Monte Carlo-based scatter correction for the plastic-based modular PET scanner J-PET.

Area of Science:

• Medical Imaging
• Nuclear Medicine
• Physics

Background:

• Positron Emission Tomography (PET) imaging is crucial for quantitative diagnostics.
• Scatter events in PET images degrade image quality and quantitative accuracy.
• The Jagiellonian PET (J-PET) scanner utilizes plastic scintillators, presenting unique challenges for scatter correction.

Purpose of the Study:

• To develop and evaluate a Monte Carlo (MC)-based scatter correction (SC) method for the J-PET scanner.
• To assess the impact of SC on image quality metrics and quantitative accuracy.
• To explore computational acceleration using surrogate materials in simulations.

Main Methods:

• Implemented an MC-based SC algorithm within a time-of-flight ordered-subsets expectation maximization (TOF-OSEM) reconstruction framework.
• Utilized SimSET for MC simulations.
• Evaluated the method using NEMA IQ phantom and human subject data on the J-PET scanner.
• Assessed LYSO crystals as a computational surrogate for BC-404 plastic scintillators in simulations.

Main Results:

• SC improved contrast recovery coefficients (CRC) by over 20% and reduced background variability (BGVar) by 8.5% in phantom studies.
• Residual activity in cold regions was reduced, and organ delineation was improved in human scans.
• Simulations with LYSO reduced runtime by nearly an order of magnitude with <6% deviation in image quality metrics compared to BC-404.
• Quantitative comparison with a commercial PET/CT scanner showed consistent activity concentration ratios, though J-PET exhibited higher noise and residual scatter.

Conclusions:

• The developed MC-based SC method effectively removes scatter for the J-PET scanner.
• The SC method enhances quantitative performance, enabling more accurate PET imaging.
• This work provides a foundation for advanced correction techniques and advances the J-PET scanner towards clinical applicability.