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Modeling GE advance PET-scanner using FLUKA simulation code.

Y Nasirzadeh1, N Ghal-Eh1, M H Hadizadeh Yazdi1

  • 1Department of Physics, Faculty of Science, Ferdowsi University of Mashhad, P.O. Box 91775-1436, Mashhad, Iran.

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|April 2, 2022
PubMed
Summary

FLUKA simulations modeled the GE Advance PET scanner, enabling source localization without reconstruction packages. Time-of-flight PET imaging yielded optimal results for positron-emitting sources.

Keywords:
FLUKA Monte Carlo codeGPUGamma-rayImage reconstructionPositron emission tomography (PET)TOFUSERDUMP

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Area of Science:

  • Medical Physics
  • Nuclear Instrumentation
  • Computational Science

Background:

  • Positron Emission Tomography (PET) scanners require accurate modeling for performance evaluation.
  • GE Advance PET scanner (GEMS) is a widely used system in clinical research.
  • Particle transport simulations are crucial for understanding scanner physics.

Purpose of the Study:

  • To model the GE Advance PET scanner using the FLUKA code.
  • To develop and validate algorithms for source localization without conventional reconstruction.
  • To evaluate the performance of time-of-flight PET (TOF-PET) imaging.

Main Methods:

  • Utilized the FLUKA particle transport code to simulate the GEMS scanner.
  • Employed the USERDUMP phase-space card and mgdraw user-routine for data extraction.
  • Developed three algorithms for source localization and applied TOF-PET for image reconstruction.
  • Performed post-processing calculations using MATLAB and Fortran on CPU and GPU.

Main Results:

  • Successfully modeled the GE Advance PET scanner geometry and response.
  • Demonstrated effective source localization using proposed algorithms, bypassing standard reconstruction.
  • Achieved optimal image reconstruction for volumetric sources via TOF-PET, validated by chi-square analysis.
  • Efficiently handled post-processing computations using both CPU and GPU.

Conclusions:

  • FLUKA is a suitable tool for detailed modeling of PET scanners like GEMS.
  • Novel algorithms can accurately identify source locations, reducing reliance on reconstruction packages.
  • TOF-PET imaging provides high-quality reconstructions for volumetric positron emitters.
  • Computational efficiency was achieved through parallel processing (CPU/GPU) and optimized programming.