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Field-programable-gate-array-based distributed coincidence processor for high count-rate online positron emission

Xinyi Cheng1, Kun Hu1, Dongxu Yang1

  • 1Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75057, United States of America.

Physics in Medicine and Biology
|February 16, 2021
PubMed
Summary
This summary is machine-generated.

Distributed coincidence processors (DCP) offer a solution for positron emission tomography (PET) data acquisition, overcoming limitations of centralized systems. This novel approach enhances count-rate capability and simplifies implementation for advanced PET imaging.

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Area of Science:

  • Nuclear Instrumentation
  • Medical Imaging Physics
  • High-Energy Physics Detectors

Background:

  • Centralized coincidence processors (CCP) are standard in positron emission tomography (PET) but face limitations with high count-rates and complex implementations, especially on FPGAs.
  • Existing distributed processing solutions are often proprietary or lack detailed technical information, hindering adoption by research communities.
  • The need for improved data acquisition systems in PET is driven by increasing detector counts and the demand for higher throughput imaging.

Purpose of the Study:

  • To investigate the efficacy of distributed coincidence processors (DCP) as an alternative to CCP for PET online data acquisition.
  • To address the data processing delays and count-rate limitations inherent in CCP systems.
  • To develop a simplified and adaptable solution for coincidence event selection in PET scanners.

Main Methods:

  • Developed a distributed coincidence processor (DCP) architecture where each processor handles a single detector pair, enabling parallel processing.
  • Implemented a prototype DCP with 42 processors on an FPGA development board for a 12-detector PET system.
  • Tested DCP performance using pulsed signals and gamma ray interactions, evaluating data loss, resource utilization, and timing accuracy.

Main Results:

  • The DCP demonstrated no coincidence data loss up to the detector's maximum singles count-rate of 250 k s⁻¹.
  • Each coincidence processor utilized approximately 1.2 k registers, with FPGA resource usage scaling proportionally to the number of processors.
  • Coincidence timing spectra confirmed the accurate acquisition of coincidence events, validating the DCP's functionality.

Conclusions:

  • Distributed coincidence processors (DCP) offer a viable alternative to CCP, providing high count-rate capability and simplified implementation for PET systems.
  • The DCP architecture is scalable and practical for PET scanners with a large number of detector pairs or those requiring ultrahigh-throughput imaging.
  • This research presents a potentially adaptable solution for the PET research community, enhancing online data acquisition performance.