Monte Carlo Simulation of RPC-based PET with GEANT4

TL;DR

This paper uses GEANT4 simulations to explore how RPC-based detectors can be optimized for PET imaging by adjusting design parameters to improve detection efficiency while considering resolution and background levels.

Contribution

It systematically evaluates various design modifications for RPC-based PET detectors, providing insights into optimizing efficiency and resolution.

Findings

High-Z materials increase detection efficiency but reduce spatial resolution.

Multi-gap RPCs improve detection efficiency.

Trade-offs exist between efficiency, resolution, and background levels.

Abstract

The Resistive Plate Chambers (RPC) are low-cost charged-particle detectors with good timing resolution and potentially good spatial resolution. Using RPC as gamma detector provides an opportunity for application in positron emission tomography (PET). In this work, we use GEANT4 simulation package to study various methods improving the detection efficiency of a realistic RPC-based PET model for 511keV photons, by adding more detection units, changing the thickness of each layer, choosing different converters and using multi-gaps RPC (MRPC) technique. Proper balance among these factors are discussed. It's found that although RPC with materials of high atomic number can reach a higher efficiency, they may contribute to a poor spatial resolution and higher background level.