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Updated: Sep 28, 2025

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

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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.

Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine

|April 2, 2022

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 code GPU Gamma-ray Image reconstruction Positron emission tomography (PET)TOF USERDUMP

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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.