D. Emfietzoglou

Monte Carlo single-cell dosimetry of Auger-electron emitting radionuclides

A hybrid Monte Carlo transport scheme combining event-by-event and condensed-history simulation with a full account of energy-loss straggling was used to study the dosimetric characteristics of the Auger-emitting radionuclides 67Ga, 99mTc, 111In, 123I, 125I and 201Tl at the single-cell level. The influence of the intracellular localization of the Auger radionuclide upon cellular S-values, radial dose rate profiles and dose-volume-histograms (DVHs) was investigated. For the case where the radiopharmaceutical was either internalized into the cytoplasm or remained bound onto the cell surface (non-internalized), the dose to the cell nucleus was found to differ significantly from the MIRD values and other published data. In this case, the assumption of a homogeneous distribution throughout the cell is shown to significantly overestimate the nuclear dose. A dosimetric case study relevant to the radioimmunotherapy of single lymphoma B-cells with 125I and 123I is presented.

A Monte Carlo study of absorbed dose distributions in both the vapor and liquid phases of water by intermediate energy electrons based on different condensed-history transport schemes.

Monte Carlo transport calculations of dose point kernels (DPKs) and depth dose profiles (DDPs) in both the vapor and liquid phases of water are presented for electrons with initial energy between 10 keV and 1 MeV. The results are obtained by the MC4 code using three different implementations of the condensed-history technique for inelastic collisions, namely the continuous slowing down approximation, the mixed-simulation with delta-ray transport and the addition of straggling distributions for soft collisions derived from accurate relativistic Born cross sections. In all schemes, elastic collisions are simulated individually based on single-scattering cross sections. Electron transport below 10 keV is performed in an event-by-event mode. Differences on inelastic interactions between the vapor and liquid phase are treated explicitly using our recently developed dielectric response function which is supplemented by relativistic corrections and the transverse contribution. On the whole, the interaction coefficients used agree to better than approximately 5% with NIST/ICRU values. It is shown that condensed phase effects in both DPKs and DDPs practically vanish above 100 keV. The effect of delta-rays, although decreases with energy, is sizeable leading to more diffused distributions, especially for DPKs. The addition of straggling for soft collisions is practically inconsequential above a few hundred keV. An extensive benchmarking with other condensed-history codes is provided.

Analytic expressions for the inelastic scattering and energy loss of electron and proton beams in carbon nanotubes

We have determined “effective” Bethe coefficients and the mean excitation energy of stopping theory (I-value) for multiwalled carbon nanotubes (MWCNTs) and single-walled carbon nanotube (SWCNT) bundles based on a sum-rule constrained optical-data model energy loss function with improved asymptotic properties. Noticeable differences between MWCNTs, SWCNT bundles, and the three allotropes of carbon (diamond, graphite, glassy carbon) are found. By means of Bethe’s asymptotic approximation, the inelastic scattering cross section, the electronic stopping power, and the average energy transfer to target electrons in a single inelastic collision, are calculated analytically for a broad range of electron and proton beam energies using realistic excitation parameters.

A Monte Carlo study of cellular S-factors for 1 keV to 1 MeV electrons

A systematic study of cellular S-factors and absorbed fractions for monoenergetic electrons of initial energy from 1 keV to 1 MeV is presented. The calculations are based on our in-house Monte Carlo codes which have been developed to simulate electron transport up to a few MeV using both event-by-event and condensed-history techniques. An extensive comparison with the MIRD tabulations is presented for spherical volumes of 1-10 microm radius and various source-to-target combinations relevant to the intracellular localization of the emitted electrons. When the primary electron range is comparable to the sphere radius, we find significantly higher values from the MIRD, while with increasing electron energy the escape of delta-rays leads gradually to the opposite effect. The largest differences with the MIRD are found for geometries where the target region is at some distance from the source region (e.g. surface-to-nucleus or cytoplasm-to-nucleus). The sensitivity of the results to different transport approximations is examined. The grouping of inelastic collisions is found adequate as long as delta-rays are explicitly simulated, while the inclusion of straggling for soft collisions has a negligible effect.

A unified spatio-temporal parallelization framework for accelerated Monte Carlo radiobiological modeling of electron tracks and subsequent radiation chemistry

Abstract Monte Carlo (MC) nano-scale modeling of the cellular damage is desirable but most times is prohibitive for large scaled systems due to their intensive computational cost. In this study a parallelized computational framework is presented, for accelerated MC simulations of both particle propagation and subsequent radiation chemistry at the subcellular level. Given the inherent parallelism of the electron tracks, the physical stage was “embarrassingly parallelized” into a number of independent tasks. For the chemical stage, the diffusion–reaction of the radical species was simulated with a time-driven kinetic Monte Carlo algorithm (KMC) based on the Smoluchowski formalism and the parallelization was realized by employing a spatio-temporal linked-list cell method based on a spatial subdivision with a uniform grid. The evaluation of our method was established on two metrics: speedup and efficiency. The results indicated a linear speedup ratio for the physical stage and a linear latency for shared- versus a distributed-memory system with a maximum of 3.6 ⋅ 10 − 3 % per electron track. For the chemical stage, a series of simulations were performed to show how the execution time per step was scaling with respect to the number of radical species and a 5.7× speedup was achieved when a larger number of reactants were simulated and eight processors were employed. The simulations were deployed on the Amazon EC2 infrastructure. It is also elucidated how the overhead started becoming significant as the number of reactant species decrease relative to the number of processors. The method reported here lays the methodological foundations for accelerated MC simulations and allows envisaging a future use for large-scale radiobiological modeling of multi-cellular systems involved into a clinical scenario.

Parallelization of a Monte Carlo particle transport simulation code

We have developed a high performance version of the Monte Carlo particle transport simulation code MC4. The original application code, developed in Visual Basic for Applications (VBA) for Microsoft Excel, was first rewritten in the C programming language for improving code portability. Several pseudo-random number generators have been also integrated and studied. The new MC4 version was then parallelized for shared and distributed-memory multiprocessor systems using the Message Passing Interface. Two parallel pseudo-random number generator libraries (SPRNG and DCMT) have been seamlessly integrated. The performance speedup of parallel MC4 has been studied on a variety of parallel computing architectures including an Intel Xeon server with 4 dual-core processors, a Sun cluster consisting of 16 nodes of 2 dual-core AMD Opteron processors and a 200 dual-processor HP cluster. For large problem size, which is limited only by the physical memory of the multiprocessor server, the speedup results are almost linear on all systems. We have validated the parallel implementation against the serial VBA and C implementations using the same random number generator. Our experimental results on the transport and energy loss of electrons in a water medium show that the serial and parallel codes are equivalent in accuracy. The present improvements allow for studying of higher particle energies with the use of more accurate physical models, and improve statistics as more particles tracks can be simulated in low response time.