocardial tissue extraction (k(1)) and egress (k(2)), as well as LV + RV contributions (f(v), r(v)), by orthogonal voxel grouping. In addition, 13 patients were injected with 2.22 +/- 0.19 GBq (60 +/- 5 mCi) of (82)Rb and imaged dynamically for 6 min at rest and during dipyridamole stress.
  
  
  RESULTS
  In Monte Carlo simulations, GFADS yielded estimates of the 3 factors and corresponding factor images, with average errors of -4.2% +/- 6.3%, 3.5% +/- 4.3%, and 2.0% +/- 5.5% in the LV, RV, and myocardial factor estimates, respectively. The estimates were significantly more accurate and robust to noise than those obtained using TACs based on manually drawn volumes of interest (P < 0.01). The 2-compartment approach yielded accurate k(1), k(2), f(v), and r(v) parametric maps; the average error of estimates of k(1) was 6.8% +/- 3.6%. In all patient studies, our approach yielded robust estimates of k(1), k(2), f(v), and r(v), which correlated very well with the status of the subject and the catheterization results.
  
  
  CONCLUSIONS
  Quantitative dynamic (82)Rb PET using generalized factor analysis of dynamic sequences and compartmental modeling yields estimates of parameters of absolute myocardial perfusion and kinetics with errors of <9%.
authors.affiliation: Division of Nuclear Medicine, Department of Radiology, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts, USA.
authors.forename: Georges
authors.initials: G
authors.lastname: El Fakhri
authors.forename: Arkadiusz
authors.initials: A
authors.lastname: Sitek
authors.forename: Bastien
authors.initials: B
authors.lastname: Guérin
authors.forename: Marie Foley
authors.initials: MF
authors.lastname: Kijewski
authors.forename: Marcelo F
authors.initials: MF
authors.lastname: Di Carli
authors.forename: Stephen C
authors.initials: SC
authors.lastname: Moore
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D005240:Feasibility Studies; D005260:Female; D006321:Heart / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012414:Rubidium Radioisotopes; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index
chemical_list: D019275:Radiopharmaceuticals; D012414:Rubidium Radioisotopes