Coherent scatter imaging Monte Carlo simulation.
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ABSTRACT:
SUBMITTER: Hassan L
PROVIDER: S-EPMC4999523 | biostudies-other | 2016 Jul
REPOSITORIES: biostudies-other
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Project description:BackgroundMonte Carlo simulation is considered as the most accurate method for dose calculation in radiotherapy. PRIMO is a Monte-Carlo program with a user-friendly graphical interface.Material and methodA VitalBeam with 6MV and 6MV flattening filter free (FFF), equipped with the 120 Millennium multileaf collimator was simulated by PRIMO. We adjusted initial energy, energy full width at half maximum (FWHM), focal spot FWHM, and beam divergence to match the measurements. The water tank and ion-chamber were used in the measurement. Percentage depth dose (PDD) and off axis ratio (OAR) were evaluated with gamma passing rates (GPRs) implemented in PRIMO. PDDs were matched at different widths of standard square fields. OARs were matched at five depths. Transmission factor and dose leaf gap (DLG) were simulated. DLG was measured by electronic portal imaging device using a sweeping gap method.ResultFor the criterion of 2%/2 mm, 1%/2 mm and 1%/1 mm, the GPRs of 6MV PDD were 99.33-100%, 99-100%, and 99-100%, respectively; the GPRs of 6MV FFF PDD were 99.33-100%, 98.99-99.66%, and 97.64-98.99%, respectively; the GPRs of 6MV OAR were 96.4-100%, 90.99-100%, and 85.12-98.62%, respectively; the GPRs of 6MV FFF OAR were 95.15-100%, 89.32-100%, and 87.02-99.74%, respectively. The calculated DLG matched well with the measurement (6MV: 1.36 mm vs. 1.41 mm; 6MV FFF: 1.07 mm vs. 1.03 mm, simulation vs measurement). The transmission factors were similar (6MV: 1.25% vs. 1.32%; 6MV FFF: 0.8% vs. 1.12%, simulation vs measurement).ConclusionThe calculated PDD, OAR, DLG and transmission factor were all in good agreement with measurements. PRIMO is an independent (with respect to analytical dose calculation algorithm) and accurate Monte Carlo tool.
| S-EPMC9667592 | biostudies-literature
Project description:PURPOSE:In 90 Y microsphere radioembolization (RE), accurate post-therapy imaging-based dosimetry is important for establishing absorbed dose versus outcome relationships for developing future treatment planning strategies. Additionally, accurately assessing microsphere distributions is important because of concerns for unexpected activity deposition outside the liver. Quantitative 90 Y imaging by either SPECT or PET is challenging. In 90 Y SPECT model based methods are necessary for scatter correction because energy window-based methods are not feasible with the continuous bremsstrahlung energy spectrum. The objective of this work was to implement and evaluate a scatter estimation method for accurate 90 Y bremsstrahlung SPECT/CT imaging. METHODS:Since a fully Monte Carlo (MC) approach to 90 Y SPECT reconstruction is computationally very demanding, in the present study the scatter estimate generated by a MC simulator was combined with an analytical projector in the 3D OS-EM reconstruction model. A single window (105 to 195-keV) was used for both the acquisition and the projector modeling. A liver/lung torso phantom with intrahepatic lesions and low-uptake extrahepatic objects was imaged to evaluate SPECT/CT reconstruction without and with scatter correction. Clinical application was demonstrated by applying the reconstruction approach to five patients treated with RE to determine lesion and normal liver activity concentrations using a (liver) relative calibration. RESULTS:There was convergence of the scatter estimate after just two updates, greatly reducing computational requirements. In the phantom study, compared with reconstruction without scatter correction, with MC scatter modeling there was substantial improvement in activity recovery in intrahepatic lesions (from > 55% to > 86%), normal liver (from 113% to 104%), and lungs (from 227% to 104%) with only a small degradation in noise (13% vs. 17%). Similarly, with scatter modeling contrast improved substantially both visually and in terms of a detectability index, which was especially relevant for the low uptake extrahepatic objects. The trends observed for the phantom were also seen in the patient studies where lesion activity concentrations and lesion-to-liver concentration ratios were lower for SPECT without scatter correction compared with reconstruction with just two MC scatter updates: in eleven lesions the mean uptake was 4.9 vs. 7.1 MBq/mL (P = 0.0547), the mean normal liver uptake was 1.6 vs. 1.5 MBq/mL (P = 0.056) and the mean lesion-to-liver uptake ratio was 2.7 vs. 4.3 (P = 0.0402) for reconstruction without and with scatter correction respectively. CONCLUSIONS:Quantitative accuracy of 90 Y bremsstrahlung imaging can be substantially improved with MC scatter modeling without significant degradation in image noise or intensive computational requirements.
| S-EPMC5734647 | biostudies-literature
Project description:This article describes the development and application of an integrated, generalized, and efficient Monte Carlo simulation system for diffusion magnetic resonance imaging (dMRI), named Diffusion Microscopist Simulator (DMS). DMS comprises a random walk Monte Carlo simulator and an MR image synthesizer. The former has the capacity to perform large-scale simulations of Brownian dynamics in the virtual environments of neural tissues at various levels of complexity, and the latter is flexible enough to synthesize dMRI datasets from a variety of simulated MRI pulse sequences. The aims of DMS are to give insights into the link between the fundamental diffusion process in biological tissues and the features observed in dMRI, as well as to provide appropriate ground-truth information for the development, optimization, and validation of dMRI acquisition schemes for different applications. The validity, efficiency, and potential applications of DMS are evaluated through four benchmark experiments, including the simulated dMRI of white matter fibers, the multiple scattering diffusion imaging, the biophysical modeling of polar cell membranes, and the high angular resolution diffusion imaging and fiber tractography of complex fiber configurations. We expect that this novel software tool would be substantially advantageous to clarify the interrelationship between dMRI and the microscopic characteristics of brain tissues, and to advance the biophysical modeling and the dMRI methodologies.
| S-EPMC3794953 | biostudies-literature
Project description:The Monte Carlo simulation algorithm of photon trajectory computation is implemented in object oriented R code. Diffuse reflectance, also called backscattering, is modeled in semi-infinite homogeneous media. Spatial photon flux leaving the surface of the media is collected. The profile of intensity along radii relative to the incident point is used to simulate measurement of computer vision systems. Four optical parameters of the media are used: absorption coefficient, scattering coefficient, anisotropy factor and refractive index. Five parameters are used to describe configuration of the vision system: number of photons, radius of circular light beam, limiting energy level of photons, radius of observed area, spatial resolution of the vision system.•The incident angle of the light beam is included in the photon launch procedure. Initial direction is typically assumed to be normal with x,y,z coordinates of 0,0,1. In the proposed modification, initial move vector is calculated based on the incident angle and refractive index of the media. Additionally, elliptic distortion of the circular light beam on the surface is calculated based on the incident angle.•Photon flux leaving media through the surface is corrected with Lambertian method to measure intensity captured by an imaging device in normal position.•The software implementing the method is written in R language, the R code is available as standard package.
| S-EPMC7327276 | biostudies-literature
Project description:Traditional multiple-group confirmatory factor analysis (multiple-group CFA) is usually criticized for having too restrictive model assumption, namely the scalar measurement invariance. The new multiple-group analysis methodology, alignment, has become an effective alternative. The alignment evaluates measurement invariance and more importantly, permits factor mean comparisons without requiring scalar invariance which is usually required in traditional multiple-group CFA. Some simulation studies and empirical studies have investigated the applicability of alignment under different conditions, but some areas remain unexplored. Based on the simulation studies of Asparouhov and Muthén and of Flake and McCoach, this current simulation study is broken into two sections. The first study investigates the minimal group sizes required for alignment in three-factor models. The second study compares the performance of multiple-group CFA, multiple-group exploratory structural equation model (multiple-group ESEM), and alignment by including different proportions and magnitudes of cross-loadings in the models. Study 1 shows that when the model has no noninvariant parameters, the alignment requires relatively lower group sizes. Explicitly, the minimal group size required for alignment was 250 when the amount of groups was three, the minimal group size was 150 when the amount of groups was nine, and 200 when the amount of groups was 15. When there are noninvariant parameters in the model and the amount of groups is low, a group size of 350 is a safe rule of thumb. When there are noninvariant parameters in the model and the amount of groups is high, a group size of 250 is required for trustworthy results. The magnitude of noninvariance and the noninvariance rate do not affect the minimal group size required for alignment. Study 2 shows that multiple-group CFA provides accurate factor mean estimates when each factor had 20% factor loading (1 factor loading) with small-sized cross-loading. Multiple-group ESEM provides accurate factor mean estimates when the magnitude of cross-loading is small or when each factor had 20% factor loading (1 factor loading) with medium-sized cross-loading. Alignment provides accurate factor mean estimates when there are only small-sized cross-loadings in the model. The parameter estimates, coverage rates and ratios of average standard error to standard deviation for each methodology are not influenced by the amount of groups. Recommendations are concluded for using multiple-group CFA, multiple-group ESEM, traditional alignment and aligned ESEM (AESEM) based on the results. Multiple-group CFA is more suitable for use when scalar invariance is established. Multiple-group ESEM works best when there are small-sized or only a few medium-sized cross-loadings in the model. Traditional alignment allows for small-sized cross-loadings and a few noninvariant parameters in the model. AESEM integrates the advantages of alignment and ESEM, can provide accurate estimates when noninvariant parameters and cross-loadings both exist in the model. Compared to multiple-group CFA, multiple-group ESEM, the alignment methodology performs well in more situations.
| S-EPMC9263979 | biostudies-literature
Project description:A computational method is developed to carry out explicit solvent simulations of complex molecular systems under conditions of constant pH. In constant-pH simulations, preidentified ionizable sites are allowed to spontaneously protonate and deprotonate as a function of time in response to the environment and the imposed pH. The method, based on a hybrid scheme originally proposed by H. A. Stern (J. Chem. Phys. 2007, 126, 164112), consists of carrying out short nonequilibrium molecular dynamics (neMD) switching trajectories to generate physically plausible configurations with changed protonation states that are subsequently accepted or rejected according to a Metropolis Monte Carlo (MC) criterion. To ensure microscopic detailed balance arising from such nonequilibrium switches, the atomic momenta are altered according to the symmetric two-ends momentum reversal prescription. To achieve higher efficiency, the original neMD-MC scheme is separated into two steps, reducing the need for generating a large number of unproductive and costly nonequilibrium trajectories. In the first step, the protonation state of a site is randomly attributed via a Metropolis MC process on the basis of an intrinsic pKa; an attempted nonequilibrium switch is generated only if this change in protonation state is accepted. This hybrid two-step inherent pKa neMD-MC simulation method is tested with single amino acids in solution (Asp, Glu, and His) and then applied to turkey ovomucoid third domain and hen egg-white lysozyme. Because of the simple linear increase in the computational cost relative to the number of titratable sites, the present method is naturally able to treat extremely large systems.
| S-EPMC4535364 | biostudies-literature
Project description:The invention and advancement of biological microscopy depends critically on an ability to accurately simulate imaging of complex biological structures embedded within complex scattering media. Unfortunately no technique exists for rigorous simulation of the complete imaging process, including the source, instrument, sample and detector. Monte-Carlo modelling is the gold standard for the modelling of light propagation in tissue, but is somewhat laborious to implement and does not incorporate the rejection of scattered light by the microscope. On the other hand microscopes may be rigorously and rapidly modelled using commercial ray-tracing software, but excluding the interaction with the biological sample. We report a hybrid Monte-Carlo optical ray-tracing technique for modelling of complete imaging systems of arbitrary complexity. We make the software available to enable user-friendly and rigorous virtual prototyping of biological microscopy of arbitrary complexity involving light scattering, fluorescence, polarised light propagation, diffraction and coherence. Examples are presented for the modelling and optimisation of representative imaging of neural cells using light-sheet and micro-endoscopic fluorescence microscopy and imaging of retinal vasculature using confocal and non-confocal scanning-laser ophthalmoscopes.
| S-EPMC6825179 | biostudies-literature
Project description:To investigate the efficacy of two widely used scatter mitigation methods: antiscatter grids (ASGs) and beam modulating with bowtie filters (BTFs), in combination with subtractive scatter correction or zeroth order normalization phantom calibration, for improving image noise, contrast, contrast-to-noise ratio (CNR), and image uniformity for on-board cone-beam CT (CBCT) imaging systems used for image-guided radiation therapy.PTRAN Monte Carlo CBCT x-ray projections of head and pelvic phantoms were calculated for combinations of beam-modulation and scatter rejection methods and images were reconstructed by in-house developed software. In addition, a simple one-dimensional analytic model was developed to predict scatter-to-primary ratio (SPR) and CNR as a function of cylindrical phantom thickness, ASG transmission, and beam modulation with bow-tie filters.ASGs were found to have slightly negative or no effect on head phantom image CNR and to modestly improve CNR (10%-20%) in pelvic phantom images. However, scatter subtraction and norm-phantom calibration perform better when applied on data acquired with ASGs. Scatter subtraction improves CT number accuracy, but increases noise, and in high SPR/low primary-photon transmission scenarios can dramatically reduce CNR and introduce streaking artifacts. The BTF is found to reduce SPR and image noise, resulting in a better trade-off between CNR and imaging dose, but introduces a circular band artifact.Our study shows that ASGs have a modest positive impact in pelvic scans and negative in head scans, scatter subtraction improves the HU accuracy but reduces CNR, while BTF has a clearly positive effect.
| S-EPMC2962662 | biostudies-other
Project description:BACKGROUND: In the biological sciences the TCID50 (median tissue culture infective dose) assay is often used to determine the strength of a virus. METHODS: When the so-called Spearman-Kaerber calculation is used, the ratio between the pfu (the number of plaque forming units, the effective number of virus particles) and the TCID50, theoretically approaches a simple function of Eulers constant. Further, the standard deviation of the logarithm of the TCID50 approaches a simple function of the dilution factor and the number of wells used for determining the ratios in the assay. However, these theoretical calculations assume that the dilutions of the assay are independent, and in practice this is not completely correct. The assay was simulated using Monte Carlo techniques. RESULTS: Our simulation studies show that the theoretical results actually hold true for practical implementations of the assay. Furthermore, the simulation studies show that the distribution of the (the log of) TCID50, although discrete in nature, has a close relationship to the normal distribution. CONCLUSION: The pfu is proportional to the TCID50 titre with a factor of about 0.56 when using the Spearman-Kaerber calculation method. The normal distribution can be used for statistical inferences and ANOVA on the (the log of) TCID50 values is meaningful with group sizes of 5 and above.
| S-EPMC3331834 | biostudies-other
Project description:Performance optimization of indirect x-ray detectors requires proper characterization of both ionizing (gamma) and optical photon transport in a heterogeneous medium. As the tool of choice for modeling detector physics, Monte Carlo methods have failed to gain traction as a design utility, due mostly to excessive simulation times and a lack of convenient simulation packages. The most important figure-of-merit in assessing detector performance is the detective quantum efficiency (DQE), for which most of the computational burden has traditionally been associated with the determination of the noise power spectrum (NPS) from an ensemble of flood images, each conventionally having 10(7) - 10(9) detected gamma photons. In this work, the authors show that the idealized conditions inherent in a numerical simulation allow for a dramatic reduction in the number of gamma and optical photons required to accurately predict the NPS.The authors derived an expression for the mean squared error (MSE) of a simulated NPS when computed using the International Electrotechnical Commission-recommended technique based on taking the 2D Fourier transform of flood images. It is shown that the MSE is inversely proportional to the number of flood images, and is independent of the input fluence provided that the input fluence is above a minimal value that avoids biasing the estimate. The authors then propose to further lower the input fluence so that each event creates a point-spread function rather than a flood field. The authors use this finding as the foundation for a novel algorithm in which the characteristic MTF(f), NPS(f), and DQE(f) curves are simultaneously generated from the results of a single run. The authors also investigate lowering the number of optical photons used in a scintillator simulation to further increase efficiency. Simulation results are compared with measurements performed on a Varian AS1000 portal imager, and with a previously published simulation performed using clinical fluence levels.On the order of only 10-100 gamma photons per flood image were required to be detected to avoid biasing the NPS estimate. This allowed for a factor of 10(7) reduction in fluence compared to clinical levels with no loss of accuracy. An optimal signal-to-noise ratio (SNR) was achieved by increasing the number of flood images from a typical value of 100 up to 500, thereby illustrating the importance of flood image quantity over the number of gammas per flood. For the point-spread ensemble technique, an additional 2× reduction in the number of incident gammas was realized. As a result, when modeling gamma transport in a thick pixelated array, the simulation time was reduced from 2.5 × 10(6) CPU min if using clinical fluence levels to 3.1 CPU min if using optimized fluence levels while also producing a higher SNR. The AS1000 DQE(f) simulation entailing both optical and radiative transport matched experimental results to within 11%, and required 14.5 min to complete on a single CPU.The authors demonstrate the feasibility of accurately modeling x-ray detector DQE(f) with completion times on the order of several minutes using a single CPU. Convenience of simulation can be achieved using GEANT4 which offers both gamma and optical photon transport capabilities.
| S-EPMC3978362 | biostudies-other