Monte Carlo simulation of two Siemens Biograph PET/CT system using GATE: Image quality performance

Abstract

The utilization of Monte Carlo simulation is a highly effective method in advancing research within the field of nuclear medicine. An important software tool for simulating and modeling cutting-edge systems for Positron Emission Tomography (PET) is the Geant4 Application for Tomographic Emission (GATE). This research specifically concentrates on two Siemens PET scanners: the Siemens Biograph True point (True V) and Siemens Biograph mcT 20 excel. Our primary objective was to validate the GATE V8.2 simulation in accordance with the NEMA (National Electrical Manufacturers Association) NU 2-2018 protocol, using a parallel computing platform on a local cluster of computers. This cluster was managed by the open-source package TORQUE version 6.1.0, which is based on the original wrapper PBS.The results of this validation process for the Siemens Biograph True point (True V) scanner were highly promising. The scatter fraction (SF), peak noise equivalent count rate (NECR), and sensitivity all demonstrated a remarkable level of agreement, with deviations within 10.02%, 5.4%, and 1.57%, respectively. Additionally, the spatial resolution was found to deviate by less than 0.59 mm. Image evaluations demonstrate high-quality results for both Siemens Biograph True point (True V) and Siemens Biograph mcT 20 excel scanners, validating the GATE simulation. The study on acquisition time provides insights into optimizing computing simulation time.This research demonstrates the effectiveness of Monte Carlo simulation, facilitated by GATE, in accurately modeling advanced PET systems. The validation results affirm the reliability of GATE V8.2 in accordance with NEMA standards for the Siemens Biograph True point (True V) scanner. The high-quality images obtained from GATE-validated scanners underscore the potential of this simulation approach in advancing nuclear medicine research. Additionally, the study on acquisition time provides valuable considerations for optimizing simulation efficiency.