Optimizing positron emission tomography for accurate plant imaging using Monte Carlo simulations to correct positron...

Area of Science:

• Nuclear physics and instrumentation
• Plant science and imaging
• Medical physics

Background:

• Positron Emission Tomography (PET) is crucial for plant imaging.
• Positron range effects can reduce PET imaging accuracy.
• Accurate quantification is essential for plant research.

Purpose of the Study:

• To improve PET imaging accuracy in plants by correcting positron range effects.
• To validate the GATE Monte Carlo simulation model for PET systems.
• To investigate the impact of different isotopes and phantom properties on image quality.

Main Methods:

• Validated a GATE Monte Carlo model for the Siemens Biograph Vision PET system using NEMA NU 2-2018 standards.
• Simulated various isotopes (18F, 11C, 15O, 30P) and plant phantom properties.
• Analyzed the effect of a magnetic field on positron range effects.

Main Results:

• The GATE model showed good agreement with experimental data (sensitivity within 9%, NECR within 3%).
• Significant improvements in image quality were observed with a magnetic field for 15O (sixfold) and 11C (threefold).
• Positron range effects were quantified and methods for correction were explored.

Conclusions:

• GATE Monte Carlo simulation is a reliable tool for validating PET systems and understanding positron range effects.
• Magnetic field application shows potential for mitigating positron range effects in plant PET imaging.
• This research offers refined methodologies for precise PET plant imaging and integrated imaging techniques.