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192 results on '"Jean Michel Létang"'

1. Prompt gamma energy integration: a new method for online-range verification in proton therapy with pulsed-beams

Author

Pierre Everaere, Denis Dauvergne, Marie-Laure Gallin-Martel, Joël Hérault, Ayoub Koudia, Charbel Koumeir, Jean Michel Létang, and Étienne Testa

Subjects
prompt-gamma, particle therapy, range verification, Monte Carlo simulations, integral method, Physics, QC1-999
Abstract

Introduction: We propose a method for prompt-gamma verification of proton range during particle therapy, called Prompt-Gamma Energy Integration (PGEI).Method: This method is based on the measurement of the total energy deposited in a set of detectors located around a patient. It is particularly suited in the case of high-instantaneous beam intensities, like for pulsed beams extracted from a synchro-cyclotron. GATE simuations were used to evaluate the sensitivity, and dedicated scintillators were tested as a function of beam intensity.Results and discussion: Simulations show that millimetric range shifts can be measured at a beam-spot scale. The sensitivity is slightly degraded as compared to the Prompt-Gamma Peak Integration Method, for which Time-of-Flight can be employed to reduce the background in single-photon detection conditions at cyclotron accelerators. Experimentally, lead tungstate scintillators have shown to cope with the high instantaneous gamma count rates for PGEI at synchro-cyclotrons.

Published
2024
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2. Combining Wave and Particle Effects in the Simulation of X-ray Phase Contrast—A Review

Author

Emilie Pietersoone, Jean Michel Létang, Simon Rit, Emmanuel Brun, and Max Langer

Subjects
X-ray imaging, phase contrast, simulation, Monte Carlo, diffraction, refraction, Physics, QC1-999, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

X-ray phase-contrast imaging (XPCI) is a family of imaging techniques that makes contrast visible due to phase shifts in the sample. Phase-sensitive techniques can potentially be several orders of magnitude more sensitive than attenuation-based techniques, finding applications in a wide range of fields, from biomedicine to materials science. The accurate simulation of XPCI allows for the planning of imaging experiments, potentially reducing the need for costly synchrotron beam access to find suitable imaging parameters. It can also provide training data for recently proposed machine learning-based phase retrieval algorithms. The simulation of XPCI has classically been carried out using wave optics or ray optics approaches. However, these approaches have not been capable of simulating all the artifacts present in experimental images. The increased interest in dark-field imaging has also prompted the inclusion of scattering in XPCI simulation codes. Scattering is classically simulated using Monte Carlo particle transport codes. The combination of the two perspectives has proven not to be straightforward, and several methods have been proposed. We review the available literature on the simulation of XPCI with attention given to particular methods, including the scattering component, and discuss the possible future directions for the simulation of both wave and particle effects in XPCI.

Published
2024
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3. Characterization of internal fatigue cracks in aluminum alloys by simulation of phase contrast tomography

Author

Ce Xiao, Jean Michel Létang, and Jean-Yves Buffière

Subjects
Medicine, Science
Abstract

Abstract Synchrotron Radiation Computed Tomography (SRCT) allows a better detection of fatigue cracks in metals than laboratory CT due to the existence of phase contrast. However the presence in reconstructed images of fringes at the edges of objects generated by Fresnel diffraction makes it difficult to identify and analyze the cracks quantitatively. Simulations of phase contrast synchrotron tomography images containing cracks with different sizes and shapes are obtained by using GATE software. Analyzing the simulation results, firstly, we confirmed that the bright parts with strong contrast in SRCT image are streak artifacts; secondly, we found that the gray scale values within the cracks in SRCT images are related to the crack size; these simulation results are used to analyse SRCT images of internal fatigue cracks in a cast Al alloy, providing a clearer visualisation of damage.

Published
2022
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6. Artificial Intelligence for Monte Carlo Simulation in Medical Physics

Author

David Sarrut, Ane Etxebeste, Enrique Muñoz, Nils Krah, and Jean Michel Létang

Subjects
AI, Monte Carlo simulation, medical physics, GAN, deep learning, Physics, QC1-999
Abstract

Monte Carlo simulation of particle tracking in matter is the reference simulation method in the field of medical physics. It is heavily used in various applications such as 1) patient dose distribution estimation in different therapy modalities (radiotherapy, protontherapy or ion therapy) or for radio-protection investigations of ionizing radiation-based imaging systems (CT, nuclear imaging), 2) development of numerous imaging detectors, in X-ray imaging (conventional CT, dual-energy, multi-spectral, phase contrast … ), nuclear imaging (PET, SPECT, Compton Camera) or even advanced specific imaging methods such as proton/ion imaging, or prompt-gamma emission distribution estimation in hadrontherapy monitoring. Monte Carlo simulation is a key tool both in academic research labs as well as industrial research and development services. Because of the very nature of the Monte Carlo method, involving iterative and stochastic estimation of numerous probability density functions, the computation time is high. Despite the continuous and significant progress on computer hardware and the (relative) easiness of using code parallelisms, the computation time is still an issue for highly demanding and complex simulations. Hence, since decades, Variance Reduction Techniques have been proposed to accelerate the processes in a specific configuration. In this article, we review the recent use of Artificial Intelligence methods for Monte Carlo simulation in medical physics and their main associated challenges. In the first section, the main principles of some neural networks architectures such as Convolutional Neural Networks or Generative Adversarial Network are briefly described together with a literature review of their applications in the domain of medical physics Monte Carlo simulations. In particular, we will focus on dose estimation with convolutional neural networks, dose denoising from low statistics Monte Carlo simulations, detector modelling and event selection with neural networks, generative networks for source and phase space modelling. The expected interests of those approaches are discussed. In the second section, we focus on the current challenges that still arise in this promising field.

Published
2021
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7. On the Role of Single Particle Irradiation and Fast Timing for Efficient Online-Control in Particle Therapy

Author

Denis Dauvergne, Oreste Allegrini, Cairo Caplan, Xiushan Chen, Sébastien Curtoni, Ane Etxebeste, Marie-Laure Gallin-Martel, Maxime Jacquet, Jean Michel Létang, Jayde Livingstone, Sara Marcatili, Christian Morel, Étienne Testa, and Yannick Zoccarato

Subjects
particle therapy, range verification, prompt-gamma, proton radiography, proton interaction vertex imaging, time-of-flight, Physics, QC1-999
Abstract

Within the frame of the CLaRyS collaboration, we discuss the assets of using a reduced-intensity in vivo treatment control phase during one or a few beam spots at the beginning of a particle therapy session. By doing so we can improve considerably the conditions for secondary radiation detection and particle radiography. This also makes Time-of-Flight (ToF) resolutions of 100 ps rms feasible for both the transmitted particles and secondary radiations, by means of a single-projectile counting mode using a beam-tagging monitor with time and position registration. This opens up new perspectives for prompt-gamma timing and Compton imaging for range verification. ToF-based proton computed tomography (CT) and ToF-assisted secondary proton vertex imaging in carbon therapy are also discussed, although for the latter, no evidence of any benefit at small observation angles is anticipated. The reduction of the beam intensity during one or a few spots on the various accelerators for particle therapy should not significantly reduce the patient workflow.

Published
2020
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8. Deriving the mean excitation energy map from dual-energy and proton computed tomography

Author

Gloria Vilches-Freixas, Catherine Therese Quiñones, Jean Michel Létang, and Simon Rit

Subjects
Medical physics. Medical radiology. Nuclear medicine, R895-920, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

The mean excitation energy, I, is an essential quantity for proton treatment planning. This work investigated the feasibility of extracting the spatial distribution of I by combining two computed tomography (CT) modalities, dual-energy CT and proton CT, which provided the spatial distribution of the relative electron density and the stopping power relative to water, respectively. We provided the analytical derivation of I as well as its uncertainty. Results were validated on simulated X-ray and proton CT images of a digital anthropomorphic phantom. Accuracy was below 15% with a large uncertainty, which demonstrated the potential and limits of the technique. Keywords: Proton CT, Dual-energy CT, Mean excitation energy

Published
2018
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9. Comparison of projection- and image-based methods for proton stopping power estimation using dual energy CT

Author

Gloria Vilches-Freixas, Vicki Trier Taasti, Ludvig Paul Muren, Jørgen Breede Baltzer Petersen, Jean Michel Létang, David Christoffer Hansen, and Simon Rit

Subjects
Medical physics. Medical radiology. Nuclear medicine, R895-920, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Background and Purpose: Several strategies for estimating stopping power ratio (SPR) from dual-energy CT (DECT) have been proposed to improve accuracy of proton dose calculations. DECT methods can mainly be categorized into projection-based methods, where material decomposition is performed prior to image reconstruction, and image-based methods, where decomposition takes place after image reconstruction. With the advent of photon-counting and dual-layer technology, projection-based methods could be considered for SPR estimation. In this simulation-based study we compared the SPR accuracy of one projection- and three image-based DECT methods. Materials and Methods: X-ray CT projections of the female ICRP phantom were simulated using two different X-ray spectra with a realistic detector response and noise levels. ICRP slices at four different locations were selected. Reference SPR-maps were computed at 200 MeV. The SPR comparison was based on percentage deviation inside ROIs and relative range errors calculated with Radon transform of difference maps. Results: SPR root-mean-square errors (RMSE) over the selected ROIs were 0.54% for the projection-based method and 0.68%, 0.61% and 0.70% for the three image-based methods. The RMSE for the relative range errors were slightly smaller for the projection-based approach, but close to zero for all decomposition domains as positive and negative errors averaged out over the slice. Conclusions: SPR estimations with the projection-based method produced slightly better results (though not statistically significant) than the three image-based methods used in this simulation-based study, therefore, with the advent of technological developments, projection-based methods could be considered for SPR estimation if projection data is available. Keywords: CT noise, Dual-energy CT, Proton stopping power ratio, Range uncertainty, Robustness

Published
2017
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18. Neutron elastic scattering kernel for Monte Carlo next-event estimators in Tripoli-4®

Author

Henri Hutinet, Cindy Le Loirec, Davide Mancusi, Jean Michel Létang, Abdallah Lyoussi, Service de Physique des Réacteurs et du Cycle (SPRC), Département Etude des Réacteurs (DER), CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Service d’Études des Réacteurs et de Mathématiques Appliquées (SERMA), Département de Modélisation des Systèmes et Structures (DM2S), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Léon Bérard [Lyon], and Service Physique EXpérimentale, d'essais en Sûreté et d'Instrumentation (SPESI)

Subjects
[PHYS]Physics [physics], Fluid Flow and Transfer Processes, General Physics and Astronomy
Abstract

International audience

Published
2023
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19. Monte Carlo simulations of nanodosimetry and radiolytic species production for monoenergetic proton and electron beams: Benchmarking of GEANT4‐DNA and LPCHEM codes

Author

Yasmine Ali, Lucas Auzel, Caterina Monini, Kateryna Kriachok, Jean Michel Létang, Etienne Testa, Lydia Maigne, Michael Beuve, Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and ANR-11-LABX-0063,PRIMES,Physique, Radiobiologie, Imagerie Médicale et Simulation(2011)

Subjects
Ions, Benchmarking, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Water, Computer Simulation, Electrons, DNA, General Medicine, Protons, Monte Carlo Method, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Abstract

International audience; PurposeIn hadrontherapy, biophysical models can be used to predict the biological effect received by cancerous tissues and organs at risk. The input data of these models generally consist of information on nano/micro dosimetric quantities and, concerning some models, reactive species produced in water radiolysis. In order to fully account for the radiation stochastic effects, these input data have to be provided by Monte Carlo track structure (MCTS) codes allowing to estimate physical, physico-chemical and chemical effects of radiation at the molecular scale. The objective of this study is to benchmark two MCTS codes, Geant4-DNA and LPCHEM, that are useful codes for estimating the biological effects of ions during radiation therapy treatments.Material and methodsIn this study we considered the simulation of specific energy spectra for monoenergetic proton beams (10 MeV) as well as radiolysis species production for both electron (1 MeV) and proton (10 MeV) beams with Geant4-DNA and LPCHEM codes. Options 2, 4 and 6 of the Geant4-DNA physics lists have been benchmarked against LPCHEM. We compared probability distributions of energy transfer points in cylindrical nanometric targets (10 nm) positioned in a liquid water box. Then, radiochemical seconds after irradiation are compared.ResultsOverall, the specific energy spectra and the chemical yields obtained by the two codes are in good agreement considering the uncertainties on experimental data used to calibrate the parameters of the MCTS codes. For 10 MeV proton beams, ionization and excitation processes are the major contributors to the specific energy deposition (larger than 90 %) while attachment, solvation and vibration processes are minor contributors. LPCHEM simulates tracks with slightly more concentrated energy depositions than Geant4-DNA which translates into slightly faster recombination than Geant4-DNA. Relative deviations (CEV) in respect to the average of evolution rates of the radical yields between 10−12 and 10−6 s remain below 10%. When comparing execution times between the codes, we showed that LPCHEM is faster than Geant4-DNA by a factor of about 4 for 1000 primary particles in all simulation stages (physical, physico-chemical and chemical). In multi-thread mode (4 threads), Geant4-DNA computing times are reduced but remain slower than LPCHEM by ∼20% up to ∼50%.ConclusionsFor the first time, the entire physical, physicochemical and chemical models of two track structure Monte Carlo codes have been benchmarked along with an extensive analysis on the effects on the water radiolysis simulation. This study opens up new perspectives in using specific energy distributions and radiolytic species yields from monoenergetic ions in biophysical models integrated to Monte Carlo software.

Published
2022
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21. Modeling families of particle distributions with conditional GAN for Monte Carlo SPECT simulations

Author

Albert Saporta, Ane Etxebeste, Théo Kaprelian, Jean Michel Létang, and David Sarrut

Subjects
Tomography, Emission-Computed, Single-Photon, Radiological and Ultrasound Technology, Phantoms, Imaging, Radiology, Nuclear Medicine and imaging, Computer Simulation, Monte Carlo Method
Abstract

Objective. We propose a method to model families of distributions of particles exiting a phantom with a conditional generative adversarial network (condGAN) during Monte Carlo simulation of single photon emission computed tomography imaging devices. Approach. The proposed condGAN is trained on a low statistics dataset containing the energy, the time, the position and the direction of exiting particles. In addition, it also contains a vector of conditions composed of four dimensions: the initial energy and the position of emitted particles within the phantom (a total of 12 dimensions). The information related to the gammas absorbed within the phantom is also added in the dataset. At the end of the training process, one component of the condGAN, the generator (G), is obtained. Main results. Particles with specific energies and positions of emission within the phantom can then be generated with G to replace the tracking of particle within the phantom, allowing reduced computation time compared to conventional Monte Carlo simulation. Significance. The condGAN generator is trained only once for a given phantom but can generate particles from various activity source distributions.

Published
2022

22. Imaging of polychromatic sources through Compton spectral reconstruction

Author

Enrique Muñoz, Ane Etxebeste, Denis Dauvergne, Jean Michel Létang, David Sarrut, Voichita Maxim, and Etienne Testa

Subjects
Diagnostic Imaging, Photons, Radiological and Ultrasound Technology, Phantoms, Imaging, Image Processing, Computer-Assisted, Radiology, Nuclear Medicine and imaging, Monte Carlo Method, Algorithms
Abstract

Objective. Study the performance of a spectral reconstruction method for Compton imaging of polychromatic sources and compare it to standard Compton reconstruction based on the selection of photopeak events. Approach. The proposed spectral and the standard photopeak reconstruction methods are used to reconstruct images from simulated sources emitting simultaneously photons of 140, 245, 364 and 511 keV. Data are simulated with perfect and realistic energy resolutions and including Doppler broadening. We compare photopeak and spectral reconstructed images both qualitatively and quantitatively by means of activity recovery coefficient and spatial resolution. Main results. The presented method allows improving the images of polychromatic sources with respect to standard reconstruction methods. The main reasons for this improvement are the increase of available statistics and the reduction of contamination from higher initial photon energies. The reconstructed images present lower noise, higher activity recovery coefficient and better spatial resolution. The improvements become more sensible as the energy resolution of the detectors decreases. Significance. Compton cameras have been studied for their capability of imaging polychromatic sources, thus allowing simultaneous imaging of multiple radiotracers. In such scenarios, Compton images are conventionally reconstructed for each emission energy independently, selecting only those measured events depositing a total energy within a fixed window around the known emission lines. We propose to employ a spectral image reconstruction method for polychromatic sources, which allows increasing the available statistics by using the information from events with partial energy deposition. The detector energy resolution influences the energy window used to select photopeak events and therefore the level of contamination by higher energies. The spectral method is expected to have a more important impact as the detector resolution worsens. In this paper we focus on energy ranges from nuclear medical imaging and we consider realistic energy resolutions.

Published
2022

23. Scatter Correction for Spectral CT Using a Primary Modulator Mask

Author

Joachim Tabary, Jean Michel Létang, Clarisse Fournier, Odran Pivot, Simon Rit, Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Rit, Simon, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Statistical noise, media_common.quotation_subject, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Scatter correction, Radiation, 030218 nuclear medicine & medical imaging, Spectral CT, 03 medical and health sciences, Matrix (mathematics), 0302 clinical medicine, Optics, Approximation error, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Scattering, Radiation, Contrast (vision), Electrical and Electronic Engineering, media_common, Physics, Photons, Radiological and Ultrasound Technology, Phantoms, Imaging, business.industry, Primary modulator mask, Detector, Function (mathematics), Photon counting, Computer Science Applications, Photon counting detectors, Artifacts, Tomography, X-Ray Computed, business, Algorithms, Software
Abstract

International audience; The problem of scattered radiation correction in computed tomography (CT) is well known because scatter induces a bias, a loss of contrast and artifacts. Numerous strategies have been proposed in conventional CT (using energy-integrating detectors) but the problem is still open in the field of spectral CT, a new imaging technique based on energy-selective photon counting detectors. The aim of the present study is to introduce a scatter correction method adapted to multi-energy imaging and based on the use of a primary modulator mask. The main contributions are a correction matrix, which compensates for the effect of the mask, a scatter model based on B-splines and a cost function based on the mask structures and robust to the object structures. The performances of the method have been evaluated on both simulated and experimental data. The mean relative error was reduced from 20% in the lower energy-bins without correction to 4% with the proposed technique, which is close to the error caused by statistical noise.

Published
2020
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24. Use of fast realistic simulations on GPU to extract CAD models from microtomographic data in the presence of strong CT artefacts

Author

Franck Vidal, Jean Michel Létang, Iwan T. Mitchell, Bangor University, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Computer science, CAD, Numerical simulation, Evolutionary computation, 01 natural sciences, 030218 nuclear medicine & medical imaging, 010309 optics, 03 medical and health sciences, 0302 clinical medicine, High fidelity, 0103 physical sciences, X-rays, Computer vision, Optimisation, Computed tomography, Impulse response, Computer simulation, Computer aided analysis, business.industry, Detector, General Engineering, Process (computing), Image segmentation, [INFO.INFO-IA]Computer Science [cs]/Computer Aided Engineering, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Artificial intelligence, High performance computing, business
Abstract

International audience; The presence of strong imaging artefacts in microtomographic X-ray data makes the CAD modelling process difficult to carry out. As an alternative to traditional image segmentation techniques, we propose to register the CAD models by deploying a realistic X-ray simulation on GPU in an optimisation framework. A user study was also conducted to compare the measurements made manually by a cohort of volunteers and those produced with our framework. Our implementation relies on open source software only. We numerically modelled the real experiment, taking into account geometrical properties as well as beam hardening, impulse response of the detector, phase contrast, and photon noise. Parameters of the overall model are then optimised so that X-ray projections of the registered the CAD models match the projections from an actual experiment. It appeared that manual measurements can be variable and subject to bias whereas our framework produced more reliable results. The features seen in the real CT image, including artefacts, were accurately replicated in the CT image reconstructed from the simulated data after registration: (i) linear attenuation coefficients are comparable for all the materials, (ii) geometrical properties are accurately recovered, and (iii) simulated images reproduce observed experimental artefacts. We showed that the choice of objective function is crucial to produce high fidelity results. We also demonstrated how to automatically produce CAD models as an optimisation problem, producing a high cross-correlation between the experimental CT slice and the simulated CT slice. These results pave the way towards the use of fast realistic simulation for accurate CAD modelling in tomographic X-ray data

Published
2022
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25. Characterization of Internal Fatigue Cracks in Aluminum Alloys by Simulation of Phase Contrast Tomography

Author

Ce, Xiao, Jean Michel, Létang, and Jean-Yves, Buffière

Subjects
Multidisciplinary, Alloys, Humans, Stress, Mechanical, Tomography, X-Ray Computed, Tomography, Aluminum
Abstract

Synchrotron Radiation Computed Tomography (SRCT) allows a better detection of fatigue cracks in metals than laboratory CT due to the existence of phase contrast. However the presence in reconstructed images of fringes at the edges of objects generated by Fresnel diffraction makes it difficult to identify and analyze the cracks quantitatively. Simulations of phase contrast synchrotron tomography images containing cracks with different sizes and shapes are obtained by using GATE software. Analyzing the simulation results, firstly, we confirmed that the bright parts with strong contrast in SRCT image are streak artifacts; secondly, we found that the gray scale values within the cracks in SRCT images are related to the crack size; these simulation results are used to analyse SRCT images of internal fatigue cracks in a cast Al alloy, providing a clearer visualisation of damage.

Published
2021
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26. Evaluation of simulators for x-ray speckle-based phase contrast imaging

Author

Max Langer, Jean Michel Létang, Laurène Quénot, Emmanuel Brun, Synchrotron Radiation for Biomedicine = Rayonnement SynchroTROn pour la Recherche BiomédicalE (STROBE), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Rayet, Béatrice

Subjects
Computer science, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Monte Carlo method, X-ray Phase Contrast Imaging, 01 natural sciences, 030218 nuclear medicine & medical imaging, 010309 optics, 03 medical and health sciences, Speckle pattern, 0302 clinical medicine, Optics, Speckle based Imaging, 0103 physical sciences, Radiology, Nuclear Medicine and imaging, Computer Simulation, Monte-Carlo Simulations, Radiological and Ultrasound Technology, business.industry, Scattering, X-Rays, Phase-contrast imaging, Experimental data, Ranging, Refraction, Radiography, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, X-Ray Phase-Contrast Imaging, business, Monte Carlo Method, Synchrotrons
Abstract

International audience; X-ray phase contrast imaging (PCI) denotes a group of highly sensitive imaging techniques that permits imaging at scales ranging from nanoscopic to the medical. Recently introduced, speckle-based imaging has seen a rapid development because of its experimental simplicity and its capability to retrieve the refraction, the scattering and the absorption of a sample using a conventional X-ray set-up. Precise simulation would permit to optimise the imaging setups for different applications, but until now works on simulation of X-ray speckle-based phase contrast imaging have been very few. In this work we evaluate different simulation codes, based on Monte-Carlo, analytical ray-tracing and wave-optics Fresnel propagation. The simulation results are compared to both synchrotron and conventional imaging experiments to permits their validation. We obtain a strong similarity between simulated and experimental data. We discuss the validity and applicability of each approach.

Published
2021
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31. Relative stopping power resolution in time-of-flight proton CT

Author

Nils Krah, Denis Dauvergne, Jean Michel Létang, Simon Rit, Étienne Testa, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Rit, Simon, Imagerie Tomographique et Radiothérapie, Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[PHYS]Physics [physics], Physics - Instrumentation and Detectors, Radiological and Ultrasound Technology, Phantoms, Imaging, Physics::Instrumentation and Detectors, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, FOS: Physical sciences, Instrumentation and Detectors (physics.ins-det), Helium, Physics - Medical Physics, [PHYS] Physics [physics], [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Image Processing, Computer-Assisted, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Radiology, Nuclear Medicine and imaging, Medical Physics (physics.med-ph), [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Protons, Tomography, X-Ray Computed, Nuclear Experiment, Monte Carlo Method
Abstract

Objective. Proton computed tomography (CT) is similar to x-ray CT but relies on protons rather than photons to form an image. In its most common operation mode, the measured quantity is the amount of energy that a proton has lost while traversing the imaged object from which a relative stopping power map can be obtained via tomographic reconstruction. To this end, a calorimeter which measures the energy deposited by protons downstream of the scanned object has been studied or implemented as energy detector in several proton CT prototypes. An alternative method is to measure the proton’s residual velocity and thus its kinetic energy via the time of flight (TOF) between at least two sensor planes. In this work, we study the RSP resolution, seen as image noise, which can be expected from TOF proton CT systems. Approach. We rely on physics models on the one hand and statistical models of the relevant uncertainties on the other to derive closed form expressions for the noise in projection images. The TOF measurement error scales with the distance between the TOF sensor planes and is reported as velocity error in ps/m. We use variance reconstruction to obtain noise maps of a water cylinder phantom given the scanner characteristics and additionally reconstruct noise maps for a calorimeter-based proton CT system as reference. We use Monte Carlo simulations to verify our model and to estimate the noise due to multiple Coulomb scattering inside the object. We also provide a comparison of TOF helium and proton CT. Main results. We find that TOF proton CT with 30 ps m−1 velocity error reaches similar image noise as a calorimeter-based proton CT system with 1% energy error (1 sigma error). A TOF proton CT system with a 50 ps m−1 velocity error produces slightly less noise than a 2% calorimeter system. Noise in a reconstructed TOF proton CT image is spatially inhomogeneous with a marked increase towards the object periphery. Our modelled noise was consistent with Monte Carlo simulated images. TOF helium CT offers lower RSP noise at equal fluence, but is less advantageous at equal imaging dose. Significance. This systematic study of image noise in TOF proton CT can serve as a guide for future developments of this alternative solution for estimating the residual energy of protons and helium ions after the scanned object.

Published
2022
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33. Modeling complex particles phase space with GAN for Monte Carlo SPECT simulations: a proof of concept

Author

David Sarrut, A. Etxebeste, Jean Michel Létang, Nils Krah, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), HEP, INSPIRE, Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Computer science, Computation, Monte Carlo method, Physics::Medical Physics, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Single-photon emission computed tomography, Tracking (particle physics), 030218 nuclear medicine & medical imaging, [PHYS] Physics [physics], 03 medical and health sciences, 0302 clinical medicine, Neoplasms, medicine, Humans, Radiology, Nuclear Medicine and imaging, Computer Simulation, [PHYS]Physics [physics], Tomography, Emission-Computed, Single-Photon, Radiological and Ultrasound Technology, Artificial neural network, medicine.diagnostic_test, Phantoms, Imaging, Detector, Proof of concept, 030220 oncology & carcinogenesis, Phase space, Particle, Tomography, Neural Networks, Computer, Tomography, X-Ray Computed, Algorithm, Monte Carlo Method
Abstract

A method is proposed to model by a generative adversarial network the distribution of particles exiting a patient during Monte Carlo simulation of emission tomography imaging devices. The resulting compact neural network is then able to generate particles exiting the patient, going towards the detectors, avoiding costly particle tracking within the patient. As a proof of concept, the method is evaluated for single photon emission computed tomography (SPECT) imaging and combined with another neural network modeling the detector response function (ARF-nn). A complete rotating SPECT acquisition can be simulated with reduced computation time compared to conventional Monte Carlo simulation. It also allows the user to perform simulations with several imaging systems or parameters, which is useful for imaging system design.

Published
2021
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34. Influence of sub-nanosecond time of flight resolution for online range verification in proton therapy using the line-cone reconstruction in Compton imaging

Author

M.-L. Gallin-Martel, A. Etxebeste, David Sarrut, Brent Huisman, Denis Dauvergne, Jean Michel Létang, E. Testa, Jayde Livingstone, Mattia Fontana, Sara Marcatili, Rayet, Béatrice, Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Diagnostic Imaging, Iterative reconstruction, Scintillator, Imaging phantom, Collimated light, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Optics, Image Processing, Computer-Assisted, Proton Therapy, Radiology, Nuclear Medicine and imaging, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Proton therapy, ComputingMilieux_MISCELLANEOUS, Physics, [PHYS.PHYS.PHYS-MED-PH] Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Radiological and Ultrasound Technology, Phantoms, Imaging, business.industry, Detector, Time of flight, Gamma Rays, [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], 030220 oncology & carcinogenesis, Temporal resolution, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], business, Monte Carlo Method
Abstract

Online ion range monitoring in hadron therapy can be performed via detection of secondary radiation, such as prompt γ-rays, emitted during treatment. The prompt γ emission profile is correlated with the ion depth-dose profile and can be reconstructed via Compton imaging. The line-cone reconstruction, using the intersection between the primary beam trajectory and the cone reconstructed via a Compton camera, requires negligible computation time compared to iterative algorithms. A recent report hypothesised that time of flight (TOF) based discrimination could improve the precision of the γ fall-off position measured via line-cone reconstruction, where TOF comprises both the proton transit time from the phantom entrance until γ emission, and the flight time of the γ-ray to the detector. The aim of this study was to implement such a method and investigate the influence of temporal resolution on the precision of the fall-off position. Monte Carlo simulations of a 160 MeV proton beam incident on a homogeneous PMMA phantom were performed using GATE. The Compton camera consisted of a silicon-based scatterer and CeBr3 scintillator absorber. The temporal resolution of the detection system (absorber + beam trigger) was varied between 0.1 and 1.3 ns RMS and a TOF-based discrimination method applied to eliminate unlikely solution(s) from the line-cone reconstruction. The fall-off position was obtained for varying temporal resolutions and its precision obtained from its shift across 100 independent γ emission profiles compared to a high statistics reference profile. The optimal temporal resolution for the given camera geometry and 108 primary protons was 0.2 ns where a precision of 2.30 ± 0.15 mm (1σ) on the fall-off position was found. This precision is comparable to current state of-the-art Compton imaging using iterative reconstruction methods or 1D imaging with mechanically collimated devices, and satisfies the requirement of being smaller than the clinical safety margins.

Published
2021
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35. Energy-adaptive calculation of the most likely path in proton CT

Author

Etienne Testa, Denis Dauvergne, Jean Michel Létang, Nils Krah, Simon Rit, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), and Krah, Nils

Subjects
Computer science, Computer Science::Neural and Evolutionary Computation, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Polynomial and rational function modeling, Software, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Radiology, Nuclear Medicine and imaging, Image resolution, [PHYS.PHYS.PHYS-MED-PH] Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Radiological and Ultrasound Technology, Phantoms, Imaging, business.industry, Function (mathematics), Expression (mathematics), Power (physics), 030220 oncology & carcinogenesis, Computer Science::Computer Vision and Pattern Recognition, Path (graph theory), [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Protons, Tomography, X-Ray Computed, business, Monte Carlo Method, Algorithm, Algorithms, Energy (signal processing)
Abstract

International audience; This note addresses an issue faced by every proton computed tomography (CT) reconstruction software: the modelling and the parametrisation of the multiple Coulomb scattering power for the estimation of the most likely path of each proton. The conventional approach uses a polynomial model parameterised as a function of depth for a given initial beam energy. This makes it cumbersome to implement a software that works for proton CT data acquired with an arbitrary beam energy or with energy modulation during acquisition. We propose a simple way to parametrise the scattering power based on the measured proton CT list-mode data only and derive a compact expression for the most likely path (MLP) based on a conventional MLP model. Our MLP does not require any parameter. The method assumes the imaged object to be homogeneous, as most conventional MLPs, but requires no information about the material as opposed to most conventional MLP expressions which often assume water to infer energy loss. Instead, our MLP automatically adapts itself to the energy-loss which actually occurred in the object and which is one of the measurements required for proton CT reconstruction. We validate our MLP method numerically and find excellent agreement with conventional MLP methods. We propose a simple way to parametrise the scattering power based on the measured proton CT list-mode data only and derive a compact expression for the MLP. Our MLP does not require any parameter. The method assumes the imaged object to be homogeneous, as most conventional MLPs, but makes no assumption about the kind of material as opposed to most conventional MLP expressions which generally assume water. Instead, our MLP automatically adapts itself to the energy-loss which actually occurred in the object and which is one of the measurements required for proton CT reconstruction. Our results indicate that this might improve spatial resolution in proton CT images of objects which are significantly different from water, e.g.~the lungs. We validate our MLP method numerically and find excellent agreement with conventional MLP methods.

Published
2021
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36. A time-of-flight-based reconstruction for real-time prompt-gamma imaging in proton therapy

Author

Laurent Gallin-Martel, Daniel Maneval, Yannick Boursier, Sara Marcatili, Jean-François Muraz, Christian Morel, Jean-Luc Bouly, M. Dupont, M.-L. Gallin-Martel, Joel Herault, Etienne Testa, Maxime Jacquet, Denis Dauvergne, Jean Michel Létang, Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Imagerie Tomographique et Radiothérapie, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)

Subjects
Diagnostic Imaging, Proton, FOS: Physical sciences, Iterative reconstruction, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Optics, Proton Therapy, Radiology, Nuclear Medicine and imaging, Proton therapy, Physics, [PHYS]Physics [physics], Radiological and Ultrasound Technology, Pixel, business.industry, Phantoms, Imaging, Detector, Physics - Medical Physics, Time of flight, Transverse plane, Gamma Rays, 030220 oncology & carcinogenesis, Physics::Accelerator Physics, Medical Physics (physics.med-ph), Protons, business, Monte Carlo Method, Beam (structure)
Abstract

We are currently conceiving, through (MC) simulation, a multi-channel gamma detector array (TIARA for Time-of-flight Imaging ARrAy) for the online monitoring of protontherapy treatments. By measuring the Time-Of-Flight (TOF) between a beam monitor placed upstream and the Prompt-Gamma (PG) detector, our goal is to reconstruct the PG vertex distribution to detect a possible deviation of proton beam delivery. In this paper, two non-iterative reconstruction strategies are proposed. The first is based on the resolution of an analytical formula describing the PG vertex distribution in 3D. Here, it was resolved under a one-dimensional approximation in order to measure a potential proton range shift along the beam direction. The second is based on the calculation of the Centre-Of-Gravity (COG) of the TIARA pixel detectors counts and also provides 3D information on a possible beam displacement. The PG vertex reconstruction was evaluated in two different scenarios. A coincidence time resolution of 100 ps (rms) can be attained in single proton regime (operating a reduction of the beam current) and using an external beam monitor to provide a start trigger for the TOF measurement. Under these conditions, MC simulations have shown that a millimetric proton range shift sensitivity can be achieved at 2$\sigma$ with 10$^{8}$ incident protons. This level of accuracy would allow to act in real-time if the treatment does not conform to treatment plan. A worst case scenario of a 1 ns (rms) TOF resolution was also considered to demonstrate that a degraded timing information can be compensated by increasing the acquisition statistics: in this case, a 2 mm range shift would be detectable at 2$\sigma$ with 10$^{9}$ incident protons. The COG method has shown excellent capabilities of detecting lateral beam displacements: a 2 mm sensitivity was found at 2$\sigma$ with 10$^{8}$ incident protons.

Published
2021
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37. Region-of-Interest CT Reconstruction using Object Extent and Singular Value Decomposition

Author

Rolf Clackdoyle, S. Rit, Aurelien Coussat, Michel Defrise, Jean Michel Létang, Laurent Desbat, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Gestes Medico-chirurgicaux Assistés par Ordinateur (TIMC-GMCAO), Translational Innovation in Medicine and Complexity / Recherche Translationnelle et Innovation en Médecine et Complexité - UMR 5525 (TIMC ), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Vrije Universiteit Brussel (VUB), Supporting clinical sciences, and Medical Imaging

Subjects
Inverse problems, Convex hull, Computer tomography, Iterative reconstruction, Atomic and Molecular Physics, and Optics, Projection (linear algebra), Singular value, symbols.namesake, Conjugate gradient method, Image reconstruction, Singular value decomposition, symbols, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Radiology, Nuclear Medicine and imaging, Truncated data, Truncation (statistics), Hilbert transform, Computed tomography, Instrumentation, Algorithm, Mathematics
Abstract

International audience; In computed tomography, a whole scan of the object may be impossible, generally because the object is larger than the scanner field-of-view. Such a set up leads to truncated projections. Using differentiated backprojection, the reconstruction problem can be reduced to a set of one-dimensional problems consisting of the inversion of the Hilbert transform. When the object partly overlaps the scanner field-of-view, this problem is commonly referred to as the "one-sided truncated Hilbert transform". Our work investigates this situation and proposes a novel approach to address it. Using differentiated backprojection, and the object extent supposedly known a priori, a pseudo-inverse of the truncated Hilbert transform is computed by truncated singular value decomposition, and its truncated singular values are replaced by a simple estimation. The estimation is calculated using the singular value decomposition of the known convex hull filled with a constant value per line computed from the corresponding projection in the direction of the Hilbert transform. Experiments illustrate the image quality improvements resulting from this approach compared to a simple truncation of the singular values and the reconstruction speed improvement compared to two-dimensional iterative reconstruction solving penalized least squares with the conjugate gradient algorithm.

Published
2021
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38. Influence of Doppler broadening model accuracy in Compton camera list-mode MLEM reconstruction

Author

Yuemeng Feng, Jean Michel Létang, David Sarrut, Voichia Maxim, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Rayet, Béatrice, Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[PHYS.PHYS.PHYS-MED-PH] Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], 010308 nuclear & particles physics, Applied Mathematics, MLEM, General Engineering, 01 natural sciences, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, 030218 nuclear medicine & medical imaging, Computer Science Applications, 03 medical and health sciences, Doppler broadening, 0302 clinical medicine, total variation, [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Computer Science::Computer Vision and Pattern Recognition, 0103 physical sciences, MAP-EM, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], ComputingMilieux_MISCELLANEOUS, Compton camera imaging
Abstract

International audience; The Compton camera is a gamma ray imaging device expected to provide clinically relevant images in the SPECT applications where collimated cameras are suboptimal. Its imaging performances depend not only on the design of the detection system but also on choices related to tomographic reconstruction. The aim of this work is to show that the accuracy in modeling the acquisition largely influences the quality of the images. For this purpose we restrict here to Doppler broadening models in conjunction with the list-mode maximum likelihood expectation maximization (LM-MLEM) algorithm. The study was carried out with Monte Carlo simulation. We show that the reconstructed point spread function is location-dependent when the model is not accurate, and the usual elongation artefacts well-known in Compton camera imaging will appear. The model we propose allows to reconstruct isolated point sources and more complex non-uniform sources with improved resolution even in the direction orthogonal to the camera.

Published
2021
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39. A new hybrid next-event estimator for photon-based Monte Carlo dose rate calculations

Author

Cheikh Diop, Ettore Guadagni, Cindy Le Loirec, Y. Peneliau, Davide Mancusi, Jean Michel Létang, Institut de recherche sur les systèmes nucléaires pour la production d'énergie bas carbone (IRESNE), CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut de Recherche sur la Fusion par confinement Magnétique (IRFM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie Tomographique et Radiothérapie, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut des Sciences Appliquées et de la Simulation pour les énergies bas carbone (ISAS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Physics, Photon, Speedup, 010308 nuclear & particles physics, Monte Carlo method, General Physics and Astronomy, Estimator, 01 natural sciences, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, 3. Good health, 030218 nuclear medicine & medical imaging, Exponential function, 03 medical and health sciences, 0302 clinical medicine, Monte carlo code, 0103 physical sciences, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Applied mathematics, Dose rate, Event (probability theory)
Abstract

This work describes the implementation of a deterministic-like straight-line transport routine inside the $$\hbox {TRIPOLI-4}^{\circledR }$$ Monte Carlo code, aimed at developing a hybrid estimator that can speed up the MC calculation while retaining its precision. The algorithm is based on the exponential track length estimator or eTLE, a next-event estimator that has already been investigated for medical applications. In this implementation, the eTLE is paired with a forced detection algorithm. We describe the implementation of the method in $$\hbox {TRIPOLI-4}^{\circledR }$$ , then we present the first results obtained over some test cases and compare them with the classic track-length estimator already implemented in $$\hbox {TRIPOLI-4}^{\circledR }$$ . These results show that the forced detection technique drastically improves the eTLE performance.

Published
2021
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40. Estimate of the Biological Dose in Hadrontherapy Using GATE

Author

Yasmine Ali, Caterina Monini, Etienne Russeil, Jean Michel Létang, Etienne Testa, Lydia Maigne, Michael Beuve, Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), ANR-11-LABX-0063,PRIMES,Physique, Radiobiologie, Imagerie Médicale et Simulation(2011), Rayet, Béatrice, Physique, Radiobiologie, Imagerie Médicale et Simulation - - PRIMES2011 - ANR-11-LABX-0063 - LABX - VALID, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Cancer Research, [PHYS.PHYS.PHYS-MED-PH] Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], biological dose, Monte Carlo, Geant4-DNA, LPCHEM, GATE, mMKM, NanOx, Oncology, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Abstract

International audience; For the evaluation of the biological effects, Monte Carlo toolkits were used to provide an RBE-weighted dose using databases of survival fraction coefficients predicted through biophysical models. Biophysics models, such as the mMKM and NanOx models, have previously been developed to estimate a biological dose. Using the mMKM model, we calculated the saturation corrected dose mean specific energy z1D* (Gy) and the dose at 10% D10 for human salivary gland (HSG) cells using Monte Carlo Track Structure codes LPCHEM and Geant4-DNA, and compared these with data from the literature for monoenergetic ions. These two models were used to create databases of survival fraction coefficients for several ion types (hydrogen, carbon, helium and oxygen) and for energies ranging from 0.1 to 400 MeV/n. We calculated α values as a function of LET with the mMKM and the NanOx models, and compared these with the literature. In order to estimate the biological dose for SOBPs, these databases were used with a Monte Carlo toolkit. We considered GATE, an open-source software based on the GEANT4 Monte Carlo toolkit. We implemented a tool, the BioDoseActor, in GATE, using the mMKM and NanOx databases of cell survival predictions as input, to estimate, at a voxel scale, biological outcomes when treating a patient. We modeled the HIBMC 320 MeV/u carbon-ion beam line. We then tested the BioDoseActor for the estimation of biological dose, the relative biological effectiveness (RBE) and the cell survival fraction for the irradiation of the HSG cell line. We then tested the implementation for the prediction of cell survival fraction, RBE and biological dose for the HIBMC 320 MeV/u carbon-ion beamline. For the cell survival fraction, we obtained satisfying results. Concerning the prediction of the biological dose, a 10% relative difference between mMKM and NanOx was reported.

Published
2022
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41. Motion detection in helical CT using data consistency conditions

Author

Melanie Mouchet, Jean Michel Létang, Simon Rit, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Rit, Simon

Subjects
Data consistency, Computer science, Image quality, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Motion detection, data consistency conditions, Imaging phantom, Position (vector), Line (geometry), Shortest path problem, motion detection, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Trajectory, Computed tomography, Algorithm
Abstract

International audience; In computed tomography (CT), unexpected motion can result in poor image quality after reconstruction. One way to detect this motion is to verify data consistency conditions (DCC). DCC are mathematical relationships that characterize the redundancy of the data and must be verified by the projections. Necessary conditions for cone-beam projections with a linear source trajectory state that the integral of the cosine weighted projections along each row of the detector must be equal. In this work, we apply these conditions to pairs of source positions along a helical trajectory by rebinning the projections to a virtual detector parallel to the line connecting the two source positions. Then, we construct a graph connecting source positions between which we can calculate DCC and we use the Dijkstra algorithm to compute the shortest path between the first source position and all the other ones. This method was tested on simulated projections of the dynamic version of the Forbild thorax phantom, mostly static at end-inhale except for one breathing cycle during the acquisition. The proposed method allows a clear identification of when motion occurs during the acquisition.

Published
2020
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42. Characterization of a beam-tagging hodoscope for hadrontherapy monitoring

Author

Etienne Testa, M.-L. Gallin-Martel, O. Allegrini, J.-P. Cachemiche, X. Chen, R. Della Negra, C. Morel, C.P.C. Caplan, B. Carlus, Joel Herault, Y. Zoccarato, S. Curtoni, Denis Dauvergne, Jean Michel Létang, Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre de Lutte contre le Cancer Antoine Lacassagne [Nice] (UNICANCER/CAL), UNICANCER-Université Côte d'Azur (UCA), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), ANR-11-LABX-0063,PRIMES,Physique, Radiobiologie, Imagerie Médicale et Simulation(2011), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Rayet, Béatrice, Physique, Radiobiologie, Imagerie Médicale et Simulation - - PRIMES2011 - ANR-11-LABX-0063 - LABX - VALID, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Photomultiplier, Physics - Instrumentation and Detectors, beam monitoring, Proton, Physics::Instrumentation and Detectors, FOS: Physical sciences, 01 natural sciences, Coincidence, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Optics, Hodoscope, hadrontherapy, 0103 physical sciences, Perpendicular, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Nuclear Experiment, Instrumentation, Mathematical Physics, Physics, [PHYS.PHYS.PHYS-MED-PH] Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], 010308 nuclear & particles physics, business.industry, Resolution (electron density), Instrumentation and Detectors (physics.ins-det), Physics - Medical Physics, Full width at half maximum, [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Physics::Accelerator Physics, Medical Physics (physics.med-ph), scintillating fibers, business, Beam (structure)
Abstract

A beam tagging hodoscope prototype made of squared 1 mm$^2$ fibers arranged in two perpendicular planes and coupled to multi-anode photomultipliers has been studied using 65 MeV proton as well as 95 MeV/u $^{12}$C beams at various intensities. This hodoscope successfully provided 2D images of proton beams with a detection efficiency larger than 98 % with logical OR condition between the two fiber planes. The detection efficiency with a coincidence between the two planes is close to 75 % for beam intensities up to $\sim1$ MHz. Moreover, the timing resolution is around 1.8 ns FWHM. Overall, the performances show that such a technology is viable for beam monitoring during hadrontherapy., 17 pages, 18 figures

Published
2020
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43. 2D directional ramp filter

Author

Jean Michel Létang, Feriel Khellaf, Nils Krah, Simon Rit, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Rit, Simon

Subjects
Computer science, Physics::Medical Physics, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Iterative reconstruction, Imaging phantom, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Image Processing, Computer-Assisted, Humans, Scattering, Radiation, Radiology, Nuclear Medicine and imaging, Image resolution, ComputingMilieux_MISCELLANEOUS, Tomographic reconstruction, Radiological and Ultrasound Technology, Phantoms, Imaging, Filter (signal processing), Mockup, 030220 oncology & carcinogenesis, Tomography, Protons, Tomography, X-Ray Computed, Algorithm, Algorithms
Abstract

International audience; Usual tomographic reconstruction methods start by filtering projections before backpro-jecting the data. In some cases, inverting the filtering and the backprojection steps can be useful to preserve spatial information. In this paper, an intermediate between a filter-backproject and a backproject-filter approach is proposed, based on the extension of the usual ramp filter to two dimensions. To this end, an expression for a band-limited 2D version of the ramp filter is derived. We have tested this filter on simulated X-ray CT projections of a Shepp-Logan phantom and on proton CT list-mode data. We accurately reconstructed the X-ray CT and the proton CT data, although the reconstruction can be slightly noisier than a standard filtered backprojection in some cases. A slight improvement of the spatial resolution of proton CT images reconstructed with this 2D filter has been observed.

Published
2020
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44. A comparison of direct reconstruction algorithms in proton computed tomography

Author

Jean Michel Létang, Feriel Khellaf, Nils Krah, Charles-Antoine Collins-Fekete, Simon Rit, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Physique Nucléaire de Lyon (IPNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Department of Medical Physics and Biomedical Engineering (UCL), University College of London [London] (UCL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Rit, Simon, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Proton computed tomography, Proton, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Imaging phantom, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, symbols.namesake, 0302 clinical medicine, Approximation error, Image Processing, Computer-Assisted, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Radiology, Nuclear Medicine and imaging, spatial resolution, Image resolution, ComputingMilieux_MISCELLANEOUS, Physics, Radiological and Ultrasound Technology, Phantoms, Imaging, Detector, direct algorithms, proton CT reconstruction, Grid, Nonlinear Dynamics, 030220 oncology & carcinogenesis, symbols, Hilbert transform, Protons, Tomography, X-Ray Computed, Algorithm, Algorithms
Abstract

International audience; Several direct algorithms have been proposed to take into account the non-linear path of protons in the reconstruction of a proton CT (pCT) image. This paper presents a comparison between five of them, in terms of spatial resolution and relative stopping power (RSP) accuracy. Our comparison includes (1) a distance-driven algorithm extending the filtered backprojection to non-linear trajectories (DD), (2) an algorithm reconstructing a pCT image from optimized projections (ML), (3) a backproject-then-filter approach using a 2D cone filter (BTF), (4) a differentiated backprojection algorithm based on the inversion of the Hilbert transform (DBP), and (5) an algorithm using a 2D directional ramp filter (DR). We have simulated a single tracking pCT setup using Geant4 through GATE, with a proton source and two position, direction and energy detectors upstream and downstream from the object. Tracker uncertainties were added on the position and direction measurements. A Catphan 528 phantom and a spiral phantom were simulated to measure the spatial resolution and a Gammex 467 phantom was used for the RSP accuracy. Each proton's trajectory was estimated using a most likely path (MLP) formalism. The spatial resolution was evaluated using the frequency corresponding to an MTF of 10% of its peak value and the RSP accuracy using the mean values in the inserts of the Gammex phantom. In terms of spatial resolution, it was shown that, for ideal trackers, the DR and BTF methods offer a slightly better resolution since each proton is directly binned in the image grid according to its MLP. However, all methods but the ML show comparable resolution when using realistic trackers. Regarding the RSP, three algorithms (DR, DD and BTF) show a mean relative error inside the inserts about 0.1%. As the DR and BTF methods are more computationally expensive, the DD-which allows the same spatial resolution in realistic conditions and the same accuracy-and the DBP-which has a fairly good accuracy (< 0.2%) and allows reconstruction from truncated data-can be used for a reduced reconstruction time.

Published
2020
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45. Monitoring ion beam therapy with a Compton Camera: simulation studies of the clinical feasibility

Author

Etienne Testa, J.-L. Ley, I. Rinaldi, J. Krimmer, Jean Michel Létang, Mattia Fontana, M.-H. Richard, Nicolas Freud, Voichita Maxim, Denis Dauvergne, Institut de Physique Nucléaire de Lyon (IPNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), and Université Grenoble Alpes (UGA)

Subjects
Physics, [PHYS]Physics [physics], Particle therapy, Ion beam, business.industry, medicine.medical_treatment, Detector, Monte Carlo method, Physics::Medical Physics, Dose profile, Atomic and Molecular Physics, and Optics, Imaging phantom, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Optics, 030220 oncology & carcinogenesis, medicine, Radiology, Nuclear Medicine and imaging, business, Instrumentation, Beam (structure), Event reconstruction
Abstract

As more and more particle therapy centers are being built world-wide, there is increasing need in treatment monitoring methods, ideally in real time. This article investigates the clinical applicability of a Compton camera design by means of Monte Carlo simulations. The Compton camera performance has been studied with the simulation of point-like source and beam irradiation of a polymethyl methacrylate (PMMA) phantom. The system absolute photon detection efficiency, measured via source irradiation, varies in the range [1, 4] $\times 10^{-4}$ with energy variations in the prompt gamma (PG) energy range and source position shifts with respect to the center of the camera. With proton and carbon beams impinging on a PMMA cylindrical phantom, the number of detected PG coincidences related to various beam time structure has been studied. Finally, the accuracy of the camera in identifying the dose profile fall-off position has been estimated and two different event reconstruction methods have been compared for this purpose; one based on analytical calculation with a line-cone technique, the second relying on an iterative maximum likelihood expectation maximization algorithm. Both methods showed the possibility to reconstruct the beam depth-dose profile and to retrieve the dose fall-off with millimeter precision on a spot basis.

Published
2020
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46. Ultra-fast prompt gamma detection in single proton counting regime for range monitoring in particle therapy

Author

Jayde Livingstone, Vincent Métivier, Denis Dauvergne, Jean Michel Létang, Etienne Testa, Charbel Koumeir, M. Yamouni, J-Y. Hostachy, Sara Marcatili, Jean-François Muraz, M.L. Gallin-Martel, L. Gallin-Martel, S. Curtoni, J. Collot, Noël Servagent, Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire de physique subatomique et des technologies associées (SUBATECH), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Cyclotron ARRONAX, GIP, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Nantes (UN)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), HEP, INSPIRE, Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Université de Nantes - Faculté des Sciences et des Techniques, and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Physics - Instrumentation and Detectors, Proton, Physics::Instrumentation and Detectors, medicine.medical_treatment, FOS: Physical sciences, Particle detector, 030218 nuclear medicine & medical imaging, [PHYS] Physics [physics], 03 medical and health sciences, 0302 clinical medicine, Optics, Hodoscope, medicine, Proton Therapy, Humans, Radiology, Nuclear Medicine and imaging, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Physics, [PHYS]Physics [physics], Range (particle radiation), Particle therapy, Radiological and Ultrasound Technology, business.industry, Phantoms, Imaging, Detector, Gamma ray, Instrumentation and Detectors (physics.ins-det), Physics - Medical Physics, 3. Good health, Time of flight, [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Gamma Rays, 030220 oncology & carcinogenesis, Medical Physics (physics.med-ph), business, Monte Carlo Method
Abstract

In order to fully exploit the ballistic potential of particle therapy, we propose an online range monitoring concept based on high-resolution Time-Of-Flight (TOF)-resolved Prompt Gamma (PG) detection in a single proton counting regime. In a proof of principle experiment, different types of monolithic scintillating gamma detectors are read in time coincidence with a diamond-based beam hodoscope, in order to build TOF spectra of PG generated in a heterogeneous target presenting an air cavity of variable thickness. Since the measurement was carried out at low beam currents ($, Comment: 17 pages, 18 figures

Published
2020
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47. CCMod: a GATE module for Compton camera imaging simulation

Author

Etienne Testa, Josep F. Oliver, David Sarrut, A. Etxebeste, Denis Dauvergne, Jean Michel Létang, Enrique Muñoz, Gabriela Llosa, M Fontana, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Imagerie Tomographique et Radiothérapie, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
[PHYS]Physics [physics], Photons, Photon, Radiological and Ultrasound Technology, business.industry, Computer science, Monte Carlo method, Detector, Iterative reconstruction, Scintillator, Spectral line, 030218 nuclear medicine & medical imaging, Radiography, 03 medical and health sciences, 0302 clinical medicine, Optics, 030220 oncology & carcinogenesis, Medical imaging, Radiology, Nuclear Medicine and imaging, Angular resolution, Computer Simulation, Gamma Cameras, business, Monte Carlo Method, ComputingMilieux_MISCELLANEOUS
Abstract

International audience; Compton cameras are gamma-ray imaging systems which have been proposed for a wide variety of applications such as medical imaging, nuclear decommissioning or homeland security. In the design and optimization of such a system Monte Carlo simulations play an essential role. In this work, we propose a generic module to perform Monte Carlo simulations and analyses of Compton Camera imaging which is included in the open-source GATE/Geant4 platform. Several digitization stages have been implemented within the module to mimic the performance of the most commonly employed detectors (e.g. monolithic blocks, pixelated scintillator crystals, strip detectors...). Time coincidence sorter and sequence coincidence reconstruction are also available in order to aim at providing modules to facilitate the comparison and reproduction of the data taken with different prototypes. All processing steps may be performed during the simulation (on–the–fly mode) or as a post–process of the output files (offline mode). The predictions of the module have been compared with experimental data in terms of energy spectra, angular resolution, efficiency and back-projection image reconstruction. Consistent results within a 3-sigma interval were obtained for the energy spectra except for low energies where small differences arise. The angular resolution measure for incident photons of 1275 keV was also in good agreement between both data sets with a value close to 13°. Moreover, with the aim of demonstrating the versatility of such a tool the performance of two different Compton camera designs was evaluated and compared.

Published
2019
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49. Compton camera study for high efficiency SPECT and benchmark with Anger system

Author

Mattia Fontana, Denis Dauvergne, Jean Michel Létang, J.-L. Ley, Etienne Testa, Institut de Physique Nucléaire de Lyon (IPNL), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), PRISME (PRISME), Institut de Physique des 2 Infinis de Lyon (IP2I Lyon), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), ANR-11-LABX-0063,PRIMES,Physique, Radiobiologie, Imagerie Médicale et Simulation(2011), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
medicine.medical_specialty, Anger camera, Photon, Astrophysics::High Energy Astrophysical Phenomena, Physics::Medical Physics, Monte Carlo method, Single-photon emission computed tomography, Collimated light, gamma detection, single photon emission computed tomography, 030218 nuclear medicine & medical imaging, law.invention, 03 medical and health sciences, 0302 clinical medicine, Optics, imaging radiotracers, law, Compton imaging, medicine, Humans, Gamma Cameras, Radiology, Nuclear Medicine and imaging, Medical physics, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Image resolution, Probability, Tomography, Emission-Computed, Single-Photon, Physics, Photons, Radiological and Ultrasound Technology, medicine.diagnostic_test, Phantoms, Imaging, business.industry, Detector, Collimator, 3. Good health, Anger Camera, Benchmarking, 030220 oncology & carcinogenesis, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], business, Monte Carlo Method, Algorithms
Abstract

International audience; Single photon emission computed tomography (SPECT) is at present one of the major techniques for non-invasive diagnostics in nuclear medicine. The clinical routine is mostly based on collimated cameras, originally proposed by Hal Anger. Due to the presence of mechanical collimation, detection efficiency and energy acceptance are limited and fixed by the system's geometrical features. In order to overcome these limitations, the application of Compton cameras for SPECT has been investigated for several years.In this study we compare a commercial SPECT-Anger device, the General Electric HealthCare Infinia system with a High Energy General Purpose (HEGP) collimator, and the Compton camera prototype under development by the French collaboration CLaRyS, through Monte Carlo simulations (GATE—GEANT4 Application for Tomographic Emission—version 7.1 and GEANT4 version 9.6, respectively). Given the possible introduction of new radio-emitters at higher energies intrinsically allowed by the Compton camera detection principle, the two detectors are exposed to point-like sources at increasing primary gamma energies, from actual isotopes already suggested for nuclear medicine applications. The Compton camera prototype is first characterized for SPECT application by studying the main parameters affecting its imaging performance: detector energy resolution and random coincidence rate. The two detector performances are then compared in terms of radial event distribution, detection efficiency and final image, obtained by gamma transmission analysis for the Anger system, and with an iterative List Mode-Maximum Likelihood Expectation Maximization (LM-MLEM) algorithm for the Compton reconstruction.The results show for the Compton camera a detection efficiency increased by a factor larger than an order of magnitude with respect to the Anger camera, associated with an enhanced spatial resolution for energies beyond 500 keV. We discuss the advantages of Compton camera application for SPECT if compared to present commercial Anger systems, with particular focus on dose delivered to the patient, examination time, and spatial uncertainties.

Published
2017
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50. Convolution-based scatter correction using kernels combining measurements and Monte Carlo simulations

Author

Navnina Bhatia, Jean Michel Létang, David Tisseur, Département Imagerie et Simulation pour le Contrôle (DISC), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Imagerie Tomographique et Radiothérapie, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
geometry, Object detection, Image quality, Computer science, Experimental techniques, Monte Carlo method, Scatter correction, Gaussian distribution, Scatter contamination, 030218 nuclear medicine & medical imaging, Hybrid Monte Carlo, Object-to-detector distance, 03 medical and health sciences, Superposition principle, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Intelligent systems, controlled study, Radiology, Nuclear Medicine and imaging, Electrical and Electronic Engineering, Instrumentation, calculation, [PHYS]Physics [physics], Radiation, Detector, Cone-beam computed tomography, CBCT, Monte Carlo methods, cone beam computed tomography, CIVA, Computerized tomography, Condensed Matter Physics, thickness, Scatter-to-primary ratio, Kernel (image processing), 030220 oncology & carcinogenesis, Dynamic Monte Carlo method, Deconvolution, Algorithm
Abstract

International audience; One of the well-recognized challenge of Cone-Beam Computed Tomography (CBCT) is scatter contamination within the projection images. Scatter degrades the image quality by decreasing the contrast, introducing cupping and shading artifacts and thus leading to inaccuracies in the reconstructed values. The higher scatter to primary ratio experienced in industrial applications leads to even more important artifacts. Various strategies have been investigated to manage the scatter signal in CBCT projection data. One of these strategies is to calculate the scatter intensity by deconvolution of primary intensity using Scatter Kernel Superposition (SKS). In this paper, we present an approach combining experimental measurements and Monte Carlo simulations to estimate the scatter kernels for industrial applications based on the continuously thickness-adapted kernels strategy with a four-Gaussian modeling of kernels. We compare this approach with an experimental technique based on a two-Gaussian modeling of the kernels. The results obtained prove the superiority of a four-Gaussian model to effectively take into account both the contribution of object and detector scattering as compared to a two-Gaussian approach. We also present the parameterisation of the scatter kernels with respect to object to detector distance. This approach facilitates the use of a single geometry for calculation of scatter kernels over the whole magnification range of the acquisition setup.

Published
2017
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