Free-running ADC- and FPGA-based signal processing method for brain PET using GAPD arrays

Currently, for most photomultiplier tube (PMT)-based PET systems, constant fraction discriminators (CFD) and time to digital converters (TDC) have been employed to detect gamma ray signal arrival time, whereas anger logic circuits and peak detection analog-to-digital converters (ADCs) have been implemented to acquire position and energy information of detected events. As compared to PMT the Geiger-mode avalanche photodiodes (GAPDs) have a variety of advantages, such as compactness, low bias voltage requirement and MRI compatibility. Furthermore, the individual read-out method using a GAPD array coupled 1:1 with an array scintillator can provide better image uniformity than can be achieved using PMT and anger logic circuits. Recently, a brain PET using 72 GAPD arrays (4×4 array, pixel size: 3 mm×3 mm) coupled 1:1 with LYSO scintillators (4×4 array, pixel size: 3 mm×3 mm×20 mm) has been developed for simultaneous PET/MRI imaging in our laboratory. Eighteen 64:1 position decoder circuits (PDCs) were used to reduce GAPD channel number and three off-the-shelf free-running ADC and field programmable gate array (FPGA) combined data acquisition (DAQ) cards were used for data acquisition and processing. In this study, a free-running ADC- and FPGA-based signal processing method was developed for the detection of gamma ray signal arrival time, energy and position information all together for each GAPD channel. For the method developed herein, three DAQ cards continuously acquired 18 channels of pre-amplified analog gamma ray signals and 108-bit digital addresses from 18 PDCs. In the FPGA, the digitized gamma ray pulses and digital addresses were processed to generate data packages containing pulse arrival time, baseline value, energy value and GAPD channel ID. Finally, these data packages were saved to a 128 Mbyte on-board synchronous dynamic random access memory (SDRAM) and then transferred to a host computer for coincidence sorting and image reconstruction. In order to evaluate the functionality of the developed signal processing method, energy and timing resolutions for brain PET were measured via the placement of a 6 μCi ²²Na point source at the center of the PET scanner. Furthermore the PET image of the hot rod phantom (rod diameter: from 2.5 mm to 6.5 mm) with activity of 1 mCi was simulated, and then image acquisition experiment was performed using the brain PET. Measured average energy resolution for 1152 GAPD channels and system timing resolution were 19.5% (FWHM%) and 2.7 ns (FWHM), respectively. With regard to the acquisition of the hot rod phantom image, rods could be resolved down to a diameter of 2.5 mm, which was similar to simulated results. The experimental results demonstrated that the signal processing method developed herein was successfully implemented for brain PET. This reduced the complexity, cost and developing duration for PET system relative to normal PET electronics, and it will obviously be useful for the development of high-performance investigational PET systems.