Monte-Carlo Based Characterization of the Counting Rate (NECR) Response for Personalized Optimization of the Administered Activity in Clinical PET Imaging

The statistical quality of a PET scan can be significantly affected by the associated patient and scanner characteristics. Standard protocols could be optimized by regulating the administered activity Aadm such that the statistical quality is maximized for each individual patient for a given scan time. The objective is to model the direct relationship between the noise equivalent count rate NECR and Aadm for a wide range of scanner and patient parameters employed in clinical scans. A series of extensive and validated Monte Carlo simulations is utilized to systematically investigate, under realistic and controlled conditions, the effect of a wide set of (i) phantom sizes modeling children, slim and obese patients, (ii) bed positions, (iii) energy windows, (iv) coincidence time windows, (v) and combination of dead times and detector responses on the NECR for a range of Aadm. A wide plateau is observed in NECR(Aadm) curves particularly for large patients, suggesting that 90-95% of peak NECR can still be obtained with considerably less Aadm. Moreover, for default scanner configurations and cardiac beds, an optimal Aadm range of 55-65 MBq for HR+ and 300-450 MBq for Biograph scanners, with the maximum NECR being considerably higher for the latter. The generalized NECR(Aadm) model can be utilized to predict for each individual Optimization, patient scan an optimal range of Aadm for which NECR is maximized, thus potentially allowing (a) for efficient utilization of the available activity in PET centers and (b) for minimization of cumulative radiation exposure.