Effective dose in percutaneous transhepatic biliary drainage examination using PCXMC2.0 and MCNP5 Monte Carlo codes

ObjectivesTo estimate the organ equivalent doses and the effective doses (E) in patient undergoing percutaneous transhepatic biliary drainage (PTBD) examinations, using the MCNP5 and PCXMC2 Monte Carlo-based codes.MethodsThe purpose of this study is to estimate the organ doses to patients undergoing PTBD examinations by clinical measurements and Monte Carlo simulation. Dose area products (DAP) values were assessed during examination of 43 patients undergoing PTBD examination separated into groups based on the gender and the dimensions and location of the beam.ResultsMonte Carlo simulation of photon transport in male and female mathematical phantoms was applied using the MCNP5 and PCXMC2 codes in order to estimate equivalent organ doses. Regarding the PTBD examination the organ receiving the maximum radiation dose was the lumbar spine. The mean calculated H_T for the lumbar spine using the MCNP5 and PCXMC2 methods respectively, was 117.25 mSv and 131.7 mSv, in males. The corresponding doses were 139.45 mSv and 157.1 mSv respectively in females. The H_T values for organs receiving considerable amounts of radiation during PTBD examinations were varied between 0.16% and 73.2% for the male group and between 1.10% and 77.6% for the female group. E in females and males using MCNP5 and PCXMC2.0 was 5.88 mSv and 6.77 mSv, and 4.93 mSv and 5.60 mSv.ConclusionThe doses remain high compared to other invasive operations in interventional radiology. There is a reasonable good coincidence between the MCNP5 and PCXMC2.0 calculation for most of the organs.     

An overview of recent developments in FLUKA PET tools

The new developments of the FLUKA Positron-Emission-Tomography (PET) tools are detailed. FLUKA is a fully integrated Monte Carlo (MC) particle transport code, used for an extended range of applications, including Medical Physics. Recently, it provided the medical community with dedicated simulation tools for clinical applications, including the PET simulation package. PET is a well-established imaging technique in nuclear medicine, and a promising method for clinical in vivo treatment verification in hadrontherapy. The application of clinically established PET scanners to new irradiation environments such as hadrontherapy requires further experimental and theoretical research to which MC simulations could be applied. The FLUKA PET tools, besides featuring PET scanner models in its library, allow the configuration of new PET prototypes via the FLUKA Graphical User Interface (GUI) Flair. Both the beam time structure and scan time can be specified by the user, reproducing PET acquisitions in time, in a particle therapy scenario. Furthermore, different scoring routines allow the analysis of single and coincident events, and identification of parent isotopes generating annihilation events. Two reconstruction codes are currently supported: the Filtered Back–Projection (FBP) and Maximum–Likelihood Expectation Maximization (MLEM), the latter embedded in the tools. Compatibility with other reconstruction frameworks is also possible. The FLUKA PET tools package has been successfully tested for different detectors and scenarios, including conventional functional PET applications and in beam PET, either using radioactive sources, or simulating hadron beam irradiations. The results obtained so far confirm the FLUKA PET tools suitability to perform PET simulations in R&D environment.     

Atomistic simulations of the effects of polyglutamine chain length and solvent quality on conformational equilibria and spontaneous homodimerization

Aggregation of expanded polyglutamine tracts is associated with nine different neurodegenerative diseases, including Huntington's disease. Experiments and computer simulations have demonstrated that monomeric forms of polyglutamine molecules sample heterogeneous sets of collapsed structures in water. The current work focuses on a mechanistic characterization of polyglutamine homodimerization as a function of chain length and temperature. These studies were carried out using molecular simulations based on a recently developed continuum solvation model that was designed for studying conformational and binding equilibria of intrinsically disordered molecules such as polyglutamine systems. The main results are as follows: Polyglutamine molecules form disordered, collapsed globules in aqueous solution. These molecules spontaneously associate at conditions approaching those of typical in vitro experiments for chains of length N ≥ 15. The spontaneity of these homotypic associations increases with increasing chain length and decreases with increasing temperature. Similar and generic driving forces govern both collapse and spontaneous homodimerization of polyglutamine in aqueous milieus. Collapse and dimerization maximize self-interactions and reduce the interface between polyglutamine molecules and the surrounding solvent. Other than these generic considerations, there do not appear to be any specific structural requirements for either chain collapse or chain dimerization; that is, both collapse and dimerization are nonspecific in that disordered globules form disordered dimers. In fact, it is shown that the driving force for intermolecular associations is governed by spontaneous conformational fluctuations within monomeric polyglutamine. These results suggest that polyglutamine aggregation is unlikely to follow a homogeneous nucleation mechanism with the monomer as the critical nucleus. Instead, the results support the formation of disordered, non-β-sheet-like soluble molten oligomers as early intermediates—a proposal that is congruent with recent experimental data.     

Variation within and between cyanobacterial species and strains affects competition: Implications for phytoplankton modelling

Cyanobacteria Microcystis aeruginosa and Cylindrospermopsis raciborskii are two harmful species which co-occur and successively dominate in freshwaters globally. Within-species strain variability affects cyanobacterial population responses to environmental conditions, and it is unclear which species/strain would dominate under different environmental conditions. This study applied a Monte Carlo approach to a phytoplankton dynamic growth model to identify how growth variability of multiple strains of these two species affects their competition.Pairwise competition between four M. aeruginosa and eight C. raciborskii strains was simulated using a deterministic model, parameterized with laboratory measurements of growth and light attenuation for all strains, and run at two temperatures and light intensities. 17 000 runs were simulated for each pair using a statistical distribution with Monte Carlo approach.The model results showed that cyanobacterial competition was highly variable, depending on strains present, light and temperature conditions. There was no absolute ‘winner’ under all conditions as there were always strains predicted to coexist with the dominant strains, which were M. aeruginosa strains at 20 °C and C. raciborskii strains at 28 °C. The uncertainty in prediction of species competition outcomes was due to the substantial variability of growth responses within and between strains. Overall, this study demonstrates that within-species strain variability has a potentially large effect on cyanobacterial population dynamics, and therefore this variability may substantially reduce confidence in predicting outcomes of phytoplankton competition in deterministic models, that are based on only one set of parameters for each species or strain.     

A new cone-beam computed tomography dosimetry method providing optimal measurement positions: A Monte Carlo study

PurposeThe conventional weighted computed tomography dose index (CTDI_w) may not be suitable for cone-beam computed tomography (CBCT) dosimetry because a cross-sectional dose distribution is angularly inhomogeneous owing to partial angle irradiations. This study was conducted to develop a new dose metric (f(0)^CB_w) for CBCT dosimetry to determine a more accurate average dose in the central cross-sectional plane of a cylindrical phantom using Monte Carlo simulations.MethodsFirst, cross-sectional dose distributions of cylindrical polymethyl methacrylate phantoms over a wide range of phantom diameters (8–40 cm) were calculated for various CBCT scan protocols. Then, by obtaining linear least-squares fits of the full datasets of the cross-sectional dose distributions, the optimal radial positions, which represented measurement positions for the average phantom dose, were determined. Finally, the f(0)^CB_w method was developed by averaging point doses at the optimal radial positions of the phantoms. To demonstrate its validity, the relative differences between the average doses and each dose index value were estimated for the devised f(0)^CB_w, conventional CTDI_w, and Haba’s CTDI_w methods, respectively.ResultsThe relative differences between the average doses and each dose index value were within 4.1%, 16.7%, and 11.9% for the devised, conventional CTDI_w, and Haba’s CTDI_w methods, respectively.ConclusionsThe devised f(0)^CB_w value was calculated by averaging four “point doses” at 90° intervals and the optimal radial positions of the cylindrical phantom. The devised method can estimate the average dose more accurately than the previously developed CTDI_w methods for CBCT dosimetry.     

Monte Carlo simulations of individual variability and their effects on simulated heat stress using thermoregulatory modeling

This paper addresses a variable-dependence (VD) MC method developed based on a previous attempt (VI-MC method) (J. Therm. Biol. 29 (2004), 515) to be incorporated in a thermoregulatory model. Simulated individuals with anthropometrics by VI- and VD-MC methods for US Army population were compared using principal component analysis and Fisher's exact tests. The results indicated that VD-MC data represented overall body size as the primary component and body shape as the secondary component that were more realistic and similar to the measured US Army data (p>0.05) rather than VI-MC data (p<0.05). Such differences consequently affected individual thermoregulatory responses to simulated heat stress. The VD-MC method provides a more realistic representation of individual variability and thus underpins more realistic predictions of individual thermoregulatory responses.     

Accuracy evaluation of distance inverse square law in determining virtual electron source location in Siemens Primus linac

Aim

The aim of this study is to evaluate the accuracy of the inverse square law (ISL) method for determining location of virtual electron source (S_Vir) in Siemens Primus linac.

Forced Detection Monte Carlo Algorithms for Accelerated Blood Vessel Image Simulations

Two forced detection (FD) variance reduction Monte Carlo algorithms for image simulations of tissue‐embedded objects with matched refractive index are presented. The principle of the algorithms is to force a fraction of the photon weight to the detector at each and every scattering event. The fractional weight is given by the probability for the photon to reach the detector without further interactions. Two imaging setups are applied to a tissue model including blood vessels, where the FD algorithms produce identical results as traditional brute force simulations, while being accelerated with two orders of magnitude. Extending the methods to include refraction mismatches is discussed. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Skin models and their impact on mean glandular dose in mammography

PurposeTo quantify the influence of different skin models on mammographic breast dosimetry, based on dosimetric protocols and recent breast skin thickness findings.MethodsBy using an adapted PENELOPE (v. 2014) + PenEasy (v. 2015) Monte Carlo (MC) code, simulations were performed in order to obtain the mean glandular dose (MGD), the normalized MGD by incident air Kerma (DgN), and the glandular depth dose (GDD(z)). The geometry was based on a cranio-caudal mammographic examination. Monoenergetic and polyenergetic beams were implemented, for a breast thickness from 2 cm to 9 cm, with different compositions. Seven skin models were used: a 5 mm adipose layer; a skin layer ranging from 5 mm to 1.45 mm, a 1.45 mm skin thickness with a subcutaneous adipose layer of 2 mm and 3.55 mm.ResultsThe differences, for monoenergetic beams, are higher (up to 200%) for lower energies (8 keV), thicker and low glandular content breasts, decreasing to less than 5% at 40 keV. Without a skin layer, the differences reach a maximum of 1240%. The relative difference in DgN values for 1.45 mm skin and 5 mm adipose layers and polyenergetic beams varies from −14% to 12%.ConclusionsThe implemented MC code is suitable for mammography dosimetry calculations. The skin models have major impacts on MGD values, and the results complement previous literature findings. The current protocols should be updated to include a more realistic skin model, which provides a reliable breast dose estimation.     

Importance Sampling Via the Estimated Sampler

Monte Carlo importance sampling for evaluating numerical integrationis discussed. We consider a parametric family of sampling distributionsand propose the use of the sampling distribution estimated bymaximum likelihood. The proposed method of importance samplingusing the estimated sampling distribution is shown to improvethe asymptotic variance of the ordinary method using the truesampling distribution. The argument is closely related to thediscussion of the paradox in Henmi & Eguchi (2004). We focuson a condition under which the estimated integration value obtainedby the proposed method has asymptotic zero variance.     

Determination of backscatter factors based on the quality index for diagnostic kilovoltage x-ray beams

PurposeThis study aims to investigate the relationship between backscatter factors and Al-half-value-layers (Al-HVL) by making the quality index (QI) a parameter for diagnostic kilovoltage x-ray beams.MethodsBackscatter factors, B_w, for x-ray fluence spectra were calculated from the weighted average of B_w for monoenergetic photons of between 8 and 140 keV with field sizes of 10 cm × 10 cm to 40 cm × 40 cm. The value of B_w for monoenergetic photons was calculated from the ratio of the water kerma at the surface of a water phantom and that at the same point free-in-air using the EGSnrc/cavity code. The weighted averaged backscatter factors were validated by comparing them with those of direct Monte Carlo calculations for the x-ray fluence spectra. The B_w for the x-ray fluence spectra were classified by a QI of 0.35, 0.4, 0.5, 0.6, and 0.7 specified by the ratio of the effective energy and maximum energy. The relationship between B_w and Al-HVL was evaluated for the given QI values. The x-ray fluence spectra were generated for tube voltages of 40–140 kVp with Al-HVLs of 0.5–13.2 mm using the SpekCalc program.ResultsThe weighted averaged backscatter factors for x-ray fluence spectra agreed within 0.7% with those of the direct Monte Carlo calculations. The backscatter factors were represented by the fitting curves of R² > 0.99 with Al-HVL for the given QI values.ConclusionsIt is possible to obtain B_w more accurately by using QI specified by the measured Al-HVL.     

Integration of the M6 Cyberknife in the Moderato Monte Carlo platform and prediction of beam parameters using machine learning

PurposeThis work describes the integration of the M6 Cyberknife in the Moderato Monte Carlo platform, and introduces a machine learning method to accelerate the modelling of a linac.MethodsThe MLC-equipped M6 Cyberknife was modelled and integrated in Moderato, our in-house platform offering independent verification of radiotherapy dose distributions. The model was validated by comparing TPS dose distributions with Moderato and by film measurements. Using this model, a machine learning algorithm was trained to find electron beam parameters for other M6 devices, by simulating dose curves with varying spot size and energy. The algorithm was optimized using cross-validation and tested with measurements from other institutions equipped with a M6 Cyberknife.ResultsOptimal agreement in the Monte Carlo model was reached for a monoenergetic electron beam of 6.75 MeV with Gaussian spatial distribution of 2.4 mm FWHM. Clinical plan dose distributions from Moderato agreed within 2% with the TPS, and film measurements confirmed the accuracy of the model. Cross-validation of the prediction algorithm produced mean absolute errors of 0.1 MeV and 0.3 mm for beam energy and spot size respectively. Prediction-based simulated dose curves for other centres agreed within 3% with measurements, except for one device where differences up to 6% were detected.ConclusionsThe M6 Cyberknife was integrated in Moderato and validated through dose re-calculations and film measurements. The prediction algorithm was successfully applied to obtain electron beam parameters for other M6 devices. This method would prove useful to speed up modelling of new machines in Monte Carlo systems.     

Impact of the cavity on sinus wall dose in magnetic resonance image-guided radiation therapy

PurposeThis study aims to investigate the impact of the cavity on the sinus wall dose by comparing dose distributions with and without the sinus under magnetic fields using Monte Carlo calculations.MethodsA water phantom containing a sinus cavity (Empty) was created, and dose distributions were calculated for 1, 2, and 4 irradiation fields with 6 MV photons. The sinus in the phantom was then filled with water (Full), and the dose distributions were calculated again. The sinus was set to cubes of 2 cm and 4 cm. The magnetic field was applied to the transverse and inline direction under the magnetic flux densities of 0 T, 0.35 T, 0.5 T, 1.0 T, and 1.5 T. The dose distributions were analyzed by the dose difference, dose volume histogram, and D₂ with sinus wall thicknesses of 1 and 5 mm.ResultsD₂ in the “Empty” sinus wall under transverse magnetic fields for the 1-field and 4-field cases was 51.9% higher and 3.7% lower than that in the “Full” sinus wall at 1.5 T, respectively. Meanwhile, D₂ in the Empty sinus wall under inline magnetic fields for 1-field and 4-fields was 2.3% and 2.6% lower than that in the “Full” sinus at B = 0 T, respectively, whereas D₂ was 0.9% and 0.7% larger at 1.0 T, respectively.ConclusionsThe impact of the cavity on the sinus wall dose depends on the magnetic flux density, direction of the magnetic field and irradiation beam, and number of irradiation fields.     

Testing ecological interactions between Gnomoniopsis castaneae and Dryocosmus kuriphilus

An emerging nut rot of chestnut caused by the fungus Gnomoniopsis castaneae was reported soon after the invasion of the exotic gall wasp Dryocosmus kuriphilus in Italy. The goal of this work was to assess the association between the spread of the fungal pathogen and the infestation of the pest by testing if:I) viable inoculum of G. castaneae can be carried by adults of D. kuriphilus;II) the fungal colonization is related to the number of adults inhabiting the galls;III) the fungal colonization of chestnut buds and the oviposition are associated.Fungal isolations and PCR-based molecular assays were performed on 323 chestnut galls and on their emerging D. kuriphilus adults, whose number was compared between galls colonized and not colonized by G. castaneae. To test the association between fungal colonization and oviposition, Monte Carlo simulations assuming different scenarios of ecological interactions were carried out and validated through isolation trials performed on 597 and 688 chestnut buds collected before and after oviposition, respectively.Although DNA of G. castaneae was detected in a sample of 40% of the adults developed in colonized galls, the fungus could never be isolated from insects, suggesting that the pest is an unlikely vector of viable inoculum.On average, the emerging adults were significantly more abundant from galls colonized by G. castaneae than from not colonized ones (3.76 vs. 2.54, P < 0.05), indicating a possible fungus/pest synergy.The simulations implying no interaction between G. castaneae and D. kuriphilus after fungal colonization were confirmed as the most likely. In fact, G. castaneae was present in 33.8% of the buds before oviposition, while no association was detected between fungal colonization and oviposition (odds ratio 0.98, 0.71–1.33 95% CI). These findings suggest that the fungus/pest synergy is asymmetrically favorable to the pest and occurs after oviposition.     

Monte Carlo evaluation of the dose calculation algorithm of TomoTherapy for clinical cases in dynamic jaws mode

PurposeFor the TomoTherapy^® system, longitudinal conformation can be improved by selecting a smaller field width but at the expense of longer treatment time. Recently, the TomoEdge^® feature has been released with the possibility to move dynamically the jaws at the edges of the target volume, improving longitudinal penumbra and enabling faster treatments. Such delivery scheme requires additional modeling of treatment delivery. Using a previously validated Monte Carlo model (TomoPen), we evaluated the accuracy of the implementation of TomoEdge in the new dose engine of TomoTherapy for 15 clinical cases.MethodsTomoPen is based on PENELOPE. Particle tracking in the treatment head is performed almost instantaneously by 1) reading a particle from a phase-space file corresponding to the largest field and 2) correcting the weight of the particle depending on the actual jaw and MLC configurations using Monte Carlo pre-generated data. 15 clinical plans (5 head-and-neck, 5 lung and 5 prostate tumors) planned with TomoEdge and with the last release of the treatment planning system (VoLO^®) were re-computed with TomoPen. The resulting dose-volume histograms were compared.ResultsGood agreement was achieved overall, with deviations for the target volumes typically within 2% (D₉₅), excepted for small lung tumors (17 cm³) where a maximum deviation of 4.4% was observed for D₉₅. The results were consistent with previously reported values for static field widths.ConclusionsFor the clinical cases considered in the present study, the introduction of TomoEdge did not impact significantly the accuracy of the computed dose distributions.     

Genome analyses and modelling the relationships between coding density, recombination rate and chromosome length

In the human genomes, recombination frequency between homologous chromosomes during meiosis is highly correlated with their physical length while it differs significantly when their coding density is considered. Furthermore, it has been observed that the recombination events are distributed unevenly along the chromosomes. We have found that many of such recombination properties can be predicted by computer simulations of population evolution based on the Monte Carlo methods. For example, these simulations have shown that the probability of acceptance of the recombination events by selection is higher at the ends of chromosomes and lower in their middle parts. The regions of high coding density are more prone to enter the strategy of haplotype complementation and to form clusters of genes, which are “recombination deserts”. The phenomenon of switching in-between the purifying selection and haplotype complementation has a phase transition character, and many relations between the effective population size, coding density, chromosome size and recombination frequency are those of the power law type.     

Efficient deformation algorithm for plasmid DNA simulations

Background

Plasmid DNA molecules are closed circular molecules that are widely used in life sciences, particularly in gene therapy research. Monte Carlo methods have been used for several years to simulate the conformational behavior of DNA molecules. In each iteration these simulation methods randomly generate a new trial conformation, which is either accepted or rejected according to a criterion based on energy calculations and stochastic rules. These simulation trials are generated using a method based on crankshaft motion that, apart from some slight improvements, has remained the same for many years.

Results

In this paper, we present a new algorithm for the deformation of plasmid DNA molecules for Monte Carlo simulations. The move underlying our algorithm preserves the size and connectivity of straight-line segments of the plasmid DNA skeleton. We also present the results of three experiments comparing our deformation move with the standard and biased crankshaft moves in terms of acceptance ratio of the trials, energy and temperature evolution, and average displacement of the molecule. Our algorithm can also be used as a generic geometric algorithm for the deformation of regular polygons or polylines that preserves the connections and lengths of their segments.

Conclusion

Compared with both crankshaft moves, our move generates simulation trials with higher acceptance ratios and smoother deformations, making it suitable for real-time visualization of plasmid DNA coiling. For that purpose, we have adopted a DNA assembly algorithm that uses nucleotides as building blocks.     

Mechanistic DNA damage simulations in Geant4-DNA Part 2: Electron and proton damage in a bacterial cell

We extended a generic Geant4 application for mechanistic DNA damage simulations to an Escherichia coli cell geometry, finding electron damage yields and proton damage yields largely in line with experimental results. Depending on the simulation of radical scavenging, electrons double strand breaks (DSBs) yields range from 0.004 to 0.010 DSB Gy⁻¹ Mbp⁻¹, while protons have yields ranging from 0.004 DSB Gy⁻¹ Mbp⁻¹ at low LETs and with strict assumptions concerning scavenging, up to 0.020 DSB Gy⁻¹ Mbp⁻¹ at high LETs and when scavenging is weakest. Mechanistic DNA damage simulations can provide important limits on the extent to which physical processes can impact biology in low background experiments. We demonstrate the utility of these studies for low dose radiation biology calculating that in E. coli, the median rate at which the radiation background induces double strand breaks is 2.8 × 10⁻⁸ DSB day⁻¹, significantly less than the mutation rate per generation measured in E. coli, which is on the order of 10⁻³.