PROJECT TITLE :

Variance Estimation for Myocardial Blood Flow by Dynamic PET

ABSTRACT:

The estimation of myocardial blood flow (MBF) by ammonia or dynamic PET typically relies on an empirically determined generalized Renkin-Crone equation to relate the kinetic parameter to MBF. As a result of the Renkin-Crone equation defines MBF as an implicit function of , the MBF variance can not be determined using normal error propagation techniques. To beat this limitation, we tend to derived novel analytical approximations that give 1st- and second-order estimates of MBF variance in terms of the mean and variance of and also the Renkin-Crone parameters. The accuracy of the analytical expressions was validated by comparison with Monte Carlo simulations, and MBF variance was evaluated in clinical dynamic PET scans. For both and ammonia, sensible agreement was observed between each (initial- and second-order) analytical variance expressions and Monte Carlo simulations, with moderately better agreement for second-order estimates. The contribution of the Renkin-Crone relation to overall MBF uncertainty was found to be as high as 68percent for and thirty fivepercent for ammonia. For clinical PET information, the traditional practice of neglecting t- e statistical uncertainty in the Renkin-Crone parameters resulted in underestimation of the coefficient of variation of world MBF and coronary flow reserve by 14–49p.c. Knowledge of MBF variance is crucial for assessing the precision and reliability of MBF estimates. The form and statistical uncertainty in the empirical Renkin-Crone relation will make substantial contributions to the variance of MBF. The novel analytical variance expressions derived during this work enable direct estimation of MBF variance that includes this previously neglected contribution.