Monte-Carlo Based Characterization of the Counting Rate (NECR) Response for Personalized Optimization of the Administered Activity in Clinical PET Imaging
Purpose: 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 A(adm)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 A(adm)for a wide range of scanner and patient parametersemployed in clinical scans.
Methods: 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 A(adm).
Results: A wide plateau is observed in NECR A(adm)curves particularly for large patients,admsuggesting that 90-95% of peak NECR can still be obtained with considerably less A(adm) Moreover, for default scanner configurations and cardiac beds, an optimal A(adm)range of 55-65MBq for HR+ and 300-450 MBq for Biograph scanners, with the maximum NECR beingconsiderably higher for the latter.
Conclusions: The generalized NECR A(adm) model can be utilized to predict for each individual patient scan an optimal range of A(adm) 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.
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