Development of PET using 4 × 4 array of large size Geiger-mode avalanche photodiode

Abstract

Geiger-mode avalanche photodiode (GAPD) has been demonstrated to be a high performance PET sensor because of high gain, fast response, low excess noise, low bias voltage operation and magnetic field insensitivity. The purpose of this study is to develop a PET for human brain imaging using 4 × 4 array of large size GAPD. PET detector modules were designed and built to develop a prototype PET. The PET consisted of 72 detector modules arranged in a ring with an inner diameter of 330 mm. The LYSO arrays consisted of 4 × 4 array of 3 × 3 × 20 mm3 pixels, which were 1-to-1 coupled to 4 × 4 arrays of 9 mm2 GAPD pixels (SensL, Ireland). The GAPDs were tiled together using flip chip technology on glass and operated at a bias voltage of 32 V for a gain of 3.5 × 106. The signals of the each module were amplified by a 16 channel preamplifier circuit with differential outputs and then sent to a position decoder circuit (PDC), which readout digital address and analog pulse of the one interacted channel from 64 signals of 4 preamplifier boards. The PDC output signals were fed into FPGA-embedded DAQ boards. The analog signal was sampled with 100 MHz, and arrival time and energy of the digitized signal were calculated and stored. The coincidence data were sorted and reconstructed by standard filtered back projection. The energy and time resolution of LYSO-GAPD block detector for 511-keV was 20.4% and 2.4 ns, respectively. The developed PDC could accurately provide the interacted PET signal and reduce the number of the readout channels of PET detector modules based on array type GAPD. The rods down to a diameter of 3.5 mm were resolved in hot-rod phantom image acquired with the brain PET which is similar to the image obtained by Monte Carlo simulation. Activity distribution pattern between white and gray matter in Hoffman brain phantom was well imaged. These results demonstrate that high performance PET could be developed using the GAPD-based PET detectors, analog and digital signal processing methods designed in this work. The prototype brain PET will be tested in a clinical 3T MRI to construct a combined PET-MRI.