Effect of spatial distribution of boron and oxygen concentration on DNA damage induced from boron neutron capture therapy using Monte Carlo simulations

PURPOSE

This paper aims to investigate how the spatial distribution of boron in cells and oxygen concentration affect the DNA damage induced by charged particles in boron neutron capture therapy (BNCT) by Monte Carlo simulations, and further to evaluate the relative biological effectiveness (RBE) of DNA double-strand breaks (DSBs) induction.

MATERIALS AND METHODS

The kinetic energy spectra of α, 7Li particles in BNCT arriving at the nucleus surface were obtained from GEANT4 (Geant4 10.05.p01). The DNA damage caused by BNCT was then evaluated using MCDS (MCDS 3.10A).

RESULTS

When α or 7Li particles were distributed in the cytomembrane or cytoplasm, the difference in DNA damage of the same types was less than 0.5%. Taking the 137Cs photons as the reference radiation, when the oxygen concentration varied from 0% to 50%, the RBE of 0.54MeV protons and recoil protons varied from 5 to 2, whereas it decreased from 10 to 3 for α or 7Li particles.

CONCLUSION

The RBE of DSB induction all charged particles in BNCT decreased with the increase of oxygen concentration. This work indicated that the RBE of different radiation particles of BNCT might be affected by many factors, which should be paid attention to in theoretical research or clinical application.

Spot-Scanning Hadron Arc (SHArc) Therapy: A Study With Light and Heavy Ions

PURPOSE

To evaluate the clinical potential of spot-scanning hadron arc (SHArc) therapy with a heavy-ion gantry.

METHODS AND MATERIALS

A series of in silico studies was conducted via treatment plan optimization in FRoG and the RayStation TPS to compare SHArc therapy against reference plans using conventional techniques with single, parallel-opposed, and 3-field configurations for 3 clinical particle beams (protons [p], helium [4He], and carbon [12C] ions). Tests were performed on water-equivalent cylindrical phantoms for simple targets and clinical-like scenarios with an organ-at-risk in proximity of the target. Effective dose and dose-averaged linear energy transfer (LETD) distributions for SHArc were evaluated against conventional planning techniques applying the modified microdosimetric kinetic model for considering bio-effect with (α/β)x = 2 Gy. A model for hypoxia-induced tumor radio-resistance was developed for particle therapy with dependence on oxygen concentration and particle species/energy (Zeff/β)2 to investigate the impact on effective dose.

RESULTS

SHArc plans exhibited similar target coverage with unique treatment attributes and distributions compared with conventional planning, with carbon ions demonstrating the greatest potential for tumor control and normal tissue sparing among the arc techniques. All SHArc plans exhibited a low-dose bath outside the target volume with a reduced maximum dose in normal tissues compared with single, parallel-opposed, and 3-field configuration plans. Moreover, favorable LETD distributions were made possible using the SHArc approach, with maximum LETD in the r = 5 mm tumor core (~8 keVμm-1, ~30 keVμm-1, and ~150 keVμm-1 for p, 4He, and 12C ions, respectively) and reductions of high-LET regions in normal tissues and organs-at-risk compared with static treatment beam delivery.

CONCLUSION

SHArc therapy offers potential treatment benefits such as increased normal tissue sparing. Without explicit consideration of oxygen concentration during treatment planning and optimization, SHArc-C may mitigate tumor hypoxia-induced loss of efficacy. Findings justify further development of robust SHArc treatment planning toward potential clinical translation.

A systematic review on the usage of averaged LET in radiation biology for particle therapy

Linear Energy Transfer (LET) is widely used to express the radiation quality of ion beams, when characterizing the biological effectiveness. However, averaged LET may be defined in multiple ways, and the chosen definition may impact the resulting reported value. We review averaged LET definitions found in the literature, and quantify which impact using these various definitions have for different reference setups. We recorded the averaged LET definitions used in 354 publications quantifying the relative biological effectiveness (RBE) of hadronic beams, and investigated how these various definitions impact the reported averaged LET using a Monte Carlo particle transport code. We find that the kind of averaged LET being applied is, generally, poorly defined. Some definitions of averaged LET may influence the reported averaged LET values up to an order of magnitude. For publications involving protons, most applied dose averaged LET when reporting RBE. The absence of what target medium is used and what secondary particles are included further contributes to an ill-defined averaged LET. We also found evidence of inconsistent usage of averaged LET definitions when deriving LET-based RBE models. To conclude, due to commonly ill-defined averaged LET and to the inherent problems of LET-based RBE models, averaged LET may only be used as a coarse indicator of radiation quality. We propose a more rigorous way of reporting LET values, and suggest that ideally the entire particle fluence spectra should be recorded and provided for future RBE studies, from which any type of averaged LET (or other quantities) may be inferred.

The Effects of Dimethylsulfoxide and Oxygen on DNA Damage Induction and Repair Outcomes for Cells Irradiated by 62 MeV Proton and 3.31 MeV Helium Ions

Reactive oxygen species (ROS) play an essential role in radiation-induced indirect actions. In terms of DNA damage, double strand breaks (DSBs) have the greatest effects on the repair of DNA damage, cell survival and transformation. This study evaluated the biological effects of the presence of ROS and oxygen on DSB induction and mutation frequency. The relative biological effectiveness (RBE) and oxygen enhancement ratio (OER) of 62 MeV therapeutic proton beams and 3.31 MeV helium ions were calculated using Monte Carlo damage simulation (MCDS) software. Monte Carlo excision repair (MCER) simulations were used to calculate the repair outcomes (mutation frequency). The RBE values of proton beams decreased to 0.75 in the presence of 0.4 M dimethylsulfoxide (DMSO) and then increases to 0.9 in the presence of 2 M DMSO while the RBE values of 3.31 MeV helium ions increased from 2.9 to 5.7 (0–2 M). The mutation frequency of proton beams also decreased from 0.008–0.065 to 0.004–0.034 per cell per Gy by the addition of 2 M DMSO, indicating that ROS affects both DSB induction and repair outcomes. These results show that the combined use of DMSO in normal tissues and an increased dose in tumor regions increases treatment efficiency.

IDDRRA: A novel platform, based on Geant4-DNA to quantify DNA damage by ionizing radiation

PURPOSE

This study proposes a novel computational platform that we refer to as IDDRRA (DNA Damage Response to Ionizing RAdiation), which uses Monte Carlo (MC) simulations to score radiation induced DNA damage. MC simulations provide results of high accuracy on the interaction of radiation with matter while scoring the energy deposition based on state-of-the-art physics and chemistry models and probabilistic methods.

METHODS

The IDDRRA software is based on the Geant4-DNA toolkit together with new tools that were developed for the purpose of this study, including a new algorithm that was developed in Python for the design of the DNA molecules. New classes were developed in C++ to integrate the GUI and produce the simulation's output in text format. An algorithm was also developed to analyze the simulation's output in terms of energy deposition, Single Strand Breaks (SSB), Double Strand Breaks (DSB) and Cluster Damage Sites (CDS). Finally, a new tool was developed to implement probabilistic SSB and DSB repair models using MC techniques.

RESULTS

This article provides the first benchmarks that the user of the IDDRRA tool can use to validate the functionality of the software as well as to provide a starting point to produce different types of DNA simulations. These benchmarks incorporate different kind of particles (e-, e+, protons, electron spectrum) and DNA molecules.

CONCLUSION

We have developed the IDDRRA tool and demonstrated its use to study various aspects of the modeling and simulation of a DNA irradiation experiment. The tool is expandable and can be expanded by other users with new benchmarks and applications based on the user's needs and experience. New functionality will be added over time, including the quantification of the indirect damage.

Modeling low-dose radiation-induced acute myeloid leukemia in male CBA/H mice

The effect of low-dose ionizing radiation exposure on leukemia incidence remains poorly understood. Possible dose-response curves for various forms of leukemia are largely based on cohorts of atomic bomb survivors. Animal studies can contribute to an improved understanding of radiation-induced acute myeloid leukemia (rAML) in humans. In male CBA/H mice, incidence of rAML can be described by a two-hit model involving a radiation-induced deletion with Sfpi1 gene copy loss and a point mutation in the remaining Sfpi1 allele. In the present study (historical) mouse data were used and these processes were translated into a mathematical model to study photon-induced low-dose AML incidence in male CBA/H mice following acute exposure. Numerical model solutions for low-dose rAML incidence and diagnosis times could respectively be approximated with a model linear-quadratic in radiation dose and a normal cumulative distribution function. Interestingly, the low-dose incidence was found to be proportional to the modeled number of cells carrying the Sfpi1 deletion present per mouse following exposure. After making only model-derived high-dose rAML estimates available to extrapolate from, the linear-quadratic model could be used to approximate low-dose rAML incidence calculated with our mouse model. The accuracy in estimating low-dose rAML incidence when extrapolating from a linear model using a low-dose effectiveness factor was found to depend on whether a data transformation was used in the curve fitting procedure.

Microdosimetric investigation of the radiation quality of low-medium energy electrons using Geant4-DNA

The increasing clinical use of low-energy photon and electron sources (below few tens of keV) has raised concerns on the adequacy of the existing approximation of an energy-independent radiobiological effectiveness. In this work, the variation of the quality factor (Q) and relative biological effectiveness (RBE) of electrons over the low-medium energy range (0.1 keV-1 MeV) is examined using several microdosimetry-based Monte Carlo methodologies with input data obtained from Geant4-DNA track-structure simulations. The sensitivity of the results to the different methodologies, Geant4-DNA physics models, and target sizes is examined. Calculations of Q and RBE are based on the ICRU Report 40 recommendations, the Kellerer-Hahn approximation, the site version of the theory of dual radiation action (TDRA), the microdosimetric kinetic model (MKM) of cell survival, and the calculated yield of DNA double strand breaks (DSB). The stochastic energy deposition spectra needed as input in the above approaches have been calculated for nanometer spherical volumes using the different electron physics models of Geant4-DNA. Results are normalized at 100 keV electrons which is here considered the reference radiation. It is shown that in the energy range ~50 keV-1 MeV, the calculated Q and RBE are approximately unity (to within 1-2%) irrespective of the methodology, Geant4-DNA physics model, and target size. At lower energies, Q and RBE become energy-dependent reaching a maximum value of ~1.5-2.5 between ~200 and 700 eV. The detailed variation of Q and RBE at low energies depends mostly upon the adopted methodology and target size, and less so upon the Geant4-DNA physics model. Overall, the DSB yield predicts the highest RBE values (with RBE_max≈2.5) whereas the MKM the lowest RBE values (with RBE_max≈1.5). The ICRU Report 40, Kellerer-Hahn, and TDRA methods are in excellent agreement (to within 1-2%) over the whole energy range predicting a Q_max≈2. In conclusion, the approximation Q=RBE=1 was found to be valid only above ~50 keV whereas at lower energies both Q and RBE become strongly energy-dependent. It is envisioned that the present work will contribute towards establishing robust methodologies to determine theoretically the energy-dependence of radiation quality of individual electrons which may then be used in subsequent calculations involving practical electron and photon radiation sources.

Development of a coupled simulation toolkit for computational radiation biology based on Geant4 and CompuCell3D

Understanding and designing clinical radiation therapy is one of the most important areas of state-of-the-art oncological treatment regimens. Decades of research have gone into developing sophisticated treatment devices and optimization protocols for schedules and dosages. In this paper, we presented a comprehensive computational platform that facilitates building of the sophisticated multi-cell-based model of how radiation affects the biology of living tissue. We designed and implemented a coupled simulation method, including a radiation transport model, and a cell biology model, to simulate the tumor response after irradiation. The radiation transport simulation was implemented through Geant4 which is an open-source Monte Carlo simulation platform that provides many flexibilities for users, as well as low energy DNA damage simulation physics, Geant4-DNA. The cell biology simulation was implemented using CompuCell3D (CC3D) which is a cell biology simulation platform. In order to couple Geant4 solver with CC3D, we developed a 'bridging' module, RADCELL, that extracts tumor cellular geometry of the CC3D simulation (including specification of the individual cells) and ported it to the Geant4 for radiation transport simulation. The cell dose and cell DNA damage distribution in multicellular system were obtained using Geant4. The tumor response was simulated using cell-based tissue models based on CC3D, and the cell dose and cell DNA damage information were fed back through RADCELL to CC3D for updating the cell properties. By merging two powerful and widely used modeling platforms, CC3D and Geant4, we delivered a novel tool that can give us the ability to simulate the dynamics of biological tissue in the presence of ionizing radiation, which provides a framework for quantifying the biological consequences of radiation therapy. In this introductory methods paper, we described our modeling platform in detail and showed how it can be applied to study the application of radiotherapy to a vascularized tumor.

A Mathematical Radiobiological Model (MRM) to Predict Complex DNA Damage and Cell Survival for Ionizing Particle Radiations of Varying Quality

Predicting radiobiological effects is important in different areas of basic or clinical applications using ionizing radiation (IR); for example, towards optimizing radiation protection or radiation therapy protocols. In this case, we utilized as a basis the ‘MultiScale Approach (MSA)’ model and developed an integrated mathematical radiobiological model (MRM) with several modifications and improvements. Based on this new adaptation of the MSA model, we have predicted cell-specific levels of initial complex DNA damage and cell survival for irradiation with ¹¹Β, ¹²C, ¹⁴Ν, ¹⁶Ο, ²⁰Νe, ⁴⁰Αr, ²⁸Si and ⁵⁶Fe ions by using only three input parameters (particle’s LET and two cell-specific parameters: the cross sectional area of each cell nucleus and its genome size). The model-predicted survival curves are in good agreement with the experimental ones. The particle Relative Biological Effectiveness (RBE) and Oxygen Enhancement Ratio (OER) are also calculated in a very satisfactory way. The proposed integrated MRM model (within current limitations) can be a useful tool for the assessment of radiation biological damage for ions used in hadron-beam radiation therapy or radiation protection purposes.

A Meta-Analysis of the Effects of High-LET Ionizing Radiations in Human Gene Expression

The use of high linear energy transfer (LET) ionizing radiation (IR) is progressively being incorporated in radiation therapy due to its precise dose localization and high relative biological effectiveness. At the same time, these benefits of particle radiation become a high risk for astronauts in the case of inevitable cosmic radiation exposure. Nonetheless, DNA Damage Response (DDR) activated via complex DNA damage in healthy tissue, occurring from such types of radiation, may be instrumental in the induction of various chronic and late effects. An approach to elucidating the possible underlying mechanisms is studying alterations in gene expression. To this end, we identified differentially expressed genes (DEGs) in high Z and high energy (HZE) particle-, γ-ray- and X-ray-exposed healthy human tissues, utilizing microarray data available in public repositories. Differential gene expression analysis (DGEA) was conducted using the R programming language. Consequently, four separate meta-analyses were conducted, after DEG lists were grouped depending on radiation type, radiation dose and time of collection post-irradiation. To highlight the biological background of each meta-analysis group, functional enrichment analysis and biological network construction were conducted. For HZE particle exposure at 8–24 h post-irradiation, the most interesting finding is the variety of DNA repair mechanisms that were downregulated, a fact that is probably correlated with complex DNA damage formation. Simultaneously, after X-ray exposure during the same hours after irradiation, DNA repair mechanisms continue to take place. Finally, in a further comparison of low- and high-LET radiation effects, the most prominent result is that autophagy mechanisms seem to persist and that adaptive immune induction seems to be present. Such bioinformatics approaches may aid in obtaining an overview of the cellular response to high-LET particles. Understanding these response mechanisms can consequently aid in the development of countermeasures for future space missions and ameliorate heavy ion treatments.

Variance-based sensitivity analysis for uncertainties in proton therapy: A framework to assess the effect of simultaneous uncertainties in range, positioning, and RBE model predictions on RBE-weighted dose distributions

PURPOSE

Treatment plans in proton therapy are more sensitive to uncertainties than in conventional photon therapy. In addition to setup uncertainties, proton therapy is affected by uncertainties in proton range and relative biological effectiveness (RBE). While to date a constant RBE of 1.1 is commonly assumed, the actual RBE is known to increase toward the distal end of the spread-out Bragg peak. Several models for variable RBE predictions exist. We present a framework to evaluate the combined impact and interactions of setup, range, and RBE uncertainties in a comprehensive, variance-based sensitivity analysis (SA).

MATERIAL AND METHODS

The variance-based SA requires a large number (10⁴ -10⁵ ) of RBE-weighted dose (RWD) calculations. Based on a particle therapy extension of the research treatment planning system CERR we implemented a fast, graphics processing unit (GPU) accelerated pencil beam modeling of patient and range shifts. For RBE predictions, two biological models were included: The mechanistic repair-misrepair-fixation (RMF) model and the phenomenological Wedenberg model. All input parameters (patient position, proton range, RBE model parameters) are sampled simultaneously within their assumed probability distributions. Statistical formalisms rank the input parameters according to their influence on the overall uncertainty of RBE-weighted dose-volume histogram (RW-DVH) quantiles and the RWD in every voxel, resulting in relative, normalized sensitivity indices (S = 0: noninfluential input, S = 1: only influential input). Results are visualized as RW-DVHs with error bars and sensitivity maps.

RESULTS AND CONCLUSIONS

The approach is demonstrated for two representative brain tumor cases and a prostate case. The full SA including ∼ 3 × 10 4 RWD calculations took 39, 11, and 55 min, respectively. Range uncertainty was an important contribution to overall uncertainty at the distal end of the target, while the relatively smaller uncertainty inside the target was governed by biological uncertainties. Consequently, the uncertainty of the RW-DVH quantile D₉₈ for the target was governed by range uncertainty while the uncertainty of the mean target dose was dominated by the biological parameters. The SA framework is a powerful and flexible tool to evaluate uncertainty in RWD distributions and DVH quantiles, taking into account physical and RBE uncertainties and their interactions. The additional information might help to prioritize research efforts to reduce physical and RBE uncertainties and could also have implications for future approaches to biologically robust planning and optimization.

Cellular Response to Proton Irradiation: A Simulation Study with TOPAS-nBio

The cellular response to ionizing radiation continues to be of significant research interest in cancer radiotherapy, and DNA is recognized as the critical target for most of the biologic effects of radiation. Incident particles can cause initial DNA damages through physical and chemical interactions within a short time scale. Initial DNA damages can undergo repair via different pathways available at different stages of the cell cycle. The misrepair of DNA damage results in genomic rearrangement and causes mutations and chromosome aberrations, which are drivers of cell death. This work presents an integrated study of simulating cell response after proton irradiation with energies of 0.5-500 MeV (LET of 60-0.2 keV/µm). A model of a whole nucleus with fractal DNA geometry was implemented in TOPAS-nBio for initial DNA damage simulations. The default physics and chemistry models in TOPAS-nBio were used to describe interactions of primary particles, secondary particles, and radiolysis products within the nucleus. The initial DNA double-strand break (DSB) yield was found to increase from 6.5 DSB/Gy/Gbp at low-linear energy transfer (LET) of 0.2 keV/µm to 21.2 DSB/Gy/Gbp at high LET of 60 keV/µm. A mechanistic repair model was applied to predict the characteristics of DNA damage repair and dose response of chromosome aberrations. It was found that more than 95% of the DSBs are repaired within the first 24 h and the misrepaired DSB fraction increases rapidly with LET and reaches 15.8% at 60 keV/µm with an estimated chromosome aberration detection threshold of 3 Mbp. The dicentric and acentric fragment yields and the dose response of micronuclei formation after proton irradiation were calculated and compared with experimental results.

Experimental validation of an analytical microdosimetric model based on Geant4-DNA simulations by using a silicon-based microdosimeter

PURPOSE

To study the agreement between proton microdosimetric distributions measured with a silicon-based cylindrical microdosimeter and a previously published analytical microdosimetric model based on Geant4-DNA in-water Monte Carlo simulations for low energy proton beams.

METHODS AND MATERIAL

Distributions for lineal energy (y) are measured for four proton monoenergetic beams with nominal energies from 2.0 MeV to 4.5 MeV, with a tissue equivalent proportional counter (TEPC) and a silicon-based microdosimeter. The actual energy for protons traversing the silicon-based microdosimeter is simulated with SRIM. Monoenergetic beams with these energies are simulated with Geant4-DNA code by simulating a water cylinder site of dimensions equal to those of the microdosimeter. The microdosimeter response is calibrated by using the distribution peaks obtained from the TEPC. Analytical calculations fory ¯ F andy ¯ D using our methodology based on spherical sites are also performed choosing the equivalent sphere to be checked against experimental results.

RESULTS

Distributions for y at silicon are converted into tissue equivalent and compared to the Geant4-DNA simulated, yielding maximum deviations of 1.03% fory ¯ F and 1.17% fory ¯ D . Our analytical method generates maximum deviations of 1.29% and 3.33%, respectively, with respect to experimental results.

CONCLUSION

Simulations in Geant4-DNA with ideal cylindrical sites in liquid water produce similar results to the measurements in an actual silicon-based cylindrical microdosimeter properly calibrated. The found agreement suggests the possibility to experimentally verify the calculated clinicaly ¯ D with our analytical method.

Mechanistic Modeling of the Relative Biological Effectiveness of Boron Neutron Capture Therapy

Accurate dosimetry and determination of the biological effectiveness of boron neutron capture therapy (BNCT) is challenging because of the mix of different types and energies of radiation at the cellular and subcellular levels. In this paper, we present a computational, multiscale system of models to better assess the relative biological effectiveness (RBE) and compound biological effectiveness (CBE) of several neutron sources as applied to BNCT using boronophenylalanine (BPA) and a potential monoclonal antibody (mAb) that targets HER-2-positive cells with Trastuzumab. The multiscale model is tested against published in vitro and in vivo measurements of cell survival with and without boron. The combined dosimetric and radiobiological model includes an analytical formulation that accounts for the type of neutron source, the tissue- or cancer-specific dose–response characteristics, and the microdistribution of boron. Tests of the model against results from published experiments with and without boron show good agreement between modeled and experimentally determined cell survival for neutrons alone and in combination with boron. The system of models developed in this work is potentially useful as an aid for the optimization and individualization of BNCT for HER-2-positive cancers, as well as other cancers, that can be targeted with mAb or a conventional BPA compound.

Clinical implications of variable relative biological effectiveness in proton therapy for prostate cancer

PURPOSE

To study the potential consequences of differences in the evaluation of variable versus uniform relative biological effectiveness calculations in proton radiotherapy for prostate cancer.

METHODS AND MATERIAL

Experimental data with proton beams suggest that relative biological effectiveness increases with linear energy transfer. This relation also depends on the α / β ratio, characteristic of a tissue and a considered endpoint. Three phenomenological models (Carabe et al., Wedenberg et al. and McNamara et al.) are compared to a mechanistic model based on microdosimetry (microdosimetric kinetic model) and to the current assumption of uniform relative biological effectiveness equal to 1.1 in a prostate case.

RESULTS AND CONCLUSIONS

Phenomenological models clearly predict higher relative biological effectiveness values compared to microdosimetric kinetic model, that seems to approach to the constant value of 1.1 adopted in the clinics, at least for low linear energy transfer values achieved in typical prostate proton plans. All models predict a higher increase of the relative biological effectiveness-weighted dose for the prostate tumor than for the rest of structures involved due to its lower α / β ratio, even when linear energy transfer is, in general, lower in the tumor than on the surroundings tissues. Prostate cancer is, therefore, a good candidate to take advantage of variable relative biological effectiveness, especially if linear energy transfer is enhanced within the tumor. However, the discrepancies among models hinder the clinical implementation of variable relative biological effectiveness.

Interphase Cytogenetic Analysis of G0 Lymphocytes Exposed to α-Particles, C-Ions, and Protons Reveals their Enhanced Effectiveness for Localized Chromosome Shattering-A Critical Risk for Chromothripsis

For precision cancer radiotherapy, high linear energy transfer (LET) particle irradiation offers a substantial advantage over photon-based irradiation. In contrast to the sparse deposition of low-density energy by χ- or γ-rays, particle irradiation causes focal DNA damage through high-density energy deposition along the particle tracks. This is characterized by the formation of multiple damage sites, comprising localized clustered patterns of DNA single- and double-strand breaks as well as base damage. These clustered DNA lesions are key determinants of the enhanced relative biological effectiveness (RBE) of energetic nuclei. However, the search for a fingerprint of particle exposure remains open, while the mechanisms underlying the induction of chromothripsis-like chromosomal rearrangements by high-LET radiation (resembling chromothripsis in tumors) await to be elucidated. In this work, we investigate the transformation of clustered DNA lesions into chromosome fragmentation, as indicated by the induction and post-irradiation repair of chromosomal damage under the dynamics of premature chromosome condensation in G0 human lymphocytes. Specifically, this study provides, for the first time, experimental evidence that particle irradiation induces localized shattering of targeted chromosome domains. Yields of chromosome fragments and shattered domains are compared with those generated by γ-rays; and the RBE values obtained are up to 28.6 for α-particles (92 keV/μm), 10.5 for C-ions (295 keV/μm), and 4.9 for protons (28.5 keV/μm). Furthermore, we test the hypothesis that particle radiation-induced persistent clustered DNA lesions and chromatin decompaction at damage sites evolve into localized chromosome shattering by subsequent chromatin condensation in a single catastrophic event—posing a critical risk for random rejoining, chromothripsis, and carcinogenesis. Consistent with this hypothesis, our results highlight the potential use of shattered chromosome domains as a fingerprint of high-LET exposure, while conforming to the new model we propose for the mechanistic origin of chromothripsis-like rearrangements.

Melatonin as a Radio-Sensitizer in Cancer

Radiotherapy is one of the treatments of choice in many types of cancer. Adjuvant treatments to radiotherapy try, on one hand, to enhance the response of tumor cells to radiation and, on the other hand, to reduce the side effects to normal cells. Radiosensitizers are agents that increase the effect of radiation in tumor cells by trying not to increase side effects in normal tissues. Melatonin is a hormone produced mainly by the pineal gland which has an important role in the regulation of cancer growth, especially in hormone-dependent mammary tumors. Different studies have showed that melatonin administered with radiotherapy is able to enhance its therapeutic effects and can protect normal cells against side effects of this treatment. Several mechanisms are involved in the radiosensitization induced by melatonin: increase of reactive oxygen species production, modulation of proteins involved in estrogen biosynthesis, impairment of tumor cells to DNA repair, modulation of angiogenesis, abolition of inflammation, induction of apoptosis, stimulation of preadipocytes differentiation and modulation of metabolism. At this moment, there are very few clinical trials that study the therapeutic usefulness to associate melatonin and radiotherapy in humans. All findings point to melatonin as an effective adjuvant molecule to radiotherapy in cancer treatment.

Combined radiation strategies for novel and enhanced cancer treatment

Numerous studies focus on cancer therapy worldwide, and although many advances have been recorded, the complexity of the disease dictates thinking out of the box to confront it. This study reviews some of the currently available ionizing (IR) and non-ionizing radiation (NIR)-based treatment methods and explores their possible combinations that lead to synergistic, multimodal approaches with promising therapeutic outcomes. Traditional techniques, like radiotherapy (RT) show decent results, although they cannot spare 100% the healthy tissues neighboring with the cancer ones. Targeted therapies, such as proton and photodynamic therapy (PT and PDT, respectively) present adequate outcomes, even though each one has its own drawbacks. To overcome these limitations, the combination of therapeutic modalities has been proposed and has already been showing promising results. At the same time, the recent advances in nanotechnology in the form of nanoparticles enhance cancer therapy, making multimodal treatments worthy of exploring and studying. The combination of RT and PDT has reached the level of clinical trials and is showing promising results. Moreover, in vitro and in vivo studies of nanoparticles with PDT have also provided beneficial results concerning enhanced radiation treatments. In any case, novel and multimodal approaches have to be adopted to achieve personalized, enhanced and effective cancer treatment.

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.

Modeling RBE-weighted dose variations in irregularly moving abdominal targets treated with carbon ion beams

PURPOSE

To model four-dimensional (4D) relative biological effectiveness (RBE)-weighted dose variations in abdominal lesions treated with scanned carbon ion beam in case of irregular breathing motion.

METHODS

The proposed method, referred to as bioWED method, combines the simulation of tumor motion in a patient- and beam-specific water equivalent depth (WED)-space with RBE modeling, aiming at the estimation of RBE-weighted dose changes due to respiratory motion. The method was validated on a phantom, simulating gated and free breathing dose delivery, and on a patient case, for which free breathing irradiation was assumed and both amplitude and baseline breathing irregularities were simulated through a respiratory motion model. We quantified (a) the effect of motion on the equivalent uniform dose (EUD) and the RBE-weighted dose-volume histograms (DVH), by comparing the planned dose distribution with "ground truth" 4D RBE-weighted doses computed using 4D computed tomography data, and (ii) the estimation error, by comparing the doses estimated with the bioWED method to "ground truth" 4D RBE-weighted doses.

RESULTS

In the phantom validation, the estimation error on the EUD was limited with respect to the motion effect and the median estimation error on relevant RBE-weighted DVH metrics remained within 5%. In the patient study, the estimation error as computed on the EUD was smaller than the corresponding motion effect, exhibiting the largest values in the baseline irregularity simulation. However, the median estimation error over all simulations was below 3.2% considering relevant DVH metrics.

CONCLUSIONS

In the evaluated cases, the bioWED method showed proper accuracy when compared to deformable image registration-based 4D dose calculation. Therefore, it can be seen as a tool to test treatment plan robustness against irregular breathing motion, although its accuracy decreases as a function of increasing soft tissue deformation and should be evaluated on a larger patient dataset.

Internal microdosimetry of alpha-emitting radionuclides

At the tissue level, energy deposition in cells is determined by the microdistribution of alpha-emitting radionuclides in relation to sensitive target cells. Furthermore, the highly localized energy deposition of alpha particle tracks and the limited range of alpha particles in tissue produce a highly inhomogeneous energy deposition in traversed cell nuclei. Thus, energy deposition in cell nuclei in a given tissue is characterized by the probability of alpha particle hits and, in the case of a hit, by the energy deposited there. In classical microdosimetry, the randomness of energy deposition in cellular sites is described by a stochastic quantity, the specific energy, which approximates the macroscopic dose for a sufficiently large number of energy deposition events. Typical examples of the alpha-emitting radionuclides in internal microdosimetry are radon progeny and plutonium in the lungs, plutonium and americium in bones, and radium in targeted radionuclide therapy. Several microdosimetric approaches have been proposed to relate specific energy distributions to radiobiological effects, such as hit-related concepts, LET and track length-based models, effect-specific interpretations of specific energy distributions, such as the dual radiation action theory or the hit-size effectiveness function, and finally track structure models. Since microdosimetry characterizes only the initial step of energy deposition, microdosimetric concepts are most successful in exposure situations where biological effects are dominated by energy deposition, but not by subsequently operating biological mechanisms. Indeed, the simulation of the combined action of physical and biological factors may eventually require the application of track structure models at the nanometer scale.

Molecular Mechanisms of Radiation-Induced Cancer Cell Death: A Primer

Radiation therapy (RT) is responsible for at least 40% of cancer cures, however treatment resistance remains a clinical problem. There have been recent advances in understanding the molecular mechanisms of radiation-induced cell death. The type of cell death after radiation depends on a number of factors including cell type, radiation dose and quality, oxygen tension, TP53 status, DNA repair capacity, cell cycle phase at time of radiation exposure, and the microenvironment. Mitotic catastrophe (a pathway preceding cell death that happens in mitosis or as a consequence of aberrant mitotic progression) is the primary context of radiation-induced cell death in solid cancers, although in a small subset of cancers such as haematopoietic malignancies, radiation results in immediate interphase apoptosis, occurring within hours after exposure. There is intense therapeutic interest in using stereotactic ablative body radiotherapy (SABR), a precise, high-dose form of RT given in a small number of fractions, to prime the immune system for cancer cell killing, but the optimal radiation dose and fractionation remain unclear. Additionally, promising novel radiosensitisers targeting the cell cycle and DNA repair pathways are being trialled. In the context of the increasing use of SABR and such novel agents in the clinic, we provide an updated primer on the major types of radiation-induced cell death, focussing on their molecular mechanisms, factors affecting their initiation, and their implications on immunogenicity.

Microdosimetric calculations of the direct DNA damage induced by low energy electrons using the Geant4-DNA Monte Carlo code

To calculate the yield of direct DNA damage induced by low energy electrons using Monte Carlo generated microdosimetric spectra at the nanometer scale and examine the influence of various simulation inputs. The potential of classical microdosimetry to offer a viable and simpler alternative to more elaborate mechanistic approaches for practical applications is discussed. Track-structure simulations with the Geant4-DNA low-energy extension of the Geant4 Monte Carlo toolkit were used for calculating lineal energy spectra in spherical volumes with dimensions relevant to double-strand-break (DSB) induction. The microdosimetric spectra were then used to calculate the yield of simple and clustered DSB based on literature values of the threshold energy of DNA damage. The influence of the different implementations of the dielectric function of liquid water available in Geant4-DNA (Option 2 and Option 4 constructors), as well as the effect of particle tracking cutoff energy and target size are examined. Frequency- and dose-mean lineal energies in liquid-water spheres of 2, 2.3, 2.6, and 3.4 nm diameter, as well as, number of simple and clustered DSB/Gy/cell are presented for electrons over the 100 eV to 100 keV energy range. Results are presented for both the 'default' (Option 2) and 'Ioannina' (Option 4) physics models of Geant4-DNA applying several commonly used tracking cutoff energies (10, 20, 50, 100 eV). Overall, the choice of the physics model and target diameter has a moderate effect (up to ~10%-30%) on the DSB yield whereas the effect of the tracking cutoff energy may be significant (>100%). Importantly, the yield of both simple and clustered DSB was found to vary significantly (by a factor of 2 or more) with electron energy over the examined range. The yields of electron-induced simple and clustered DSB exhibit a strong energy dependence over the 100 eV-100 keV range with implications to radiation quality issues. It is shown that a classical microdosimetry approach for the calculation of DNA damage based on lineal energy spectra in nanometer-size targets predicts comparable results to computationally intensive mechanistic approaches which use detailed atomistic DNA geometries, thus, offering a relatively simple and robust alternative for some practical applications.

Establishing mechanisms affecting the individual response to ionizing radiation

Purpose: Humans are increasingly exposed to ionizing radiation (IR). Both low (<100 mGy) and high doses can cause stochastic effects, including cancer; whereas doses above 100 mGy are needed to promote tissue or cell damage. 10-15% of radiotherapy (RT) patients suffer adverse reactions, described as displaying radiosensitivity (RS). Sensitivity to IR's stochastic effects is termed radiosusceptibility (RSu). To optimize radiation protection we need to understand the range of individual variability and underlying mechanisms. We review the potential mechanisms contributing to RS/RSu focusing on RS following RT, the most tractable RS group.Conclusions: The IR-induced DNA damage response (DDR) has been well characterized. Patients with mutations in the DDR have been identified and display marked RS but they represent only a small percentage of the RT patients with adverse reactions. We review the impacting mechanisms and additional factors influencing RS/RSu. We discuss whether RS/RSu might be genetically determined. As a recommendation, we propose that a prospective study be established to assess RS following RT. The study should detail tumor site and encompass a well-defined grading system. Predictive assays should be independently validated. Detailed analysis of the inflammatory, stress and immune responses, mitochondrial function and life style factors should be included. Existing cohorts should also be optimally exploited.

Optimization of treatment planning for hypoxic tumours and re-modulation of radiation intensity in heavy-ion radiotherapy

Aim

The purpose of this study is to optimize treatment planning in carbon ion radiotherapy, taking into account the effect of tumour hypoxia.

Background

In conventional hadron therapy, the goal is to create a homogenous dose in the tumour area and, thus, achieve a uniform cell survival level. Since the induction of a specific damage to cells is directly influenced by the level of hypoxia in the tissue, the varying oxygen pressure in the different regions of hypoxic tumours would disrupt the uniformity of the cell survival level.

Materials and methods

Using the Geant4 Monte Carlo Code, the physical dose profile and dose-averaged linear energy transfer were calculated in the tumour. Then, the oxygen enhancement ratio in different areas of the tumour were compared with different pressures.

Results

Modulations of radiation intensities as well as energies of ion beams were calculated, both considering and disregarding the effect of hypoxia, and the required dose profiles were compared with each other. Cell survival levels were also compared between the two methods. An equation was obtained for re-modulating the beams in the presence of hypoxia, and radiation weighting factors were extracted for the beam intensities.

Conclusion

The results show that taking the effect of hypoxia into account would cause the reduction of average doses delivered to the tumour tissues up to 1.54 times. In this regard, the required dose is reduced by 1.63 times in the healthy tissues before the tumour. This will result in an effective protection of healthy tissues around the tumour.

Comparative photon and proton dosimetry for patients with mediastinal lymphoma in the era of Monte Carlo treatment planning and variable relative biological effectiveness

Background

Existing pencil beam analytical (PBA) algorithms for proton therapy treatment planning are not ideal for sites with heterogeneous tissue density and do not account for the spatial variations in proton relative biological effectiveness (vRBE). Using a commercially available Monte Carlo (MC) treatment planning system, we compared various dosimetric endpoints between proton PBA, proton MC, and photon treatment plans among patients with mediastinal lymphoma.

Methods

Eight mediastinal lymphoma patients with both free breathing (FB) and deep inspiration breath hold (DIBH) CT simulation scans were analyzed. The original PBA plans were re-calculated with MC. New proton plans that used MC for both optimization and dose calculation with equivalent CTV/ITV coverage were also created. A vRBE model, which uses a published model for DNA double strand break (DSB) induction, was applied on MC plans to study the potential impact of vRBE on cardiac doses. Comparative photon plans were generated on the DIBH scan.

Results

Re-calculation of FB PBA plans with MC demonstrated significant under coverage of the ITV V99 and V95. Target coverage was recovered by re-optimizing the PT plan with MC with minimal change to OAR doses. Compared to photons with DIBH, MC-optimized FB and DIBH proton plans had significantly lower dose to the mean lung, lung V5, breast tissue, and spinal cord for similar target coverage. Even with application of vRBE in the proton plans, the putative increase in RBE at the end of range did not decrease the dosimetric advantages of proton therapy in cardiac substructures.

Conclusions

MC should be used for PT treatment planning of mediastinal lymphoma to ensure adequate coverage of target volumes. Our preliminary data suggests that MC-optimized PT plans have better sparing of the lung and breast tissue compared to photons. Also, the potential for end of range RBE effects are unlikely to be large enough to offset the dosimetric advantages of proton therapy in cardiac substructures for mediastinal targets, although these dosimetric findings require validation with late toxicity data.

Assessment of Radio-Induced Damage in Endothelial Cells Irradiated with 40 kVp, 220 kVp, and 4 MV X-rays by Means of Micro and Nanodosimetric Calculations

The objective of this work was to study the differences in terms of early biological effects that might exist between different X-rays energies by using a mechanistic approach. To this end, radiobiological experiments exposing cell monolayers to three X-ray energies were performed in order to assess the yields of early DNA damage, in particular of double-strand breaks (DSBs). The simulation of these irradiations was set in order to understand the differences in the obtained experimental results. Hence, simulated results in terms of microdosimetric spectra and early DSB induction were analyzed and compared to the experimental data. Human umbilical vein endothelial cells (HUVECs) were irradiated with 40, 220 kVp, and 4 MV X-rays. The Geant4 Monte Carlo simulation toolkit and its extension Geant4-DNA were used for the simulations. Microdosimetric calculations aiming to determine possible differences in the variability of the energy absorbed by the irradiated cell population for those photon spectra were performed on 10,000 endothelial cell nuclei representing a cell monolayer. Nanodosimetric simulations were also carried out using a computation chain that allowed the simulation of physical, physico-chemical, and chemical stages on a single realistic endothelial cell nucleus model including both heterochromatin and euchromatin. DNA damage was scored in terms of yields of prompt DSBs per Gray (Gy) and per giga (10⁹) base pair (Gbp) and DSB complexity was derived in order to be compared to experimental data expressed as numbers of histone variant H2AX (γ-H2AX) foci per cell. The calculated microdosimetric spread in the irradiated cell population was similar when comparing between 40 and 220 kVp X-rays and higher when comparing with 4 MV X-rays. Simulated yields of induced DSB/Gy/Gbp were found to be equivalent to those for 40 and 220 kVp but larger than those for 4 MV, resulting in a relative biological effectiveness (RBE) of 1.3. Additionally, DSB complexity was similar between the considered photon spectra. Simulated results were in good agreement with experimental data obtained by IRSN (Institut de radioprotection et de sûreté nucléaire) radiobiologists. Despite differences in photon energy, few differences were observed when comparing between 40 and 220 kVp X-rays in microdosimetric and nanodosimetric calculations. Nevertheless, variations were observed when comparing between 40/220 kVp and 4 MV X-rays. Thanks to the simulation results, these variations were able to be explained by the differences in the production of secondary electrons with energies below 10 keV.

Ionizing Radiation and Complex DNA Damage: From Prediction to Detection Challenges and Biological Significance

Biological responses to ionizing radiation (IR) have been studied for many years, generally showing the dependence of these responses on the quality of radiation, i.e., the radiation particle type and energy, types of DNA damage, dose and dose rate, type of cells, etc. There is accumulating evidence on the pivotal role of complex (clustered) DNA damage towards the determination of the final biological or even clinical outcome after exposure to IR. In this review, we provide literature evidence about the significant role of damage clustering and advancements that have been made through the years in its detection and prediction using Monte Carlo (MC) simulations. We conclude that in the future, emphasis should be given to a better understanding of the mechanistic links between the induction of complex DNA damage, its processing, and systemic effects at the organism level, like genomic instability and immune responses.

Effects of indirect actions and oxygen on relative biological effectiveness: estimate of DSB inductions and conversions induced by therapeutic proton beams

Purpose: This study evaluated the DNA double strand breaks (DSBs) induced by indirect actions and its misrepairs to estimate the relative biological effectiveness (RBE) of proton beams.Materials and methods: From experimental data, DSB induction was evaluated in cells irradiated by 62 MeV proton beams in the presence of dimethylsulphoxide (DMSO) and under hypoxic conditions. The DNA damage yields for calculating the RBE were estimated using Monte Carlo Damage Simulation (MCDS) software. The repair outcomes (correct repairs, mutations and DSB conversions) were estimated using Monte Carlo Excision Repair (MCER) simulations.Results: The values for RBE of 62 MeV protons (LET = 1.051 keV/μm) for DSB induction and enzymatic DSB under aerobic condition (21% O₂) was 1.02 and 0.94, respectively, as comparing to ⁶⁰Co γ-rays (LET = 2.4 keV/μm). DMSO mitigated the inference of indirect action and reduced DSB induction to a greater extent when damaged by protons rather than γ-rays, resulting in a decreased RBE of 0.86. DMSO also efficiently prevented enzymatic DSB yields triggered by proton irradiation and reduced the RBE to 0.83. However, hypoxia (2% O₂) produced a similar level of DSB induction with respect to the protons and γ-rays, with a comparable RBE of 1.02.Conclusions: The RBE values of proton beams estimated from DSB induction and enzymatic DSB decreased by 16% and 12%, respectively, in the presence of DMSO. Our findings indicate that the overall effects of DSB induction and enzymatic DSB could intensify the tumor killing, while alleviate normal tissue damage when indirect actions are effectively interrupted.

Necessities in the Processing of DNA Double Strand Breaks and Their Effects on Genomic Instability and Cancer

Double strand breaks (DSBs) are induced in the DNA following exposure of cells to ionizing radiation (IR) and are highly consequential for genome integrity, requiring highly specialized modes of processing. Erroneous processing of DSBs is a cause of cell death or its transformation to a cancer cell. Four mechanistically distinct pathways have evolved in cells of higher eukaryotes to process DSBs, providing thus multiple options for the damaged cells. The homologous recombination repair (HRR) dependent subway of gene conversion (GC) removes IR-induced DSBs from the genome in an error-free manner. Classical non-homologous end joining (c-NHEJ) removes DSBs with very high speed but is unable to restore the sequence at the generated junction and can catalyze the formation of translocations. Alternative end-joining (alt-EJ) operates on similar principles as c-NHEJ but is slower and more error-prone regarding both sequence preservation and translocation formation. Finally, single strand annealing (SSA) is associated with large deletions and may also form translocations. Thus, the four pathways available for the processing of DSBs are not alternative options producing equivalent outcomes. We discuss the rationale for the evolution of pathways with such divergent properties and fidelities and outline the logic and necessities that govern their engagement. We reason that cells are not free to choose one specific pathway for the processing of a DSB but rather that they engage a pathway by applying the logic of highest fidelity selection, adapted to necessities imposed by the character of the DSB being processed. We introduce DSB clusters as a particularly consequential form of chromatin breakage and review findings suggesting that this form of damage underpins the increased efficacy of high linear energy transfer (LET) radiation modalities. The concepts developed have implications for the protection of humans from radon-induced cancer, as well as the treatment of cancer with radiations of high LET.

Charged particle radiobiology beamline using tandem accelerator-based MeV protons and carbon ions: a pilot study on the track-end radiation quality, variable biological effectiveness and Bayesian beam dosimetry

For in vitro cell irradiation using tandem accelerator-based MeV protons and carbon ions, by TOPAS simulation, a pilot study of performance evaluation is presented on a collimation beamline for 3 MeV protons and 10 MeV carbon ions from a 2  ×  3 MV tandem accelerator. Based on the elements and source parameters, a collimated beam of 2.8 MeV protons or 2.5 MeV carbon ions, with 5.175 mm or 5.166 mm full width tenth maximum (FWTM), respectively, can be delivered to the target cell dish. TOPAS simulations and/or deterministic algorithms present a Bragg curve of linear energy transfer (LET) (10-70 keV μm^-1) along a 138 μm range of the proton beam, and a declining LET of the carbon beam (900-100 keV μm^-1) within 4 μm range. Based on the biophysical models for relative biological effectiveness (RBE) of protons, TOPAS RBE scorers presents a set of depth-variation curves of the proton RBE (for V79 and DU145 cells), linearly related to the Bragg curve of the proton LET. Based on the microdosimetric-kinetic (MK) theory, in the 4 μm range for a monolayer cell thickness, the mean RBEα (V79 cells) of the carbon ion beam is estimated as 3.612 (late S phase) and 1.737 (G ₁/S phase) for the mean LET of 492 keV μm^-1. For practical irradiations, a tunable proton RBE can be acquired by changing the thickness of the cell dish. For the low-energy high-fluence (rate) beams, indirect beam measurements are proposed to detect the proton-beam induced scattering/recoil protons from a beam-intercepting Mylar film, and the carbon-beam induced backscattered electrons from a gold-deposited Havar-foil beam window. Statistical dosimetry for the indirect measurement is established, using a Bayesian model based on the preset number of detection counts, by which the mean value of the whole-dish dose can be prescribed and the uncertainty introduced in the survival data can be corrected.

Report of the AAPM TG-256 on the relative biological effectiveness of proton beams in radiation therapy

The biological effectiveness of proton beams relative to photon beams in radiation therapy has been taken to be 1.1 throughout the history of proton therapy. While potentially appropriate as an average value, actual relative biological effectiveness (RBE) values may differ. This Task Group report outlines the basic concepts of RBE as well as the biophysical interpretation and mathematical concepts. The current knowledge on RBE variations is reviewed and discussed in the context of the current clinical use of RBE and the clinical relevance of RBE variations (with respect to physical as well as biological parameters). The following task group aims were designed to guide the current clinical practice: Assess whether the current clinical practice of using a constant RBE for protons should be revised or maintained. Identifying sites and treatment strategies where variable RBE might be utilized for a clinical benefit. Assess the potential clinical consequences of delivering biologically weighted proton doses based on variable RBE and/or LET models implemented in treatment planning systems. Recommend experiments needed to improve our current understanding of the relationships among in vitro, in vivo, and clinical RBE, and the research required to develop models. Develop recommendations to minimize the effects of uncertainties associated with proton RBE for well-defined tumor types and critical structures.

Effect of 177Lu-iPSMA on viability and DNA damage of human glioma cells subjected to hypoxia-mimetic conditions

The therapeutic potential of ¹⁷⁷Lu-iPSMA on hypoxic cancer cells has not been yet demonstrated. The aim of this work was to evaluate the radiation dose effect of ¹⁷⁷Lu-iPSMA on viability and DNA damage in U87MG human glioma cells subjected to hypoxia-mimetic conditions. U87MG cells treated with ¹⁷⁷Lu-iPSMA were incubated with CoCl₂ in order to induce hypoxia-mimetic conditions. The cytotoxic and genotoxic effect was evaluated with an in vitro viability test and a neutral comet assay. ¹⁷⁷Lu-iPSMA decreased the cell viability and induced DNA double strand breaks in U87MG human glioma cells under hypoxia-mimetic conditions. ¹⁷⁷Lu-iPSMA produced the maximum effect at 48 h, suggesting that this radiopharmaceutical could be used as a strategy for the treatment of human glioma hypoxic cells.

Clinically relevant nanodosimetric simulation of DNA damage complexity from photons and protons

Relative Biological Effectiveness (RBE), the ratio of doses between radiation modalities to produce the same biological endpoint, is a controversial and important topic in proton therapy. A number of phenomenological models incorporate variable RBE as a function of Linear Energy Transfer (LET), though a lack of mechanistic description limits their applicability. In this work we take a different approach, using a track structure model employing fundamental physics and chemistry to make predictions of proton and photon induced DNA damage, the first step in the mechanism of radiation-induced cell death. We apply this model to a proton therapy clinical case showing, for the first time, predictions of DNA damage on a patient treatment plan. Our model predictions are for an idealised cell and are applied to an ependymoma case, at this stage without any cell specific parameters. By comparing to similar predictions for photons, we present a voxel-wise RBE of DNA damage complexity. This RBE of damage complexity shows similar trends to the expected RBE for cell kill, implying that damage complexity is an important factor in DNA repair and therefore biological effect.

Relative Biological Effectiveness (RBE) is a controversial and important topic in proton therapy. This work uses Monte Carlo simulations of DNA damage for protons and photons to probe this phenomenon, providing a plausible mechanistic understanding.

A mechanistic relative biological effectiveness model-based biological dose optimization for charged particle radiobiology studies

In charged particle therapy, the objective is to exploit both the physical and radiobiological advantages of charged particles to improve the therapeutic index. Use of the beam scanning technique provides the flexibility to implement biological dose optimized intensity-modulated ion therapy (IMIT). An easy-to-implement algorithm was developed in the current study to rapidly generate a uniform biological dose distribution, namely the product of physical dose and the relative biological effectiveness (RBE), within the target volume using scanned ion beams for charged particle radiobiological studies. Protons, helium ions and carbon ions were selected to demonstrate the feasibility and flexibility of our method. The general-purpose Monte Carlo simulation toolkit Geant4 was used for particle tracking and generation of physical and radiobiological data needed for later dose optimizations. The dose optimization algorithm was developed using the Python (version 3) programming language. A constant RBE-weighted dose (RWD) spread-out Bragg peak (SOBP) in a water phantom was selected as the desired target dose distribution to demonstrate the applicability of the optimization algorithm. The mechanistic repair-misrepair-fixation (RMF) model was incorporated into the Monte Carlo particle tracking to generate radiobiological parameters and was used to predict the RBE of cell survival in the iterative process of the biological dose optimization for the three selected ions. The post-optimization generated beam delivery strategy can be used in radiation biology experiments to obtain radiobiological data to further validate and improve the accuracy of the RBE model. This biological dose optimization algorithm developed for radiobiology studies could potentially be extended to implement biologically optimized IMIT plans for patients.

Fixed- versus Variable-RBE Computations for Intensity Modulated Proton Therapy

Purpose

To evaluate how using models of proton therapy that incorporate variable relative biological effectiveness (RBE) versus the current practice of using a fixed RBE of 1.1 affects dosimetric indices on treatment plans for large cohorts of patients treated with intensity modulated proton therapy (IMPT).

Methods and Materials

Treatment plans for 4 groups of patients who received IMPT for brain, head-and-neck, thoracic, or prostate cancer were selected. Dose distributions were recalculated in 4 ways: 1 with a fast-dose Monte Carlo calculator with fixed RBE and 3 with RBE calculated to 3 different models—McNamara, Wedenberg, and repair-misrepair-fixation. Differences among dosimetric indices (D02, D50, D98, and mean dose) for target volumes and organs at risk (OARs) on each plan were compared between the fixed-RBE and variable-RBE calculations.

Results

In analyses of all target volumes, for which the main concern is underprediction or RBE less than 1.1, none of the models predicted an RBE less than 1.05 for any of the cohorts. For OARs, the 2 models based on linear energy transfer, McNamara and Wedenberg, systematically predicted RBE >1.1 for most structures. For the mean dose of 25% of the plans for 2 OARs, they predict RBE equal to or larger than 1.4, 1.3, 1.3, and 1.2 for brain, head-and-neck, thorax, and prostate, respectively. Systematically lower increases in RBE are predicted by repair-misrepair-fixation, with a few cases (eg, femur) in which the RBE is less than 1.1 for all plans.

Conclusions

The variable-RBE models predict increased doses to various OARs, suggesting that strategies to reduce high-dose linear energy transfer in critical structures should be developed to minimize possible toxicity associated with IMPT.

A comparison of mechanism-inspired models for particle relative biological effectiveness (RBE)

BACKGROUND AND SIGNIFICANCE

The application of heavy ion beams in cancer therapy must account for the increasing relative biological effectiveness (RBE) with increasing penetration depth when determining dose prescriptions and organ at risk (OAR) constraints in treatment planning. Because RBE depends in a complex manner on factors such as the ion type, energy, cell and tissue radiosensitivity, physical dose, biological endpoint, and position within and outside treatment fields, biophysical models reflecting these dependencies are required for the personalization and optimization of treatment plans.

AIM

To review and compare three mechanism-inspired models which predict the complexities of particle RBE for various ion types, energies, linear energy transfer (LET) values and tissue radiation sensitivities.

METHODS

The review of models and mechanisms focuses on the Local Effect Model (LEM), the Microdosimetric-Kinetic (MK) model, and the Repair-Misrepair-Fixation (RMF) model in combination with the Monte Carlo Damage Simulation (MCDS). These models relate the induction of potentially lethal double strand breaks (DSBs) to the subsequent interactions and biological processing of DSB into more lethal forms of damage. A key element to explain the increased biological effectiveness of high LET ions compared to MV x rays is the characterization of the number and local complexity (clustering) of the initial DSB produced within a cell. For high LET ions, the spatial density of DSB induction along an ion's trajectory is much greater than along the path of a low LET electron, such as the secondary electrons produced by the megavoltage (MV) x rays used in conventional radiation therapy. The main aspects of the three models are introduced and the conceptual similarities and differences are critiqued and highlighted. Model predictions are compared in terms of the RBE for DSB induction and for reproductive cell survival.

RESULTS AND CONCLUSIONS

Comparisons of the RBE for DSB induction and for cell survival are presented for proton (¹ H), helium (⁴ He), and carbon (¹² C) ions for the therapeutically most relevant range of ion beam energies. The reviewed models embody mechanisms of action acting over the spatial scales underlying the biological processing of potentially lethal DSB into more lethal forms of damage. Differences among the number and types of input parameters, relevant biological targets, and the computational approaches among the LEM, MK and RMF models are summarized and critiqued. Potential experiments to test some of the seemingly contradictory aspects of the models are discussed.

A New Standard DNA Damage (SDD) Data Format

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

Modelling of Cellular Survival Following Radiation-Induced DNA Double-Strand Breaks

A mechanistic model of cellular survival following radiation-induced DNA double-strand breaks (DSBs) was proposed in this study. DSBs were assumed as the initial lesions in the DNA of the cell nucleus induced by ionizing radiation. The non-homologous end-joining (NHEJ) pathway was considered as the domain pathway of DSB repair in mammalian cells. The model was proposed to predict the relationship between radiation-induced DSBs in nucleus and probability of cell survival, which was quantitatively described by two input parameters and six fitting parameters. One input parameter was the average number of primary particles which caused DSB, the other input parameter was the average number of DSBs yielded by each primary particle that caused DSB. The fitting parameters were used to describe the biological characteristics of the irradiated cells. By determining the fitting parameters of the model with experimental data, the model is able to estimate surviving fractions for the same type of cells exposed to particles with different physical parameters. The model further revealed the mechanism of cell death induced by the DSB effect. Relative biological effectiveness (RBE) of charged particles at different survival could be calculated with the model, which would provide reference for clinical treatment.

The potential impact of ultrathin filter design on dosimetry and relative biological effectiveness in modern image-guided small animal irradiators

OBJECTIVE:

Modern image-guided small animal irradiators like the Xstrahl Small Animal Radiation Research Platform (SARRP) are designed with ultrathin 0.15 mm Cu filters, which compared with more heavily filtrated traditional cabinet-style biological irradiators, produce X-ray spectra weighted toward lower energies, impacting the dosimetric properties and the relative biological effectiveness (RBE). This study quantifies the effect of ultrathin filter design on relative depth dose profiles, absolute dose output, and RBE using Monte Carlo techniques.

METHODS:

The percent depth-dose and absolute dose output are calculated using kVDoseCalc and EGSnrc, respectively, while a tally based on the induction of double-strand breaks as a function of electron spectra invoked in PENELOPE is used to estimate the RBE.

RESULTS:

The RBE increases by >2.4% in the ultrathin filter design compared to a traditional irradiator. Furthermore, minute variations in filter thickness have notable effects on the dosimetric properties of the X-ray beam, increasing the percent depth dose (at 2 cm in water) by + 0.4%/0.01 mm Cu and decreasing absolute dose (at 2 cm depth in water) by -1.8%/0.01 mm Cu for the SARRP.

CONCLUSIONS:

These results show that modern image-guided irradiators are quite sensitive to small manufacturing variations in filter thickness, and show a small change in RBE compared to traditional X-ray irradiators.

ADVANCES IN KNOWLEDGE:

We quantify the consequences of ultrathin filter design in modern image-guided biological irradiators on relative and absolute dose, and RBE. Our results show these to be small, but not insignificant, suggesting laboratories transitioning between irradiators should carefully design their radiobiological experiments.

Does Neutron Radiation Therapy Potentiate an Immune Response to Merkel Cell Carcinoma?

BACKGROUND

Merkel cell carcinoma (MCC) is a rare and aggressive cutaneous malignancy. In the advanced setting, MCC is often treated with immune checkpoint inhibitors such as anti-PD-1/PD-L1 antibodies. X-ray radiation therapy (XRT) is commonly used for palliation. There is an unmet need for new treatment options in patients progressing on immunotherapy and XRT. We present 2 patients with progressive MCC who were successfully treated with high linear energy transfer neutron radiation therapy (NRT).

CLINICAL OBSERVATIONS

Patient A, an 85-year-old white male with chronic lymphocytic leukemia had progressive MCC with multiple tumors on the face despite prior XRT and ongoing treatment with pembrolizumab. The 5 most symptomatic lesions were treated with a short course of NRT (2 × 3 Gy) while continuing pembrolizumab. All irradiated facial lesions demonstrated a complete response 2 weeks after NRT. Remarkably, an additional 4 lesions located outside the NRT fields also completely resolved. Patient B, a 78-year-old white male with no immunosuppressive condition had recurrent MCC in the scalp and bilateral cervical nodes. The painful, ulcerative tumors on his scalp were progressing despite multiple courses of XRT and multiple immunotherapy regimens, including pembrolizumab. He was treated with NRT (16-18 Gy) to the scalp and had a complete response with successful palliation. While his disease subsequently progressed outside the NRT fields, the response to NRT bridged him to receive further investigational immunotherapies, and he remains disease free 3 years later.

CONCLUSION

Short courses of high linear energy transfer particle therapy deserve consideration as a promising modality for local tumor control in XRT refractory tumors. The out-of-field response suggests that NRT has potential for synergizing with immunotherapy. While more data are required to identify optimal NRT parameters, the NRT dose that potentiates an antitumor immune response appears to be well below organ-at-risk tolerance.

Induction of DNA Damage by Light Ions Relative to 60Co γ-rays

The specific types and numbers of clusters of DNA lesions, including both DNA double-strand breaks (DSBs) and non-DSB clusters, are widely considered 1 of the most important initiating events underlying the relative biological effectiveness (RBE) of the light ions of interest in the treatment of cancer related to megavoltage x-rays and 60Co γ-rays. This review summarizes the categorization of DNA damage, reviews the underlying mechanisms of action by ionizing radiation, and quantifies the general trends in DSB and non-DSB cluster formation by light ions under normoxic and anoxic conditions, as predicted by Monte Carlo simulations that reflect the accumulated evidence from decades of research on radiation damage to DNA. The significance of the absolute and relative numbers of clusters and the local complexity of DSB and non-DSB clusters are discussed in relation to the formation of chromosome aberrations and the loss of cell reproductive capacity. Clinical implications of the dependence of DSB induction on ionization density is reviewed with an eye towards increasing the therapeutic ratio of proton and carbon ion therapy through the explicit optimization of RBE-weighted dose.

Dosimetric characteristics of the University of Washington Clinical Neutron Therapy System

The University of Washington (UW) Clinical Neutron Therapy System (CNTS), which generates high linear energy transfer fast neutrons through interactions of 50.5 MeV protons incident on a Be target, has depth-dose characteristics similar to 6 MV x-rays. In contrast to the fixed beam angles and primitive blocking used in early clinical trials of neutron therapy, the CNTS has a gantry with a full 360° of rotation, internal wedges, and a multi-leaf collimator (MLC). Since October of 1984, over 3178 patients have received conformal neutron therapy treatments using the UW CNTS. In this work, the physical and dosimetric characteristics of the CNTS are documented through comparisons of measurements and Monte Carlo simulations. A high resolution computed tomography scan of the model 17 ionization chamber (IC-17) has also been used to improve the accuracy of simulations of the absolute calibration geometry. The response of the IC-17 approximates well the kinetic energy released per unit mass (KERMA) in water for neutrons and photons for energies from a few tens of keV up to about 20 MeV. Above 20 MeV, the simulated model 17 ion chamber response is 20%-30% higher than the neutron KERMA in water. For CNTS neutrons, simulated on- and off-axis output factors in water match measured values within ~2%  ±  2% for rectangular and irregularly shaped field with equivalent square areas ranging in a side dimension from 2.8 cm to 30.7 cm. Wedge factors vary by less than 1.9% of the measured dose in water for clinically relevant field sizes. Simulated tissue maximum ratios in water match measured values within 3.3% at depths up to 20 cm. Although the absorbed dose for water and adipose tissue are within 2% at a depth of 1.7 cm, the absorbed dose in muscle and bone can be as much as 12 to 40% lower than the absorbed dose in water. The reported studies are significant from a historical perspective and as additional validation of a new tool for patient quality assurance and as an aid in ongoing efforts to clinically implement advanced treatment techniques, such as intensity modulated neutron therapy, at the UW.