Technology transfer from HEP computing to the medical field: overview and application to dosimetry

We show how nowadays it is possible to achieve the goal of accuracy and fast computation response in radiotherapic dosimetry using MonteCarlo methods, together with a grid computing model. We present a complete, fully functional prototype system for brachytherapy, entirely based on open source software systems originally developed for High Energy Physics experiments. It integrates a Geant4-based simulation component, an AIDA-based dosimetric analysis, a web-based user interface, and distributed processing either on a local computing farm or on geographically spread nodes. Thanks to the object-oriented approach adopted for the architecture, the work presented can be easily extended to become a general purpose dosimetric system, capable to address all radiotherapic techniques. An extension for application to dosimetric studies for IMRT is in progress

Improved integrated nucleus-nucleus inelastic cross sections for light nuclides in Geant4

We propose a new root-mean-square radius parameterization for light nuclei A 30 suitable for use in Geant4 calculations of nucleus-nucleus total hadronic inelastic scattering cross sections. The new approach takes into account the proton-neutron asymmetry of the reactants, and was fit to 360 measured total inelastic cross sections from the EXFOR database. Measured nuclear radii are better described in the new approach than the current Geant4 implementation, particularly for unstable nuclides, and there is better agreement with measured cross sections for both stable and unstable nuclides. The improved parameterization should help in carbon-ion therapy applications in particular.This work was supported by the Australian Research Council under Grants DP170102423 and DP170100967

Comparative analysis of the secondary electron yield from carbon nanoparticles and pure water medium

The production of secondary electrons generated by carbon nanoparticles and pure water medium irradiated by fast protons is studied by means of model approaches and Monte Carlo simulations. It is demonstrated that due to a prominent collective response to an external field, the nanoparticles embedded in the medium enhance the yield of low-energy electrons. The maximal enhancement is observed for electrons in the energy range where plasmons, which are excited in the nanoparticles, play the dominant role. Electron yield from a solid carbon nanoparticle composed of fullerite, a crystalline form of C60 fullerene, is demonstrated to be several times higher than that from liquid water. Decay of plasmon excitations in carbon-based nanosystems thus represents a mechanism of increase of the low-energy electron yield, similar to the case of sensitizing metal nanoparticles. This observation gives a hint for investigation of novel types of sensitizers to be composed of metallic and organic parts.Comment: 9 pages, 5 figures; accepted for publication in the Topical Issue "COST Action Nano-IBCT: Nano-scale processes behind Ion-Beam Cancer Therapy" of Eur. Phys. J. D. arXiv admin note: text overlap with arXiv:1412.553

In Silico Nanodosimetry: New Insights into Nontargeted Biological Responses to Radiation

The long-held view that radiation-induced biological damage must be initiated in the cell nucleus, either on or near DNA itself, is being confronted by mounting evidence to suggest otherwise. While the efficacy of cell death may be determined by radiation damage to nuclear DNA, a plethora of less deterministic biological responses has been observed when DNA is not targeted. These so-called nontargeted responses cannot be understood in the framework of DNA-centric radiobiological models; what is needed are new physically motivated models that address the damage-sensing signalling pathways triggered by the production of reactive free radicals. To this end, we have conducted a series of in silico experiments aimed at elucidating the underlying physical processes responsible for nontargeted biological responses to radiation. Our simulation studies implement new results on very low-energy electromagnetic interactions in liquid water (applicable down to nanoscales) and we also consider a realistic simulation of extranuclear microbeam irradiation of a cell. Our results support the idea that organelles with important functional roles, such as mitochondria and lysosomes, as well as membranes, are viable targets for ionizations and excitations, and their chemical composition and density are critical to determining the free radical yield and ensuing biological responses

The GEANT4 toolkit capability in the hadron therapy field: simulation of a transport beam line

At Laboratori Nazionali del Sud of the Instituto Nazionale di Fisica Nucleare of Catania (Sicily, Italy), the first Italian hadron therapy facility named CATANA (Centro di AdroTerapia ed Applicazioni Nucleari Avanzate) has been realized. Inside CATANA 62 MeV proton beams, accelerated by a superconducting cyclotron, are used for the radiotherapeutic treatments of some types of ocular tumours. Therapy with hadron beams still represents a pioneer technique, and only a few centers worldwide can provide this advanced specialized cancer treatment. On the basis of the experience so far gained, and considering the future hadron-therapy facilities to be developed (Rinecker, Munich Germany, Heidelberg/GSI, Darmstadt, Germany, PSI Villigen, Switzerland, CNAO, Pavia, Italy, Centro di Adroterapia, Catania, Italy) we decided to develop a Monte Carlo application based on the GEANT4 toolkit, for the design, the realization and the optimization of a proton-therapy beam line. Another feature of our project is to provide a general tool able to study the interactions of hadrons with the human tissue and to test the analytical-based treatment planning systems actually used in the routine practice. All the typical elements of a hadron-therapy line, such as diffusers, range shifters, collimators and detectors were modelled. In particular, we simulated the Markus type ionization chamber and a Gaf Chromic film as dosimeters to reconstruct the depth (Bragg peak and Spread Out Bragg Peak) and lateral dose distributions, respectively. We validated our simulated detectors comparing the results with the experimental data available in our facility

Microdosimetry of electrons in liquid water using the low-energy models of Geant4

The biological effects of ionizing radiation at the cellular level are frequently studied using the well-known formalism of microdosimetry, which provides a quantitative description of the stochastic aspects of energy deposition in irradiated media. Energy deposition can be simulated using Monte Carlo codes, some adopting a computationally efficient condensed-history approach, while others follow a more detailed track-structure approach. In this work, we present the simulation of microdosimetry spectra and related quantities (frequency-mean and dose-mean lineal energies) for incident monoenergetic electrons (50 eV-10 keV) in spheres of liquid water with dimensions comparable to the size of biological targets: base pairs (2 nm diameter), nucleosomes (10 nm), chromatin fibres (30 nm) and chromosomes (300 nm). Simulations are performed using the condensed-history low-energy physics models ( Livermore and Penelope ) and the track-structure Geant4-DNA physics models, available in the Geant4 Monte Carlo simulation toolkit. The spectra are compared and the influence of simulation parameters and different physics models, with emphasis on recent developments, is discussed, underlining the suitability of Geant4-DNA models for microdosimetry simulations. It is further shown that with an appropriate choice of simulation parameters, condensed-history transport may yield reasonable results for sphere sizes as small as a few tens of a nanometer

Opportunistic dose amplification for proton and carbon ion therapy via capture of internally generated thermal neutrons

This paper presents Neutron Capture Enhanced Particle Therapy (NCEPT), a method for enhancing the radiation dose delivered to a tumour relative to surrounding healthy tissues during proton and carbon ion therapy by capturing thermal neutrons produced inside the treatment volume during irradiation. NCEPT utilises extant and in-development boron-10 and gadolinium-157-based drugs from the related field of neutron capture therapy. Using Monte Carlo simulations, we demonstrate that a typical proton or carbon ion therapy treatment plan generates an approximately uniform thermal neutron field within the target volume, centred around the beam path. The tissue concentrations of neutron capture agents required to obtain an arbitrary 10% increase in biological effective dose are estimated for realistic treatment plans, and compared to concentrations previously reported in the literature. We conclude that the proposed method is theoretically feasible, and can provide a worthwhile improvement in the dose delivered to the tumour relative to healthy tissue with readily achievable concentrations of neutron capture enhancement drugs

Correction factors to convert microdosimetry measurements in silicon to tissue in \u3csup\u3e12\u3c/sup\u3eC ion therapy

Silicon microdosimetry is a promising technology for heavy ion therapy (HIT) quality assurance, because of its sub-mm spatial resolution and capability to determine radiation effects at a cellular level in a mixed radiation field. A drawback of silicon is not being tissue-equivalent, thus the need to convert the detector response obtained in silicon to tissue. This paper presents a method for converting silicon microdosimetric spectra to tissue for a therapeutic 12C beam, based on Monte Carlo simulations. The energy deposition spectra in a 10 μm sized silicon cylindrical sensitive volume (SV) were found to be equivalent to those measured in a tissue SV, with the same shape, but with dimensions scaled by a factor κ equal to 0.57 and 0.54 for muscle and water, respectively. A low energy correction factor was determined to account for the enhanced response in silicon at low energy depositions, produced by electrons. The concept of the mean path length (lPath) to calculate the lineal energy was introduced as an alternative to the mean chord length (l) because it was found that adopting Cauchy\u27s formula for the (l) was not appropriate for the radiation field typical of HIT as it is very directional (lPath) can be determined based on the peak of the lineal energy distribution produced by the incident carbon beam. Furthermore it was demonstrated that the thickness of the SV along the direction of the incident 12C ion beam can be adopted as (lPath). The tissue equivalence conversion method and (lPath) were adopted to determine the RBE10, calculated using a modified microdosimetric kinetic model, applied to the microdosimetric spectra resulting from the simulation study. Comparison of the RBE10 along the Bragg peak to experimental TEPC measurements at HIMAC, NIRS, showed good agreement. Such agreement demonstrates the validity of the developed tissue equivalence correction factors and of the determination of (lPath)

Comparison of phantom materials for use in quality assurance of microbeam radiation therapy

Microbeam radiation therapy (MRT) is a promising radiotherapy modality that uses arrays of spatially fractionated micrometre-sized beams of synchrotron radiation to irradiate tumours. Routine dosimetry quality assurance (QA) prior to treatment is necessary to identify any changes in beam condition from the treatment plan, and is undertaken using solid homogeneous phantoms. Solid phantoms are designed for, and routinely used in, megavoltage X-ray beam radiation therapy. These solid phantoms are not necessarily designed to be water-equivalent at low X-ray energies, and therefore may not be suitable for MRT QA. This work quantitatively determines the most appropriate solid phantom to use in dosimetric MRT QA. Simulated dose profiles of various phantom materials were compared with those calculated in water under the same conditions. The phantoms under consideration were RMI457 Solid Water (Gammex-RMI, Middleton, WI, USA), Plastic Water (CIRS, Norfolk, VA, USA), Plastic Water DT (CIRS, Norfolk, VA, USA), PAGAT (CIRS, Norfolk, VA, USA), RW3 Solid Phantom (PTW Freiburg, Freiburg, Germany), PMMA, Virtual Water (Med-Cal, Verona, WI, USA) and Perspex. RMI457 Solid Water and Virtual Water were found to be the best approximations for water in MRT dosimetry (within ±3% deviation in peak and 6% in valley). RW3 and Plastic Water DT approximate the relative dose distribution in water (within ±3% deviation in the peak and 5% in the valley). PAGAT, PMMA, Perspex and Plastic Water are not recommended to be used as phantoms for MRT QA, due to dosimetric discrepancies greater than 5%

Fast and accurate dose predictions for novel radiotherapy treatments in heterogeneous phantoms using conditional 3D‐UNet generative adversarial networks

Purpose: Novel radiotherapy techniques like synchrotron X-ray microbeam radiation therapy (MRT) require fast dose distribution predictions that are accurate at the sub-mm level, especially close to tissue/bone/air interfaces. Monte Carlo (MC) physics simulations are recognized to be one of the most accurate tools to predict the dose delivered in a target tissue but can be very time consuming and therefore prohibitive for treatment planning. Faster dose prediction algorithms are usually developed for clinically deployed treatments only. In this work, we explore a new approach for fast and accurate dose estimations suitable for novel treatments using digital phantoms used in preclinical development and modern machine learning techniques. We develop a generative adversarial network (GAN) model, which is able to emulate the equivalent Geant4 MC simulation with adequate accuracy and use it to predict the radiation dose delivered by a broad synchrotron beam to various phantoms. Methods: The energy depositions used for the training of the GAN are obtained using full Geant4 MC simulations of a synchrotron radiation broad beam passing through the phantoms. The energy deposition is scored and predicted in voxel matrices of size 140 × 18 × 18 with a voxel edge length of 1 mm. The GAN model consists of two competing 3D convolutional neural networks, which are conditioned on the photon beam and phantom properties. The generator network has a U-Net structure and is designed to predict the energy depositions of the photon beam inside three phantoms of variable geometry with increasing complexity. The critic network is a relatively simple convolutional network, which is trained to distinguish energy depositions predicted by the generator from the ones obtained with the full MC simulation. Results: The energy deposition predictions inside all phantom geometries under investigation show deviations of less than 3% of the maximum deposited energy from the simulation for roughly 99% of the voxels in the field of the beam. Inside the most realistic phantom, a simple pediatric head, the model predictions deviate by less than 1% of the maximal energy deposition from the simulations in more than 96% of the in-field voxels. For all three phantoms, the model generalizes the energy deposition predictions well to phantom geometries, which have not been used for training the model but are interpolations of the training data in multiple dimensions. The computing time for a single prediction is reduced from several hundred hours using Geant4 simulation to less than a second using the GAN model. Conclusions: The proposed GAN model predicts dose distributions inside unknown phantoms with only small deviations from the full MC simulation with computations times of less than a second. It demonstrates good interpolation ability to unseen but similar phantom geometries and is flexible enough to be trained on data with different radiation scenarios without the need for optimization of the model parameter. This proof-of-concept encourages to apply and further develop the model for the use in MRT treatment planning, which requires fast and accurate predictions with sub-mm resolutions