Abstract
A GATE Monte Carlo model of the Philips Vereos digital photon counting PET imaging system using silicon photo-multiplier detectors was proposed. It was evaluated against experimental data in accordance with NEMA guidelines. Comparisons were performed using listmode data in order to remain independent of image reconstruction algorithms. An original line of response-based method is proposed to estimate intrinsic spatial resolution without reconstruction. Four sets of experiments were performed: (1) count rates and scatter fraction, (2) energy and timing resolutions, (3) sensitivity, and (4) intrinsic spatial resolution. Experimental and simulated data were found to be in good agreement, with overall differences lower than 10% for activity concentrations used in most standard clinical applications. Illustrative image reconstructions were provided. In conclusion, the proposed Monte Carlo model was validated and can be used for numerous studies such as optimizing acquisition parameters or reconstruction algorithms.
Highlights
Positron emission tomography (PET) imaging has an essential role in modern medicine for both diagnostic and follow-up of oncology treatments [1]
Precision in the location of the annihilation has been improved with the use of time-offlight (TOF) information, which spatially constrains the location of the event on the line of response (LOR), increasing the signal-to-noise ratio (SNR) in the reconstructed image [2]
The difference for scatter count rate stayed below 5% up to a concentration of 10 kBq mL−1
Summary
Positron emission tomography (PET) imaging has an essential role in modern medicine for both diagnostic and follow-up of oncology treatments [1]. PET technology has experienced tremendous improvements in performance over recent decades and new trends make use of silicon photo-multiplier (SiPM) detectors such as the Philips Vereos digital photon counting (DPC) PET/CT introduced in 2013, the GE DicoveryTM MI PET/CT launched in 2016 and the Siemens Biograph VisionTM PET/CT in 2018. Precision in the location of the annihilation has been improved with the use of time-offlight (TOF) information, which spatially constrains the location of the event on the line of response (LOR), increasing the signal-to-noise ratio (SNR) in the reconstructed image [2]. Detecting and processing signals using digital SiPMs bypasses the need to treat analogous signals by a direct binary count of optical photons, reducing noise in the processed output.
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