Ion beam therapy is a rapidly growing technique for tumor radiation therapy. Ions allow for a high dose deposition in the tumor region, while sparing the surrounding healthy tissue. For this reason, ...the highest possible accuracy in the calculation of dose and its spatial distribution is required in treatment planning. On one hand, commonly used treatment planning software solutions adopt a simplified beam-body interaction model by remapping pre-calculated dose distributions into a 3D water-equivalent representation of the patient morphology. On the other hand, Monte Carlo (MC) simulations, which explicitly take into account all the details in the interaction of particles with human tissues, are considered to be the most reliable tool to address the complexity of mixed field irradiation in a heterogeneous environment. However, full MC calculations are not routinely used in clinical practice because they typically demand substantial computational resources. Therefore MC simulations are usually only used to check treatment plans for a restricted number of difficult cases. The advent of general-purpose programming GPU cards prompted the development of trimmed-down MC-based dose engines which can significantly reduce the time needed to recalculate a treatment plan with respect to standard MC codes in CPU hardware. In this work, we report on the development of fred, a new MC simulation platform for treatment planning in ion beam therapy. The code can transport particles through a 3D voxel grid using a class II MC algorithm. Both primary and secondary particles are tracked and their energy deposition is scored along the trajectory. Effective models for particle-medium interaction have been implemented, balancing accuracy in dose deposition with computational cost. Currently, the most refined module is the transport of proton beams in water: single pencil beam dose-depth distributions obtained with fred agree with those produced by standard MC codes within 1-2% of the Bragg peak in the therapeutic energy range. A comparison with measurements taken at the CNAO treatment center shows that the lateral dose tails are reproduced within 2% in the field size factor test up to 20 cm. The tracing kernel can run on GPU hardware, achieving 10 million primary Formula: see text on a single card. This performance allows one to recalculate a proton treatment plan at 1% of the total particles in just a few minutes.
Monte Carlo simulations play a crucial role for in-vivo treatment monitoring based on PET and prompt gamma imaging in proton and carbon-ion therapies. The accuracy of the nuclear fragmentation models ...implemented in these codes might affect the quality of the treatment verification. In this paper, we investigate the nuclear models implemented in GATE/Geant4 and FLUKA by comparing the angular and energy distributions of secondary particles exiting a homogeneous target of PMMA. Comparison results were restricted to fragmentation of (16)O and (12)C. Despite the very simple target and set-up, substantial discrepancies were observed between the two codes. For instance, the number of high energy (>1 MeV) prompt gammas exiting the target was about twice as large with GATE/Geant4 than with FLUKA both for proton and carbon ion beams. Such differences were not observed for the predicted annihilation photon production yields, for which ratios of 1.09 and 1.20 were obtained between GATE and FLUKA for the proton beam and the carbon ion beam, respectively. For neutrons and protons, discrepancies from 14% (exiting protons-carbon ion beam) to 57% (exiting neutrons-proton beam) have been identified in production yields as well as in the energy spectra for neutrons.
In the field of radiotherapy, Monte Carlo (MC) particle transport calculations are recognized for their superior accuracy in predicting dose and fluence distributions in patient geometries compared ...to analytical algorithms which are generally used for treatment planning due to their shorter execution times. In this work, a newly developed MC-based treatment planning (MCTP) tool for proton therapy is proposed to support treatment planning studies and research applications. It allows for single-field and simultaneous multiple-field optimization in realistic treatment scenarios and is based on the MC code FLUKA. Relative biological effectiveness (RBE)-weighted dose is optimized either with the common approach using a constant RBE of 1.1 or using a variable RBE according to radiobiological input tables. A validated reimplementation of the local effect model was used in this work to generate radiobiological input tables. Examples of treatment plans in water phantoms and in patient-CT geometries together with an experimental dosimetric validation of the plans are presented for clinical treatment parameters as used at the Italian National Center for Oncological Hadron Therapy. To conclude, a versatile MCTP tool for proton therapy was developed and validated for realistic patient treatment scenarios against dosimetric measurements and commercial analytical TP calculations. It is aimed to be used in future for research and to support treatment planning at state-of-the-art ion beam therapy facilities.
The use and interest in Monte Carlo (MC) techniques in the field of medical physics have been rapidly increasing in the past years. This is the case especially in particle therapy, where accurate ...simulations of different physics processes in complex patient geometries are crucial for a successful patient treatment and for many related research and development activities. Thanks to the detailed implementation of physics processes in any type of material, to the capability of tracking particles in 3D, and to the possibility of including the most important radiobiological effects, MC simulations have become an essential calculation tool not only for dose calculations but also for many other purposes, like the design and commissioning of novel clinical facilities, shielding and radiation protection, the commissioning of treatment planning systems, and prediction and interpretation of data for range monitoring strategies. MC simulations are starting to be more frequently used in clinical practice, especially in the form of specialized codes oriented to dose calculations that can be performed in short time. The use of general purpose MC codes is instead more devoted to research. Despite the increased use of MC simulations for patient treatments, the existing literature suggests that there are still a number of challenges to be faced in order to increase the accuracy of MC calculations for patient treatments. The goal of this review is to discuss some of these remaining challenges. Undoubtedly, it is a work for which a multidisciplinary approach is required. Here, we try to identify some of the aspects where the community involved in applied nuclear physics, radiation biophysics, and computing development can contribute to find solutions. We have selected four specific challenges: i) the development of models in MC to describe nuclear physics interactions, ii) modeling of radiobiological processes in MC simulations, iii) developments of MC-based treatment planning tools, and iv) developments of fast MC codes. For each of them, we describe the underlying problems, present selected examples of proposed solutions, and try to give recommendations for future research.
The high dose conformity and healthy tissue sparing achievable in Particle Therapy when using C ions calls for safety factors in treatment planning, to prevent the tumor under-dosage related to the ...possible occurrence of inter-fractional morphological changes during a treatment. This limitation could be overcome by a range monitor, still missing in clinical routine, capable of providing on-line feedback. The Dose Profiler (DP) is a detector developed within the INnovative Solution for In-beam Dosimetry in hadronthErapy (INSIDE) collaboration for the monitoring of carbon ion treatments at the CNAO facility (Centro Nazionale di Adroterapia Oncologica) exploiting the detection of charged secondary fragments that escape from the patient. The DP capability to detect inter-fractional changes is demonstrated by comparing the obtained fragment emission maps in different fractions of the treatments enrolled in the first ever clinical trial of such a monitoring system, performed at CNAO. The case of a CNAO patient that underwent a significant morphological change is presented in detail, focusing on the implications that can be drawn for the achievable inter-fractional monitoring DP sensitivity in real clinical conditions. The results have been cross-checked against a simulation study.
. The Monte Carlo simulation software is a valuable tool in radiation therapy, in particular to achieve the needed accuracy in the dose evaluation for the treatment plans optimisation. The current ...challenge in this field is the time reduction to open the way to many clinical applications for which the computational time is an issue. In this manuscript we present an innovative GPU-accelerated Monte Carlo software for dose valuation in electron and photon based radiotherapy, developed as an update of the FRED (Fast paRticle thErapy Dose evaluator) software.
. The code transports particles through a 3D voxel grid, while scoring their energy deposition along their trajectory. The models of electromagnetic interactions in the energy region between 1 MeV-1 GeV available in literature have been implemented to efficiently run on GPUs, allowing to combine a fast tracking while keeping high accuracy in dose assessment. The FRED software has been bench-marked against state-of-art full MC (FLUKA, GEANT4) in the realm of two different radiotherapy applications: Intra-Operative Radio Therapy and Very High Electron Energy radiotherapy applications.
. The single pencil beam dose-depth profiles in water as well as the dose map computed on non-homogeneous phantom agree with full-MCs at 2% level, observing a gain in processing time from 200 to 5000.
. Such performance allows for computing a plan with electron beams in few minutes with an accuracy of ∼%, demonstrating the FRED potential to be adopted for fast plan re-calculation in photon or electron radiotherapy applications.
The use of charged particles and nuclei in cancer therapy is one of the most successful cases of application of nuclear physics to medicine. The physical advantages in terms of precision and ...selectivity, combined with the biological properties of densely ionizing radiation, make charged particle approach an elective choice in a number of cases. Hadron therapy is in continuous development and nuclear physicists can give important contributions to this discipline. In this work some of the relevant aspects in nuclear physics will be reviewed, summarizing the most important directions of research and development.
Nuclear fragmentation measurements are necessary when using heavy-ion beams in hadrontherapy to predict the effects of the ion nuclear interactions within the human body. Moreover, they are also ...fundamental to validate and improve the Monte Carlo codes for their use in planning tumor treatments. Nowadays, a very limited set of carbon fragmentation cross sections are being measured, and in particular, to our knowledge, no double-differential fragmentation cross sections at intermediate energies are available in the literature. In this work, we have measured the double-differential cross sections and the angular distributions of the secondary fragments produced in the (12)C fragmentation at 62 A MeV on a thin carbon target. The experimental data have been used to benchmark the prediction capability of the Geant4 Monte Carlo code at intermediate energies, where it was never tested before. In particular, we have compared the experimental data with the predictions of two Geant4 nuclear reaction models: the Binary Light Ions Cascade and the Quantum Molecular Dynamic. From the comparison, it has been observed that the Binary Light Ions Cascade approximates the angular distributions of the fragment production cross sections better than the Quantum Molecular Dynamic model. However, the discrepancies observed between the experimental data and the Monte Carlo simulations lead to the conclusion that the prediction capability of both models needs to be improved at intermediate energies.
The calculation algorithm of a modern treatment planning system for ion-beam radiotherapy should ideally be able to deal with different ion species (e.g. protons and carbon ions), to provide relative ...biological effectiveness (RBE) evaluations and to describe different beam lines. In this work we propose a new approach for ion irradiation outcomes computations, the beamlet superposition (BS) model, which satisfies these requirements. This model applies and extends the concepts of previous fluence-weighted pencil-beam algorithms to quantities of radiobiological interest other than dose, i.e. RBE- and LET-related quantities. It describes an ion beam through a beam-line specific, weighted superposition of universal beamlets. The universal physical and radiobiological irradiation effect of the beamlets on a representative set of water-like tissues is evaluated once, coupling the per-track information derived from FLUKA Monte Carlo simulations with the radiobiological effectiveness provided by the microdosimetric kinetic model and the local effect model. Thanks to an extension of the superposition concept, the beamlet irradiation action superposition is applicable for the evaluation of dose, RBE and LET distributions. The weight function for the beamlets superposition is derived from the beam phase space density at the patient entrance. A general beam model commissioning procedure is proposed, which has successfully been tested on the CNAO beam line. The BS model provides the evaluation of different irradiation quantities for different ions, the adaptability permitted by weight functions and the evaluation speed of analitical approaches. Benchmarking plans in simple geometries and clinical plans are shown to demonstrate the model capabilities.
The heterogeneity of breast cancer plays a major role in drug response and resistance and has been extensively characterized at the genomic level. Here, a single-cell breast cancer mass cytometry ...(BCMC) panel is optimized to identify cell phenotypes and their oncogenic signalling states in a biobank of patient-derived tumour xenograft (PDTX) models representing the diversity of human breast cancer. The BCMC panel identifies 13 cellular phenotypes (11 human and 2 murine), associated with both breast cancer subtypes and specific genomic features. Pre-treatment cellular phenotypic composition is a determinant of response to anticancer therapies. Single-cell profiling also reveals drug-induced cellular phenotypic dynamics, unravelling previously unnoticed intra-tumour response diversity. The comprehensive view of the landscapes of cellular phenotypic heterogeneity in PDTXs uncovered by the BCMC panel, which is mirrored in primary human tumours, has profound implications for understanding and predicting therapy response and resistance.
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