Validation of the SimSET simulation package for modeling the Siemens Biograph mCT PET scanner.

Monte Carlo simulation provides a valuable tool in performance assessment and optimization of system design parameters for PET scanners. SimSET is a popular Monte Carlo simulation toolkit that features fast simulation time, as well as variance reduction tools to further enhance computational efficiency. However, SimSET has lacked the ability to simulate block detectors until its most recent release. Our goal is to validate new features of SimSET by developing a simulation model of the Siemens Biograph mCT PET scanner and comparing the results to a simulation model developed in the GATE simulation suite and to experimental results. We used the NEMA NU-2 2007 scatter fraction, count rates, and spatial resolution protocols to validate the SimSET simulation model and its new features. The SimSET model overestimated the experimental results of the count rate tests by 11-23% and the spatial resolution test by 13-28%, which is comparable to previous validation studies of other PET scanners in the literature. The difference between the SimSET and GATE simulation was approximately 4-8% for the count rate test and approximately 3-11% for the spatial resolution test. In terms of computational time, SimSET performed simulations approximately 11 times faster than GATE simulations. The new block detector model in SimSET offers a fast and reasonably accurate simulation toolkit for PET imaging applications.

Towards component-based validation of GATE: aspects of the coincidence processor.

GATE is public domain software widely used for Monte Carlo simulation in emission tomography. Validations of GATE have primarily been performed on a whole-system basis, leaving the possibility that errors in one sub-system may be offset by errors in others. We assess the accuracy of the GATE PET coincidence generation sub-system in isolation, focusing on the options most closely modeling the majority of commercially available scanners. Independent coincidence generators were coded by teams at Toshiba Medical Research Unit (TMRU) and UC Davis. A model similar to the Siemens mCT scanner was created in GATE. Annihilation photons interacting with the detectors were recorded. Coincidences were generated using GATE, TMRU and UC Davis code and results compared to "ground truth" obtained from the history of the photon interactions. GATE was tested twice, once with every qualified single event opening a time window and initiating a coincidence check (the "multiple window method"), and once where a time window is opened and a coincidence check initiated only by the first single event to occur after the end of the prior time window (the "single window method"). True, scattered and random coincidences were compared. Noise equivalent count rates were also computed and compared. The TMRU and UC Davis coincidence generators agree well with ground truth. With GATE, reasonable accuracy can be obtained if the single window method option is chosen and random coincidences are estimated without use of the delayed coincidence option. However in this GATE version, other parameter combinations can result in significant errors.

Optimal whole-body PET scanner configurations for different volumes of LSO scintillator: a simulation study.

The axial field of view (AFOV) of the current generation of clinical whole-body PET scanners range from 15-22 cm, which limits sensitivity and renders applications such as whole-body dynamic imaging or imaging of very low activities in whole-body cellular tracking studies, almost impossible. Generally, extending the AFOV significantly increases the sensitivity and count-rate performance. However, extending the AFOV while maintaining detector thickness has significant cost implications. In addition, random coincidences, detector dead time, and object attenuation may reduce scanner performance as the AFOV increases. In this paper, we use Monte Carlo simulations to find the optimal scanner geometry (i.e. AFOV, detector thickness and acceptance angle) based on count-rate performance for a range of scintillator volumes ranging from 10 to 93 l with detector thickness varying from 5 to 20 mm. We compare the results to the performance of a scanner based on the current Siemens Biograph mCT geometry and electronics. Our simulation models were developed based on individual components of the Siemens Biograph mCT and were validated against experimental data using the NEMA NU-2 2007 count-rate protocol. In the study, noise-equivalent count rate (NECR) was computed as a function of maximum ring difference (i.e. acceptance angle) and activity concentration using a 27 cm diameter, 200 cm uniformly filled cylindrical phantom for each scanner configuration. To reduce the effect of random coincidences, we implemented a variable coincidence time window based on the length of the lines of response, which increased NECR performance up to 10% compared to using a static coincidence time window for scanners with a large maximum ring difference values. For a given scintillator volume, the optimal configuration results in modest count-rate performance gains of up to 16% compared to the shortest AFOV scanner with the thickest detectors. However, the longest AFOV of approximately 2 m with 20 mm thick detectors resulted in performance gains of 25-31 times higher NECR relative to the current Siemens Biograph mCT scanner configuration.