Implementation of Scalable Streaming Readout Data Acquisition and Analysis Platform to Enable Total-Body Positron Emission Tomography

Total-body positron emission tomography (TB-PET) is a nuclear medicine imaging modality that requires coincidence-pair event analysis with real-time processing from thousands of detector channels. Digitizing signals near the hardware shifts data triggering and analysis to software, enabling increasingly complex configurations in streaming readout (SRO). Thomas Jefferson National Accelerator Facility (JLab) has developed nuclear physics detector systems with front-ends and analysis systems which can support the scale of detector quantities and modularity needed for TB-PET. We have built scalable TB-PET capable detectors and analysis systems utilizing open-source software and commercially available detector components and are in the process of characterizing the scaling performance relevant to TB-PET data rates and analysis architectures with a prototype pre-clinical PET platform. Each detector consists of an LYSO crystal scintillator array read out by a pixelated SiPM, whose signal is processed by a Weeroc PETIROC ASIC and packaged by a single FPGA dedicated to each front-end detector. We implement the analysis architecture in JLab's Environment for Real-time Streaming, Acquisition and Processing (ERSAP) and use standard high-performance computing techniques to investigate the potential scaling performance at TB-PET scales. We show initial PET imaging results in anticipation of scheduled pre-clinical phantom benchmarking scans at the University of Maryland School of Medicine.