Integrating microdosimetricin vitroRBE models for particle therapy into TOPAS MC using the MicrOdosimetry-based modeliNg for RBE ASsessment (MONAS) tool.

Objective.In this paper, we present MONAS (MicrOdosimetry-based modelliNg for relative biological effectiveness (RBE) ASsessment) toolkit. MONAS is a TOPAS Monte Carlo extension, that combines simulations of microdosimetric distributions with radiobiological microdosimetry-based models for predicting cell survival curves and dose-dependent RBE.Approach.MONAS expands TOPAS microdosimetric extension, by including novel specific energy scorers to calculate the single- and multi-event specific energy microdosimetric distributions at different micrometer scales. These spectra are used as physical input to three different formulations of themicrodosimetric kinetic model, and to thegeneralized stochastic microdosimetric model(GSM2), to predict dose-dependent cell survival fraction and RBE. MONAS predictions are then validated against experimental microdosimetric spectra andin vitrosurvival fraction data. To show the MONAS features, we present two different applications of the code: (i) the depth-RBE curve calculation from a passively scattered proton SOBP and monoenergetic12C-ion beam by using experimentally validated spectra as physical input, and (ii) the calculation of the 3D RBE distribution on a real head and neck patient geometry treated with protons.Main results.MONAS can estimate dose-dependent RBE and cell survival curves from experimentally validated microdosimetric spectra with four clinically relevant radiobiological models. From the radiobiological characterization of a proton SOBP and12C fields, we observe the well-known trend of increasing RBE values at the distal edge of the radiation field. The 3D RBE map calculated confirmed the trend observed in the analysis of the SOBP, with the highest RBE values found in the distal edge of the target.Significance.MONAS extension offers a comprehensive microdosimetry-based framework for assessing the biological effects of particle radiation in both research and clinical environments, pushing closer the experimental physics-based description to the biological damage assessment, contributing to bridging the gap between a microdosimetric description of the radiation field and its application in proton therapy treatment with variable RBE.

An artificial intelligence-based model for cell killing prediction: development, validation and explainability analysis of the ANAKIN model.

The present work develops ANAKIN: anArtificial iNtelligence bAsed model for (radiation-induced) cell KIlliNg prediction. ANAKIN is trained and tested over 513 cell survival experiments with different types of radiation contained in the publicly available PIDE database. We show how ANAKIN accurately predicts several relevant biological endpoints over a wide broad range on ion beams and for a high number of cell-lines. We compare the prediction of ANAKIN to the only two radiobiological models forRelative Biological Effectivenessprediction used in clinics, that is theMicrodosimetric Kinetic Modeland theLocal Effect Model(LEM version III), showing how ANAKIN has higher accuracy over the all considered cell survival fractions. At last, via modern techniques ofExplainable Artificial Intelligence(XAI), we show how ANAKIN predictions can be understood and explained, highlighting how ANAKIN is in fact able to reproduce relevant well-known biological patterns, such as the overkilling effect.

Towards sustainable human space exploration-priorities for radiation research to quantify and mitigate radiation risks.

Human spaceflight is entering a new era of sustainable human space exploration. By 2030 humans will regularly fly to the Moon's orbit, return to the Moon's surface and preparations for crewed Mars missions will intensify. In planning these undertakings, several challenges will need to be addressed in order to ensure the safety of astronauts during their space travels. One of the important challenges to overcome, that could be a major showstopper of the space endeavor, is the exposure to the space radiation environment. There is an urgent need for quantifying, managing and limiting the detrimental health risks and electronics damage induced by space radiation exposure. Such risks raise key priority topics for space research programs. Risk limitation involves obtaining a better understanding of space weather phenomena and the complex radiation environment in spaceflight, as well as developing and applying accurate dosimetric instruments, understanding related short- and long-term health risks, and strategies for effective countermeasures to minimize both exposure to space radiation and the remaining effects post exposure. The ESA/SciSpacE Space Radiation White Paper identifies those topics and underlines priorities for future research and development, to enable safe human and robotic exploration of space beyond Low Earth Orbit.

Multiple levels of stochasticity accounted for in different radiation biophysical models: from physics to biology.

PURPOSE: In the present paper we investigate how some stochastic effects are included in a class of radiobiological models with particular emphasis on how such randomnesses reflect into the predicted cell survival curve. MATERIALS AND METHODS: We consider four different models, namely the Generalized Stochastic Microdosimetric Model GSM2, in its original full form, the Dirac GSM2 the Poisson GSM2 and the Repair-Misrepair Model (RMR). While GSM2 and the RMR models are known in literature, the Dirac and the Poisson GSM2  have been newly introduced in this work. We further numerically investigate via Monte Carlo simulation of four different particle beams, how the proposed stochastic approximations reflect into the predicted survival curves. To achieve these results, we consider different ion species at energies of interest for therapeutic applications, also including a mixed field scenario. RESULTS: We show how the Dirac GSM2, the Poisson GSM2 and the RMR can be obtained from the GSM2 under suitable approximations on the stochasticity considered. We analytically derive the cell survival curve predicted by the four models, characterizing rigorously the high and low dose limits. We further study how the theoretical findings emerge also using Monte Carlo numerical simulations. CONCLUSIONS: We show how different models include different levels of stochasticity in the description of cellular response to radiation. This translates into different cell survival predictions depending on the radiation quality.

Investigation of In-Field and Out-of-Field Radiation Quality With Microdosimetry and Its Impact on Relative Biological Effectiveness in Proton Therapy.

PURPOSE: Using microdosimetry, this study investigated the relative biological effectiveness (RBE) and quality factor (Q¯) variations in field and out of field as a function of radiation quality for clinical protons. METHODS AND MATERIALS: A water phantom with a spread-out Bragg peak (SOBP) was irradiated to acquire microdosimetric spectra at several distal and lateral depths with a tissue equivalent proportional counter. The measurements were used as inputs to microdosimetric kinetic and Loncol models to determine the RBE spatial distribution and compare it with predictions from the dose-averaged linear energy transfer-based McNamara model. Q¯ values and biological and dose equivalent values were also calculated. RESULTS: The data demonstrated that radiation quality changed more rapidly with depth than lateral distance from the SOBP. In beam, yD ranged from approximately 4 keV/µm at the entrance to 8 keV/µm at the SOBP far end, reaching approximately 15 keV/µm at the penumbra. Out of field, the overall highest value of 23 ± 2 keV/µm was observed at the beam-edge penumbra. Radiation quality changes caused RBE deviations from the clinical value of 1.1, whose extent depends on the approach used for assessing radiation quality as well as on the radiobiological model. For RBE10, microdosimetry-based models appeared to better reproduce the radiobiological data than the dose-averaged linear energy transfer model. Out of field, both the RBE and Q¯ values appeared to have limitations in describing the radiation biological effectiveness. This research also presents a first comprehensive benchmark of TOPAS code against in-field and out-of-field microdosimetric spectra of therapeutic protons. CONCLUSIONS: Further investigation will be necessary to evaluate the quantitative effects of RBE variations on treatment planning and assess the clinical consequences in terms of both tumor control and normal-tissue toxicity. The achievement of this goal calls for accurate radiobiological data to validate the RBE models.

An exploratory study of machine learning techniques applied to therapeutic energies particle tracking in microdosimetry using the novel hybrid detector for microdosimetry (HDM).

In this work we present an advanced random forest-based machine learning (ML) model, trained and tested on Geant4 simulations. The developed ML model is designed to improve the performance of the hybrid detector for microdosimetry (HDM), a novel hybrid detector recently introduced to augment the microdosimetric information with the track length of particles traversing the microdosimeter. The present work leads to the following improvements of HDM: (i) the detection efficiency is increased up to 100%, filling not detected particles due to scattering within the tracker or non-active regions, (ii) the track reconstruction algorithm precision. Thanks to the ML models, we were able to reconstruct the microdosimetric spectra of both protons and carbon ions at therapeutic energies, predicting the real track length for every particle detected by the microdosimeter. The ML model results have been extensively studied, focusing on non-accurate predictions of the real track lengths. Such analysis has been used to identify HDM limitations and to understand possible future improvements of both the detector and the ML models.

Cell Survival Computation via the Generalized Stochastic Microdosimetric Model (GSM2); Part I: The Theoretical Framework.

The current article presents the first application of the Generalized Stochastic Microdosimetric Model (GSM2) for computing explicitly a cell survival curve. GSM2 is a general probabilistic model that predicts the kinetic evolution of DNA damages taking full advantage of a microdosimetric description of a radiation energy deposition. We show that, despite the high generality and flexibility of GSM2, an explicit form for the survival fraction curve predicted by the GSM2 is achievable. We illustrate how several correction terms typically added a posteriori in existing radiobiological models to improve the prediction accuracy, are naturally included into GSM2. Among the most relevant features of the survival curve derived from GSM2 and presented in this article, is the linear-quadratic behavior at low doses and a purely linear trend for high doses. The study also identifies and discusses the connections between GSM2 and existing cell survival models, such as the Microdosimetric Kinetic Model (MKM) and the Multi-hit model. Several approximations to predict cell survival in different irradiation regimes are also introduced to include intercellular non-Poissonian behaviors.

Proton pencil beam scanning reduces secondary cancer risk in breast cancer patients with internal mammary chain involvement compared to photon radiotherapy.

PURPOSE: Proton pencil beam scanning (PBS) represents an interesting option for the treatment of breast cancer (BC) patients with nodal involvement. Here we compare tangential 3D-CRT and VMAT to PBS proton therapy (PT) in terms of secondary cancer risk (SCR) for the lungs and for contralateral breast. METHODS: Five BC patients including supraclavicular (SVC) nodes in the target (Group 1) and five including SVC plus internal-mammary-nodes (IMNs, Group 2) were considered. The Group 1 patients were planned by PT versus tangential 3D-CRT in free-breathing (FB). The Group 2 patients were planned by PT versus VMAT considering both FB and deep-inspiration breath hold (DIBH) irradiation. The prescription dose to the target volume was 50 Gy (2 Gy/fraction). A constant RBE = 1.1 was assumed for PT. The SCR was evaluated with the excess absolute risk (EAR) formalism, considering also the age dependence. A cumulative EAR was finally computed. RESULTS: According to the linear, linear-exponential and linear-plateau dose response model, the cumulative EAR for Group 1 patients after PT was equal to 45 ± 10, 17 ± 3 and 15 ± 3, respectively. The corresponding relative increase for tangential 3D-CRT was equal to a factor 2.1 ± 0.5, 2.1 ± 0.4 and 2.3 ± 0.4. Group 2 patients showed a cumulative EAR after PT in FB equal to 65 ± 3, 21 ± 1 and 20 ± 1, according to the different models; the relative risk obtained with VMAT increased by a factor 3.5 ± 0.2, 5.2 ± 0.3 and 5.1 ± 0.3. Similar values emerge from DIBH plans. Contrary to photon radiotherapy, PT appears to be not sensitive to the age dependence due to the very low delivered dose. CONCLUSIONS: PBS PT is associated to significant SCR reduction in BC patients compared to photon radiotherapy. The benefits are maximized for young patients with both SVC and IMNs involvement. When combined with the improved sparing of the heart, this might contribute to the establishment of effective patient-selection criteria for proton BC treatments.

Protons and High-Linear Energy Transfer Radiation Induce Genetically Similar Lymphomas With High Penetrance in a Mouse Model of the Aging Human Hematopoietic System.

PURPOSE: Humans are exposed to charged particles in different scenarios. The use of protons and high-linear energy transfer (LET) in cancer treatment is steadily growing. In outer space, astronauts will be exposed to a mixed radiation field composed of both protons and heavy ions, in particularly the long-term space missions outside of earth's magnetosphere. Thus, understanding the radiobiology and transforming potential of these types of ionizing radiation are of paramount importance. METHODS AND MATERIALS: We examined the effect of 10 or 100 cGy of whole-body doses of protons or 28Si ions on the hematopoietic system of a genetic model of aging based on recent studies that showed selective loss of the MLH1 protein in human hematopoietic stems with age. RESULTS: We found that Mlh1 deficient animals are highly prone to develop lymphomas when exposed to either low doses of protons or 28Si ions. The lymphomas that develop are genetically indistinguishable, in spite of different types of damage elicited by low- and high-LET radiation. RNA sequencing analyses reveal similar gene expression patterns, similar numbers of altered genes, similar numbers of single nucleotide variants and insertions and deletions, and similar activation of known leukemogenic loci. CONCLUSIONS: Although the incidence of malignancy is related to radiation quality, and increased due to loss of Mlh1, the phenotype of the tumors is independent of LET.

A new facility for proton radiobiology at the Trento proton therapy centre: Design and implementation.

We present a new facility dedicated to radiobiology research, which has been implemented at the Trento Proton Therapy Centre (Italy). A dual-ring double scattering system was designed to produce irradiation fields of two sizes (i.e. 6 and 16 cm diameter) starting from a fix pencil beam at 148 MeV. The modulation in depth was obtained with a custom-made range modulator, optimized to generate a 2.5 cm spread-out Bragg peak (SOBP). The resulting irradiation field was characterized in terms of lateral and depth-dose profiles. The beam characteristics and the geometry of the setup were implemented in the Geant4 Monte Carlo (MC) code. After benchmark against experimental data, the MC was used to characterize the distribution of dose-average linear energy transfer (LET) associated to the irradiation field. The results indicate that dose uniformity above 92.9% is obtained at the entrance channel as well as in the middle SOBP in the target regions for both irradiation fields. Dose rate in the range from 0.38 to 0.78 Gy/min was measured, which can be adjusted by proper selection of cyclotron output current, and eventually increased by about a factor 7. MC simulations were able to reproduce experimental data with good agreement. The characteristics of the facility are in line with the requirements of most radiobiology experiments. Importantly, the facility is also open to external users, after successful evaluation of beam proposals by the Program Advisory Committee.

Overview of the NASA space radiation laboratory.

The NASA Space Radiation Laboratory (NSRL) is a multidisciplinary center for space radiation research funded by NASA and located at the Brookhaven National Laboratory (BNL), Upton NY. Operational since 2003, the scope of NSRL is to provide ion beams in support of the NASA Humans in Space program in radiobiology, physics and engineering to measure the risk and ameliorate the effect of radiation in space. Recently, it has also been recognized as the only facility in the U.S. currently capable of contributing to heavy ion radiotherapy research. This work contains a general overview of NSRL structure, capabilities and operation.

The Role of Nuclear Fragmentation in Particle Therapy and Space Radiation Protection.

The transport of the so-called HZE particles (those having high charge, Z, and energy, E) through matter is crucially important both in space radiation protection and in the clinical setting where heavy ions are used for cancer treatment. HZE particles are usually considered those having Z > 1, though sometimes Z > 2 is meant. Transport physics is governed by two types of interactions, electromagnetic (ionization energy loss) and nuclear. Models of transport, such as those used in treatment planning and space mission planning must account for both effects in detail. The theory of electromagnetic interactions is well developed, but nucleus-nucleus collisions are so complex that no fundamental physical theory currently describes them. Instead, interaction models are generally anchored to experimental data, which in some areas are far from complete. The lack of fundamental physics knowledge introduces uncertainties in the calculations of exposures and their associated risks. These uncertainties are greatly compounded by the much larger uncertainties in biological response to HZE particles. In this article, we discuss the role of nucleus-nucleus interactions in heavy charged particle therapy and in deep space, where astronauts will receive a chronic low dose from galactic cosmic rays (GCRs) and potentially higher short-term doses from sporadic, unpredictable solar energetic particles (SEPs). GCRs include HZE particles; SEPs typically do not and we, therefore, exclude them from consideration in this article. Nucleus-nucleus collisions can result in the breakup of heavy ions into lighter ions. In space, this is generally beneficial because dose and dose equivalent are, on the whole, reduced in the process. The GCRs can be considered a radiation field with a significant high-LET component; when they pass through matter, the high-LET component is attenuated, at the cost of a slight increase in the low-LET component. Not only are the standard measures of risk reduced by fragmentation, but it can be argued that fragmentation also reduces the uncertainties in risk calculations by shifting the LET distribution toward one that is more concentrated at low LET, where biological effects are better understood. We review previous work in this area, including measurements made by the Radiation Assessment Detector during its journey to Mars and while on the surface of Mars aboard the Curiosity rover. Transport of HZE is also critically important in heavy-ion therapy, as it is necessary to know the details of the radiation field at the treatment site. This field is substantially modified compared to the incident pure (or nearly pure) ion beam by the same mechanisms of energy loss and nuclear fragmentation that pertain to the transport of space radiation.

Reference field specification and preliminary beam selection strategy for accelerator-based GCR simulation.

The galactic cosmic ray (GCR) simulator at the NASA Space Radiation Laboratory (NSRL) is intended to deliver the broad spectrum of particles and energies encountered in deep space to biological targets in a controlled laboratory setting. In this work, certain aspects of simulating the GCR environment in the laboratory are discussed. Reference field specification and beam selection strategies at NSRL are the main focus, but the analysis presented herein may be modified for other facilities and possible biological considerations. First, comparisons are made between direct simulation of the external, free space GCR field and simulation of the induced tissue field behind shielding. It is found that upper energy constraints at NSRL limit the ability to simulate the external, free space field directly (i.e. shielding placed in the beam line in front of a biological target and exposed to a free space spectrum). Second, variation in the induced tissue field associated with shielding configuration and solar activity is addressed. It is found that the observed variation is likely within the uncertainty associated with representing any GCR reference field with discrete ion beams in the laboratory, given current facility constraints. A single reference field for deep space missions is subsequently identified. Third, a preliminary approach for selecting beams at NSRL to simulate the designated reference field is presented. This approach is not a final design for the GCR simulator, but rather a single step within a broader design strategy. It is shown that the beam selection methodology is tied directly to the reference environment, allows facility constraints to be incorporated, and may be adjusted to account for additional constraints imposed by biological or animal care considerations. The major biology questions are not addressed herein but are discussed in a companion paper published in the present issue of this journal. Drawbacks of the proposed methodology are discussed and weighed against alternative simulation strategies.

Galactic cosmic ray simulation at the NASA Space Radiation Laboratory.

Most accelerator-based space radiation experiments have been performed with single ion beams at fixed energies. However, the space radiation environment consists of a wide variety of ion species with a continuous range of energies. Due to recent developments in beam switching technology implemented at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL), it is now possible to rapidly switch ion species and energies, allowing for the possibility to more realistically simulate the actual radiation environment found in space. The present paper discusses a variety of issues related to implementation of galactic cosmic ray (GCR) simulation at NSRL, especially for experiments in radiobiology. Advantages and disadvantages of different approaches to developing a GCR simulator are presented. In addition, issues common to both GCR simulation and single beam experiments are compared to issues unique to GCR simulation studies. A set of conclusions is presented as well as a discussion of the technical implementation of GCR simulation.

Biophysical characterization of a relativistic proton beam for image-guided radiosurgery.

We measured the physical and radiobiological characteristics of 1 GeV protons for possible applications in stereotactic radiosurgery (image-guided plateau-proton radiosurgery). A proton beam was accelerated at 1 GeV at the Brookhaven National Laboratory (Upton, NY) and a target in polymethyl methacrylate (PMMA) was used. Clonogenic survival was measured after exposures to 1-10 Gy in three mammalian cell lines. Measurements and simulations demonstrate that the lateral scattering of the beam is very small. The lateral dose profile was measured with or without the 20-cm plastic target, showing no significant differences up to 2 cm from the axis A large number of secondary swift protons are produced in the target and this leads to an increase of approximately 40% in the measured dose on the beam axis at 20 cm depth. The relative biological effectiveness at 10% survival level ranged between 1.0 and 1.2 on the beam axis, and was slightly higher off-axis. The very low lateral scattering of relativistic protons and the possibility of using online proton radiography during the treatment make them attractive for image-guided plateau (non-Bragg peak) stereotactic radiosurgery.

Out-of-field dose studies with an anthropomorphic phantom: comparison of X-rays and particle therapy treatments.

BACKGROUND AND PURPOSE: Characterization of the out-of-field dose profile following irradiation of the target with a 3D treatment plan delivered with modern techniques. METHODS: An anthropomorphic RANDO phantom was irradiated with a treatment plan designed for a simulated 5 × 2 × 5 cm(3) tumor volume located in the center of the head. The experiment was repeated with all most common radiation treatment types (photons, protons and carbon ions) and delivery techniques (Intensity Modulated Radiation Therapy, passive modulation and spot scanning). The measurements were performed with active diamond detector and passive thermoluminescence (TLD) detectors to investigate the out-of-field dose both inside and outside the phantom. RESULTS: The highest out-of-field dose values both on the surface and inside the phantom were measured during the treatment with 25 MV photons. In the proximity of the Planned Target Volume (PTV), the lowest lateral dose profile was observed for passively modulated protons mainly because of the presence of the collimator in combination with the chosen volume shape. In the far out-of-field region (above 100mm from the PTV), passively modulated ions were characterized by a less pronounced dose fall-off in comparison with scanned beams. Overall, the treatment with scanned carbon ions delivered the lowest dose outside the target volume. CONCLUSIONS: For the selected PTV, the use of the collimator in proton therapy drastically reduced the dose deposited by ions or photons nearby the tumor. Scanning modulation represents the optimal technique for achieving the highest dose reduction far-out-of-field.