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A Geant4 simulation for three-dimensional proton imaging of microscopic samples

Abstract : Proton imaging can be carried out on microscopic samples by focusing the beam to a diameter ranging from a few micrometers down to a few tens of nanometers, depending on the required beam intensity and spatial resolution. Three-dimensional (3D) imaging by tomography is obtained from proton transmission (STIM: Scanning Transmission Ion Microscopy) and/or X-ray emission (PIXE: Particle Induced X-ray Emission). In these experiments, the samples are dehydrated for under vacuum analysis. In situ quantification of nanoparticles has been carried out at CENBG in the frame of nanotoxicology studies, on cells and small organisms used as biological models, especially on Caenorhabditis elegans (C. elegans) nematodes. Tomography experiments reveal the distribution of mass density and chemical content (in−3) within the analyzed volume. These density values are obtained using an inversion algorithm. To investigate the effect of this data reduction process, we defined different numerical phantoms, including a (dehydrated) C. elegans phantom whose geometry and density were derived from experimental data. A Monte Carlo simulation based on the Geant4 toolkit was developed. Using different simulation and reconstruction conditions, we compared the resulting tomographic images to the initial numerical reference phantom. A study of the relative error between the reconstructed and the reference images lead to the result that 20 protons per shot can be considered as an optimal number for 3D STIM imaging. Preliminary results for PIXE tomography are also presented, showing the interest of such numerical phantoms to produce reference data for future studies on X-ray signal attenuation in thick samples.
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Submitted on : Monday, November 4, 2019 - 11:41:44 AM
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Claire Michelet, Zhuxin Li, Wen Yang, Sébastien Incerti, Pascal Desbarats, et al.. A Geant4 simulation for three-dimensional proton imaging of microscopic samples. Physica Medica, Elsevier, 2019, 65, pp.172-180. ⟨10.1016/j.ejmp.2019.08.022⟩. ⟨hal-02281684⟩



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