Modeling cell response to low doses of photon irradiation: Part 2--application to radiation-induced chromosomal aberrations in human carcinoma cells.

The biological phenomena observed at low doses of ionizing radiation (adaptive response, bystander effects, genomic instability, etc.) are still not well understood. While at high irradiation doses, cellular death may be directly linked to DNA damage, at low doses, other cellular structures may be involved in what are known as non-(DNA)-targeted effects. Mitochondria, in particular, may play a crucial role through their participation in a signaling network involving oxygen/nitrogen radical species. According to the size of the implicated organelles, the fluctuations in the energy deposited into these target structures may impact considerably the response of cells to low doses of ionizing irradiation. Based on a recent simulation of these fluctuations, a theoretical framework was established to have further insight into cell responses to low doses of photon irradiation, namely the triggering of radioresistance mechanisms by energy deposition into specific targets. Three versions of a model are considered depending on the target size and on the number of targets that need to be activated by energy deposition to trigger radioresistance mechanisms. These model versions are applied to the fraction of radiation-induced chromosomal aberrations measured at low doses in human carcinoma cells (CAL51). For this cell line, it was found in the present study that the mechanisms of radioresistance could not be triggered by the activation of a single small target (nanometric size, 100 nm), but could instead be triggered by the activation of a large target (micrometric, 10 µm) or by the activation of a great number of small targets. The mitochondria network, viewed either as a large target or as a set of small units, might be concerned by these low-dose effects.

Modeling cell response to low doses of photon irradiation--Part 1: on the origin of fluctuations.

Intra- and inter-individual variability is a well-known aspect of biological responses of cells observed at low doses of radiation, whichever the phenomenon considered (adaptive response, bystander effects, genomic instability, etc.). There is growing evidence that low-dose phenomena are related to cell mechanisms other than DNA damage and misrepair, meaning that other cellular structures may play a crucial role. Therefore, in this study, a series of calculations at low doses was carried out to study the distribution of specific energies from different irradiation doses (3, 10 and 30 cGy) in targets of different sizes (0.1, 1 and 10 µm) corresponding to the dimensions of different cell structures. The results obtained show a strong dependence of the probability distributions of specific energies on the target size: targets with dimensions comparable to those of the cell show a Gaussian-like distribution, whereas very small targets are very likely to not be hit. A statistical analysis showed that the level of fluctuations in the fraction of aberrant cells is only related to the fraction of aberrant cells and the number of irradiated cells, regardless of, for instance, the heterogeneity in cell response.

Prompt-gamma track-length estimator with time tagging from proton tracking.

The design of prompt-gamma detectors necessitates numerous Monte Carlo simulations to precisely develop and optimize the detection stages in proton therapy. Alongside the advancement of MC simulations, various variance reduction methods have been explored to speed-up calculations. Among these techniques, track-length estimators are interesting scoring methods for achieving both speed and accuracy in Monte Carlo simulations of rare events. This paper introduces an extension of the GATE vpgTLE module that incorporates the prompt-gamma emission time, which is tagged from the proton tracking, enhancing its utility for studies focused on detector design and optimization that rely on time measurements. The results obtained from a clinical radiotherapy plan are presented. We demonstrate that the new vpgTLE tally with time tagging is accurate, except for certain prompt-gamma lines corresponding to long mean-life nuclei.

Biophysical modeling of low-energy ion irradiations with NanOx.

BACKGROUND: Targeted radiotherapies with low-energy ions show interesting possibilities for the selective irradiation of tumor cells, a strategy particularly appropriate for the treatment of disseminated cancer. Two promising examples are boron neutron capture therapy (BNCT) and targeted radionuclide therapy with α $\alpha$ -particle emitters (TAT). The successful clinical translation of these radiotherapies requires the implementation of accurate radiation dosimetry approaches able to take into account the impact on treatments of the biological effectiveness of ions and the heterogeneity in the therapeutic agent distribution inside the tumor cells. To this end, biophysical models can be applied to translate the interactions of radiations with matter into biological endpoints, such as cell survival. PURPOSE: The NanOx model was initially developed for predicting the cell survival fractions resulting from irradiations with the high-energy ion beams encountered in hadrontherapy. We present in this work a new implementation of the model that extends its application to irradiations with low-energy ions, as the ones found in TAT and BNCT. METHODS: The NanOx model was adapted to consider the energy loss of primary ions within the sensitive volume (i.e., the cell nucleus). Additional assumptions were introduced to simplify the practical implementation of the model and reduce computation time. In particular, for low-energy ions the narrow-track approximation allowed to neglect the energy deposited by secondary electrons outside the sensitive volume, increasing significantly the performance of simulations. Calculations were performed to compare the original hadrontherapy implementation of the NanOx model with the present one in terms of the inactivation cross sections of human salivary gland cells as a function of the kinetic energy of incident α $\alpha$ -particles. RESULTS: The predictions of the previous and current versions of NanOx agreed for incident energies higher than 1 MeV/n. For lower energies, the new NanOx implementation predicted a decrease in the inactivation cross sections that depended on the length of the sensitive volume. CONCLUSIONS: We reported in this work an extension of the NanOx biophysical model to consider irradiations with low-energy ions, such as the ones found in TAT and BNCT. The excellent agreement observed at intermediate and high energies between the original hadrontherapy implementation and the present one showed that NanOx offers a consistent, self-integrated framework for describing the biological effects induced by ion irradiations. Future work will focus on the application of the latest version of NanOx to cases closer to the clinical setting.

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

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-1velocity 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-1velocity 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.

Estimate of the Biological Dose in Hadrontherapy Using GATE.

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.

Imaging of polychromatic sources through Compton spectral reconstruction.

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.

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

PURPOSE: In 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 METHODS: In 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 species (· OH, e aq - ${\rm{e}}_{{\rm{aq}}}^ - $ , H 3 O + , H 2 O 2 ${{\rm{H}}_3}{{\rm{O}}^ + },{\rm{\;}}{{\rm{H}}_2}{{\rm{O}}_2}$ , H2 , and O H - ) ${\rm{O}}{{\rm{H}}^ - }){\rm{\;}}$ yields simulated between 10-12 and 10-6 s after irradiation are compared. RESULTS: Overall, 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 ) with 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 four for 1000 primary particles in all simulation stages (physical, physico-chemical, and chemical). In multi-thread mode (four threads), Geant4-DNA computing times are reduced but remain slower than LPCHEM by ∼20% up to ∼50%. CONCLUSIONS: For the first time, the entire physical, physico-chemical, 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.

Influence of gold nanoparticles embedded in water on nanodosimetry for keV photon irradiation.

PURPOSE: For the past two decades, high-Z nanoparticles have been of high interest to improve the therapeutic outcomes of radiation therapy, especially for low-energy x-rays. Monte Carlo (MC) simulations have been used to evaluate the boost of dose deposition induced by Auger electrons near the nanoparticle surface, by calculating average energy deposition at the nanoscale. In this study, we propose to go beyond average quantities and quantify the stochastic nature of energy deposition at such a scale. We present results of probability density of the specific energy (restricted to ionization, excitation and electron attachment events) in cylindrical nanotargets of height and radius set at 10 nm. This quantity was evaluated for nanotargets located within 200 nm around 5-50 nm gold nanoparticles (GNPs), for 20-90 keV photon irradiation. METHODS: This nanodosimetry study was based on the MC simulation MDM that allows tracking of electrons down to thermalization energy. We introduced a new quantity, namely the probability enhancement ratio (PER), by estimating the probability of imparting to nanotargets a restricted specific energy larger than a threshold z 0 (1, 10, and 20 kGy), normalized to the probability for pure water. The PER was calculated as a function of the distance between the nanotarget and the GNP surface. The threshold values were chosen in light of the biophysical model NanOx that predicts cell survival by calculating local lethal events based on the restricted specific energy and an effective local lethal function. z 0 then represents a threshold above which the nanotarget damages induce efficiently cell death. RESULTS: Our calculations showed that the PER varied a lot with the GNP radius, the photon energy, z 0 and the distance of the GNP to the nanotarget. The highest PER was 95 when the nanotarget was located at 5 nm from the GNP surface, for a photon energy of 20 keV, a threshold of 20 kGy, and a GNP radius of 50 nm. This enhancement dramatically decreased with increasing GNP-nanotarget distances as it went below 1.5 for distances larger than 200 nm. CONCLUSIONS: The PER seems better adapted than the mean dose deposition to describe the formation of biological damages. The significant increase of the PER within 200 nm around the GNP suggests that severe damages could occur for biological nanotargets located near the GNP. These calculations will be used as an input of the biophysical model NanOx to convert PER into estimation of radiation-induced cell death enhanced by GNPs.

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

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 (MLP) 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 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.

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

Online ion range monitoring in hadron therapy can be performed via detection of secondary radiation, such as promptγ-rays, emitted during treatment. The promptγemission 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 theγfall-off position (FOP) measured via line-cone reconstruction, where TOF comprises both the proton transit time from the phantom entrance untilγemission, and the flight time of theγ-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 FOP. 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 CeBr3scintillator 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 FOP was obtained for varying temporal resolutions and its precision obtained from its shift across 100 independentγemission profiles compared to a high statistics reference profile. The optimal temporal resolution for the given camera geometry and 108primary protons was 0.2 ns where a precision of 2.30 ± 0.15 mm (1σ) on the FOP 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.

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

We propose a novel prompt-gamma (PG) imaging modality for real-time monitoring in proton therapy: PG time imaging (PGTI). By measuring the time-of-flight (TOF) between a beam monitor and a PG detector, our goal is to reconstruct the PG vertex distribution in 3D. In this paper, a dedicated, non-iterative reconstruction strategy is proposed (PGTI reconstruction). Here, it was resolved under a 1D approximation to measure a proton range shift along the beam direction. In order to show the potential of PGTI in the transverse plane, a second method, based on the calculation of the centre of gravity (COG) of the TIARA pixel detectors' counts was also explored. The feasibility of PGTI was evaluated in two different scenarios. Under the assumption of a 100 ps (rms) time resolution (achievable in single proton regime), MC simulations showed that a millimetric proton range shift is detectable at 2σwith 108incident protons in simplified simulation settings. With the same proton statistics, a potential 2 mm sensitivity (at 2σwith 108incident protons) to beam displacements in the transverse plane was found using the COG method. This level of precision would allow to act in real-time if the treatment does not conform to the 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 2σwith 109incident protons. By showing the feasibility of a time-based algorithm for the reconstruction of the PG vertex distribution for a simplified anatomy, this work poses a theoretical basis for the future development of a PG imaging detector based on the measurement of particle TOF.

Advanced Monte Carlo simulations of emission tomography imaging systems with GATE.

Built on top of the Geant4 toolkit, GATE is collaboratively developed for more than 15 years to design Monte Carlo simulations of nuclear-based imaging systems. It is, in particular, used by researchers and industrials to design, optimize, understand and create innovative emission tomography systems. In this paper, we reviewed the recent developments that have been proposed to simulate modern detectors and provide a comprehensive report on imaging systems that have been simulated and evaluated in GATE. Additionally, some methodological developments that are not specific for imaging but that can improve detector modeling and provide computation time gains, such as Variance Reduction Techniques and Artificial Intelligence integration, are described and discussed.

Determination of the Effective Local Lethal Function for the NanOx Model.

NanOx is a biophysical model recently developed in the context of hadrontherapy to predict the cell survival probability from ionizing radiation. It postulates that this may be factorized into two independent terms describing the cell response to two classes of biological events that occur in the sequence of an irradiation: the local lethal events that occur at nanometric scale and can by themselves induce cell death, and the non-local lethal events that lead to cell death by an effect of accumulation and/or interaction at a larger scale. Here we address how local lethal events are modeled in terms of the inactivation of undifferentiated nanometric targets via an "effective local lethal function F", which characterizes the response of each cell line to the spectra of "restricted specific energy". F is initially determined as a linear combination of basis functions. Then, a parametric expression is used to reproduce the function's main features, a threshold and a saturation, while at the same time reducing the number of free parameters. This strategy was applied to three cell lines in response to ions of different type and energy, which allows for benchmarking of the α(LET) curves predicted with both effective local lethal functions against the experimental data.

Comparison of biophysical models with experimental data for three cell lines in response to irradiation with monoenergetic ions.

The relative biological effectiveness (RBE) in particle therapy is currently estimated using biophysical models. We compared experimental measurements to the α curves as function of linear energy transfer computed by the Local Effect Model (LEM I-IV), the Microdosimetric Kinetic Model (MKM) and the NanOx model for HSG, V79 and CHO-K1 cells in response to monoenergetic irradiations. Although the LEM IV and the MKM predictions accurately reproduced the trend observed in the data, NanOx yielded a better agreement than the other models for more irradiation configurations. Its χ 2 estimator was indeed the lowest for three over seven considered cases.

Study of the Influence of NanOx Parameters.

NanOx is a new biophysical model that aims at predicting the biological effect of ions in the context of hadron therapy. It integrates the fully-stochastic nature of ionizing radiation both at micrometric and nanometric scales and also takes into account the production and diffusion of reactive chemical species. In order to further characterize the new framework, we discuss the meaning and relevance of most of the NanOx parameters by evaluating their influence on the linear-quadratic coefficient α and on the dose deposited to achieve 10% or 1% of cell survival, D 10 % or D 1 % , as a function of LET. We perform a theoretical study in which variations in the input parameters are propagated into the model predictions for HSG, V79 and CHO-K1 cells irradiated by monoenergetic protons and carbon ions. We conclude that, in the current version of NanOx, the modeling of a specific cell line relies on five parameters, which have to be adjusted to several experimental measurements: the average cellular nuclear radius, the linear-quadratic coefficients describing photon irradiations and the α values associated with two carbon ions of intermediate and high-LET values. This may have interesting implications toward a clinical application of the new biophysical model.

Relationship between radioadaptive response and individual radiosensitivity to low doses of gamma radiation: an extended study of chromosome damage in blood lymphocytes of three donors.

PURPOSE: Our study aimed at evaluating: 1) whether well-established variability in radioadaptive response (AR) in various donor blood lymphocytes might be attributed to inter-individual differences in radiosensitivity to different low dose levels; 2) whether AR is reproducibly present over time in the lymphocytes of AR-positive individuals. Experimental procedure: Whole blood samples of three donors were exposed to low doses (2-30 cGy) of γ-radiation alone (G0 phase) or followed by a 1 Gy challenge dose (late S/early G2 phase), and chromosome aberration were scored to assess the dose-response relationship and adaptive response, correspondingly. Three experiments were performed on blood samples of the same donors at six month intervals. RESULTS: Significant differences in dose response relationship for blood lymphocytes were found among individuals. In most cases, the donors exhibited initial low-dose hypersensitivity (HRS) followed by an increase in radioresistance (IRR). AR could be successfully induced by some particular priming doses in the lymphocytes of each donor; however, the doses resulting in a protective response were quite different for all three donors. These protective doses could equally belong to either HRS or IRR region on the individual dose-response curves. In most cases, no clear AR outcome dependence on the priming dose was found at all. Moreover, pre-exposure to the same low dose could result in opposite effects in the lymphocytes of the same donor in different experiments. CONCLUSIONS: AR variability in human lymphocytes is not attributed to variation in radiosensitivity among individuals and is more drastic than was believed. It seems doubtful that AR is a universal phenomenon which has a consistent impact on the effects of radiation exposure on humans.

Assessment of Geant4 Prompt-Gamma Emission Yields in the Context of Proton Therapy Monitoring.

Monte Carlo tools have been long used to assist the research and development of solutions for proton therapy monitoring. The present work focuses on the prompt-gamma emission yields by comparing experimental data with the outcomes of the current version of Geant4 using all applicable proton inelastic models. For the case in study and using the binary cascade model, it was found that Geant4 overestimates the prompt-gamma emission yields by 40.2 ± 0.3%, even though it predicts the prompt-gamma profile length of the experimental profile accurately. In addition, the default implementations of all proton inelastic models show an overestimation in the number of prompt gammas emitted. Finally, a set of built-in options and physically sound Geant4 source code changes have been tested in order to try to improve the discrepancy observed. A satisfactory agreement was found when using the QMD model with a wave packet width equal to 1.3 fm(2).

Probabilistic models and numerical calculation of system matrix and sensitivity in list-mode MLEM 3D reconstruction of Compton camera images.

This paper addresses the problem of evaluating the system matrix and the sensitivity for iterative reconstruction in Compton camera imaging. Proposed models and numerical calculation strategies are compared through the influence they have on the three-dimensional reconstructed images. The study attempts to address four questions. First, it proposes an analytic model for the system matrix. Second, it suggests a method for its numerical validation with Monte Carlo simulated data. Third, it compares analytical models of the sensitivity factors with Monte Carlo simulated values. Finally, it shows how the system matrix and the sensitivity calculation strategies influence the quality of the reconstructed images.

Corrigendum: Influence of Dose Rate on the Cellular Response to Low- and High-LET Radiations.

[This corrects the article on p. 58 in vol. 6, PMID: 27014633.].