title: Comparison and prognostic validation of multiple methods of quantification of myocardial blood flow with 82Rb PET.
abstract: The quantification of myocardial blood flow (MBF) and myocardial flow reserve (MFR) using PET with (82)Rb in patients with known or suspected coronary artery disease has been demonstrated to have substantial prognostic and diagnostic value. However, multiple methods for estimation of an image-derived input function and several models for the nonlinear first-pass extraction of (82)Rb by myocardium have been used. We sought to compare the differences in these methods and models and their impact on prognostic assessment in a large clinical dataset.
  
  
  METHODS
  Consecutive patients (n = 2,783) underwent clinically indicated rest-stress myocardial perfusion PET with (82)Rb. The input function was derived using a region of interest (ROI) semiautomatically placed in the region of the mitral valve, factor analysis, and a hybrid method that creates an ROI from factor analysis. We used 5 commonly used extraction models for (82)Rb to estimate MBF and MFR. Pearson correlations, bias, and Cohen κ were computed for the various measures. The relationship between MFR/stress MBF and annual rate of cardiac mortality was estimated with spline fits using Poisson regression. Finally, incremental value was assessed with the net reclassification improvement using Cox proportional hazards regression.
  
  
  RESULTS
  Correlations between MFR or stress MBF measures made with the same input function derivation method were generally high, regardless of extraction model used (Pearson r > 0.90). However, correlations between measures derived with the ROI method and other methods were only moderate (Pearson r = 0.42-0.62). Importantly, substantial biases were seen for most combinations. We saw that the relationship between cardiac mortality and stress MBF was variable depending on the input function method and extraction model, whereas the relationship between MFR and risk was highly consistent. Net reclassification improvement was comparable for most methods and models for MFR but was highly variable for stress MBF.
  
  
  CONCLUSIONS
  Although both stress MBF and MFR can improve prognostic assessment, MFR is substantially more consistent, regardless of choice of input function derivation method and extraction model used.
authors.affiliation: Noninvasive Cardiovascular Imaging Program, Departments of Radiology and Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, Michigan vlmurthy@med.umich.edu.
authors.forename: Venkatesh L
authors.initials: VL
authors.lastname: Murthy
authors.affiliation: INVIA Medical Imaging Solutions, Ann Arbor, Michigan; and.
authors.forename: Benjamin C
authors.initials: BC
authors.lastname: Lee
authors.affiliation: Division of Nuclear Medicine, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Arkadiusz
authors.initials: A
authors.lastname: Sitek
authors.affiliation: Noninvasive Cardiovascular Imaging Program, Departments of Radiology and Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
authors.forename: Masanao
authors.initials: M
authors.lastname: Naya
authors.affiliation: INVIA Medical Imaging Solutions, Ann Arbor, Michigan; and.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Moody
authors.affiliation: Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, Michigan.
authors.forename: Vivek
authors.initials: V
authors.lastname: Polavarapu
authors.affiliation: Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, Michigan INVIA Medical Imaging Solutions, Ann Arbor, Michigan; and.
authors.forename: Edward P
authors.initials: EP
authors.lastname: Ficaro
authors.affiliation: Noninvasive Cardiovascular Imaging Program, Departments of Radiology and Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
authors.forename: Marcelo F
authors.initials: MF
authors.lastname: Di Carli
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D003326:Coronary Circulation / Q000502:physiology*; D003327:Coronary Disease / Q000175:diagnosis / Q000000981:diagnostic imaging* / Q000401:mortality; D005080:Exercise Test; D005260:Female; D006321:Heart / Q000000981:diagnostic imaging*; D006801:Humans; D008297:Male; D008875:Middle Aged; D049268:Positron-Emission Tomography / Q000379:methods*; D011379:Prognosis; D015203:Reproducibility of Results; D012307:Risk Factors; D012414:Rubidium Radioisotopes
chemical_list: D012414:Rubidium Radioisotopes
keywords: 82Rb; myocardial flow reserve; myocardial perfusion imaging