A comparative analysis of GEANT4, MCNP6 and FLUKA on proton-induced gamma-ray simulation.

Background: Precise range verification is essential in proton therapy to minimize treatment margins due to the steep dose fall-off of proton beams. The emission of secondary radiation from nuclear reactions between incident particles and tissues stands out as a promising method for range verification. Two prominent techniques are PET and Prompt Gamma-Ray Spectroscopy (PGS). PGS holds significant promise due to its real-time capability for range monitoring. This method allows for prompt detection and quantification of any disparities between planned and actual dose delivery, facilitating adaptive treatment strategies. Given the key role of Monte Carlo (MC) codes in understanding the PGS mechanisms during proton therapy, it is essential to address the current lack of validated codes covering the full energy spectrum of emitted gamma-rays.

Purpose: Addressing the need for precise range monitoring in proton therapy, our study aims to develop and validate MC codes for PGS. We focus on analyse MCNP6, GEANT4, and FLUKA codes, conducting rigorous validation process by comparing our simulation results with experimental data. Additionally, we propose optimal models and parameters to refine the accuracy of simulations for prompt gamma-ray (PG) spectra.

Methods: Various proton data libraries, models and cross-sections values were used in this study to simulate proton-induced gamma-rays in MCNP6, GEANT4 and FLUKA. To validate these simulations, PGS spectra of PMMA block irradiation were obtained with inorganic scintillator detector for different proton energies, raging from approximately to .

Results: GEANT4 was the only MC code capable of successfully reproducing PG lines, while the FLUKA aligned better with experimental data for mid-range energies. At higher energies, FLUKA overestimated the PG line ( ) at , whereas GEANT4 underestimated it; MCNP6 provided the closest match. Additionally, GEANT4, FLUKA, and MCNP6 failed to accurately reproduce the PG line ( ) at , consistent with previous findings. To address this limitation, a new model based on experimental and theoretical data from literature was developed.

Conclusions: This study emphasizes the need for updates to the data tables in MC simulations and underscores the importance of further theoretical and experimental research on PG de-excitation lines relevant to proton therapy. The newly developed model, designed to address discrepancies in the simulation of and de-excitation lines across different toolkits, successfully improved the accuracy of the oxygen de-excitation line, which was previously not well-reproduced.