Online energy discrimination at DAQ front-end level on pixelated TOF-PET systems

Abstract

Pixelated positron emission tomography (PET) systems produce higher count rates than traditional block detectors because they integrate several detecting channels per detector module. An increased data flow from the detectors leads to higher bandwidth requirements. We aim to optimize the bandwidth usage efficiency by on-the-fly filtering of detected events for non-valid energies. PET systems with a SiPM-ASIC readout scheme are being extensively used to obtain enhanced images on time-of-flight PET scanners. Such digital readout systems are especially interesting for the application of online processing techniques given the ease of access to the digital information of each detected event. This study analyzes online processing techniques at the DAQ front-end level (on-detector electronics) for pixelated PET systems with SiPM-ASIC readout. In particular, we worked with a tunable online energy discriminating stage. For the optimization of its hardwired internal limits, we analyzed the system energy space. We explored various solutions, some of which are dependent on the system's energy calibration, whereas others were not. Results obtained through the application of various filter versions confirm the minimal resources consumption of such processing techniques implemented at the DAQ front-end level. Our experiments demonstrate how the filtering process reduces the bandwidth needs by excluding all non-valid energy events from the data stream, thus improving the system sensitivity under saturation conditions. Additionally, these experiments highlight how setting proper energy limits can ensure preservation of the system performance, which maintains its original energy and time resolution. In light of these findings, we see great potential for the application of online processing techniques for time-of-flight PET at the DAQ font-end level (on-detector electronics); therefore, we envisage the development of more complex processing methods.