Optimization of 15O-H2O dose for cerebral blood flow imaging on a time-of-flight PET/MR scanner (2016)

1860 Objectives In PET imaging, higher injection activity levels do not necessarily improve image quality; at some point, the additional noise from measured randoms (which scale proportional to activity squared) and effects of system deadtime combine to decrease image signal-to-noise ratio (SNR). The study objective was to determine an 15O-H2O injection activity level that optimizes PET image SNR at the peak of the arterial input function (AIF) for cerebral blood flow (CBF) measurement. Methods Six subjects were injected with 15O-H2O activity levels between 13.2 and 25.8 mCi. Each subject was injected and scanned both before and after administration of Diamox. Scanning was performed on a simultaneous time-of-flight enabled PET/MR (GE SIGNA PET/MR, Waukesha, WI). The data were grouped into short dynamic bins (3 s), and images were reconstructed. Taking into account the SNR limitations for short frame durations, the data were used to determine a standard SNR-optimized injection level for future scans. A commonly applied methodology of understanding PET image quality as a function of activity level is noise equivalent count rate (NECR) analysis (Strother et al, 1990). This approach applies statistical analysis to the raw PET data to predict relative image SNR. As exhibited in a typical NECR curve, SNR initially increases with increasing injection level, reaches a “peak NECR” point, and then decreases as randoms and deadtime effects limit effectiveness of the scanner. Traditional methods of creating an NECR curve require a full decay series acquisition with fixed activity distribution, which is not possible in the context of clinical scanning due to biological redistribution. To address this challenge, acquisition-specific NECR (AS-NECR) methods (Stearns, 2003) were developed to generate a full NECR curve from a single frame of PET raw data. To adapt this method for the GE SIGNA PET/MR scanner, the AS-NECR model parameters were first tuned based on measured phantom data. Using these parameters, the AS-NECR method was applied to each PET dataset’s dynamic frame corresponding to peak AIF. This dynamic frame was chosen due to the importance of peak AIF in cerebral blood flow estimation. PET raw data from only a single frame is needed to create this AS-NECR curve, which allows the dose optimization based on tracer biodistribution at the most critical peak AIF time point. From only a single injection, this method reveals the injection level that would have optimized peak NECR for the PET frame corresponding to peak AIF. The method was repeated for each subject to determine the injection activity that would maximize image SNR. Results The twelve datasets (two acquisitions for each of six patients) reached peak NECR corresponding to injection levels of 22.7 +/- 3.5 mCi (mean +/- standard deviation). Due to the relatively flat nature of the NECR curve near its peak, a standard site protocol of 23 mCi is deemed sufficient for each study. This protocol is adopted by the site for future studies in order to maximize image SNR for the PET dynamic frame corresponding to peak AIF.
Conclusions:AS-NECR techniques can be applied to determine optimal injection levels for dynamic PET scanning of the brain. The optimal injection level is specific to the scanner geometry, isotope/tracer, and injection method. A clinical injection protocol of 23 mCi (850 MBq) was adopted for PET scanning with 15O-H2O for future studies on the GE SIGNA PET/MR.