A quantitative assessment of Geant4 for predicting the yield and distribution of positron-emitting fragments in ion beam therapy

• DOI: 10.48550/arxiv.2402.03499
• Publication Date: 2024-02-05
• Authors: Andrew Chacon; Harley Rutherford; Akram Hamato; Munetaka Nitta; Fumihiko Nishikido; Yuma Iwao; Hideaki Tashima; Eiji Yoshida; Go Akamatsu; Sodai Takyu; Han Gyu Kang; Daniel Franklin; Katia Parodi; Taiga Yamaya; Anatoly Rosenfeld; Susanna Guatelli; Mitra Safavi‐Naeini
• Keywords: Phantoms, Imaging; FOS: Physical sciences; Electrons; Heavy Ion Radiotherapy; Computational Physics (physics.comp-ph); Physics - Medical Physics; 03 medical and health sciences; 0302 clinical medicine; Positron-Emission Tomography; Medical Physics (physics.med-ph); Physics - Computational Physics; Monte Carlo Method

Purpose: To compare the accuracy with which different hadronic inelastic physics models across ten Geant4 Monte Carlo simulation toolkit versions can predict positron-emitting fragments produced along beam path during carbon and oxygen ion therapy. Materials Methods: Phantoms of polyethylene, gelatin or poly(methyl methacrylate) were irradiated monoenergetic beams. Post-irradiation, 4D PET images acquired parent $^{11}$C, $^{10}$C $^{15}$O radionuclides contributions in each voxel determined from extracted time activity curves. Experiments simulated 10-11.1, three fragmentation models: binary cascade (BIC), quantum molecular dynamics (QMD) Liege intranuclear (INCL++) - 30 combinations. Total/parent isotope positron annihilation yields compared between simulations experiments using normalised mean squared error Pearson cross-correlation coefficient. Depth maximum/distal 50\% peak position yield also compared. Results: Performance varied considerably models, no one best predicting all fragments. BIC 10.2 provided overall agreement experimental results largest number test cases. QMD consistently estimates both depth (10.4 10.6) distal 50\%-of-peak point (10.2), while performed well INCL generally worst most versions. Conclusions: Best spatial prediction fragment production therapy was found to be 10.2.p03 QMD. These version/model combinations are recommended for future heavy research.