Development of a GEANT4-Based Monte Carlo algorithm for polarized nuclear imaging simulations integrated into GATE.

Area of Science:

• Medical Imaging
• Nuclear Physics
• Computational Science

Background:

• Polarized Nuclear Imaging (PNI) is an innovative gamma imaging technique.
• It encodes spatial information using polarized radioactive nuclei and magnetic fields.
• PNI eliminates the need for collimators by directly encoding k-space.

Purpose of the Study:

• Develop the first high-performance Monte Carlo-based algorithm for PNI.
• Integrate the algorithm into the GATE simulation framework.
• Advance research and understanding of PNI through Monte Carlo simulations.

Main Methods:

• Implemented a Geant4-based algorithm as a new source type in GATE.
• Enabled users to define and configure PNI sources within GATE.
• Simulated PNI by generating photons based on spin orientations of polarized nuclei.

Main Results:

• The simulation tool achieved minimal relative errors (∼0.0000018%) in replicating theoretical gamma emission distributions.
• Extracted k-space data showed a 3.57% difference from theoretical values.
• Simulations of a complex PNI source aligned with experimental data.

Conclusions:

• The GATE-based PNI simulation toolkit provides an efficient and accurate method for PNI research.
• Facilitates user-friendly investigation of PNI.
• Paves the way for advanced PNI research and system optimization.