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Background: Proton linear energy transfer (LET) is associated with the relative biological effectiveness of radiation on tissues. Monte Carlo (MC) simulations have been known to be the preferred method to calculate LET. Detectors have also been built to measure LET, but they need to be calibrated with MC simulations. Purpose: To propose and test a MC‐free method for determining LET from the measured integral depth dose (LFI) of the protons of interest. Method and materials: LFI consists of three steps: (1) IDD measurements, (2) extraction of energy spectrum (ES) from the IDD, and (3) LET determination from the extracted ES and the stopping power of each energy. To validate the accuracy of the extraction of ES, we use Gaussian ES to synthesize IDD, extract ES from the synthesized IDD, and then compare the original (ground truth) and extracted ES. LETs calculated from the original and extracted ES are also compared. To obtain the LET of protons of interest, we measure IDDs by a large‐area plane‐parallel ionization chamber in water. Finally, TOPAS MC is employed to simulate IDDs, ES, and LETs. From the simulated IDD, the extracted ES and LET are compared with the simulations from TOPAS MC. Results: From the synthesized IDDs, the LETs agreed excellently when the peak energies ≥10 and 1.25 MeV with depth resolutions 0.1 and 0.01 mm, respectively. For energy <1.25 MeV, even higher depth resolution than 0.01 mm is required. From the MC simulated IDDs, our track‐averaged LET excellently agreed with MC simulation, but not the LETd. Our LETd was smaller than MC simulated LETd in the shallow region but larger in the distal Bragg peak region. Conclusion: LET can be accurately determined from the IDD. This method can be used in the clinic to commission or validate LETs from other measurement methods or a treatment planning system. [ABSTRACT FROM AUTHOR]

Purpose: Neutron capture therapy (NCT) by 10B and 157Gd agents is a unique irradiation‐based method which can be used to treat brain tumors. Current study aims to quantitatively evaluate the relative biological effectiveness (RBE) and dose distributions during the combined BNCT and GdNCT modalities through a hybrid Monte Carlo (MC) simulation approach. Methods: Snyder head phantom as well as a cubic hypothetical tumor was at first modeled by Geant4 MC Code. Then, the energy spectra and dose distribution relevant to the released secondary particles during the combined Gd/BNCT were scored for different concentrations of 157Gd and 10B inside tumor volume. Finally, the scored energy spectra were imported to the MCDS code to estimate both RBESSB and RBEDSB values for different 157Gd concentrations. Results: The results showed that combined Gd/BNCT increases the fluence‐averaged RBESSB values by about 1.7 times when 157Gd concentration increments from 0 to 2000 µg/g for both considered cell oxygen levels (pO2 = 10% and 100%). Besides, a reduction of about 26% was found for fluence‐averaged RBEDSB values with an increment of 157Gd concentration in tumor volume. Conclusion: From the results, it can be concluded that combined Gd/BNCT technique can improve tumor coverage with higher dose levels but in the expense of RBEDSB reduction which can affect the clinical efficacy of the NCT technique. [ABSTRACT FROM AUTHOR]

Purpose: Carbon ion radiotherapy (CIRT) relies on relative biological effectiveness (RBE)‐weighted dose calculations. Japanese clinics predominantly use the microdosimetric kinetic model (MKM), while European centers utilize the local effect model (LEM). Despite both models estimating RBE‐distributions in tissue, their physical and mathematical assumptions differ, leading to significant disparities in RBE‐weighted doses. Several European clinics adopted Japanese treatment schedules, necessitating adjustments in dose prescriptions and organ at risk (OAR) constraints. In the context of these two clinically used standards for RBE‐weighted dose estimation, the objective of this study was to highlight specific scenarios for which the translations between models diverge, as shortcomings between them can influence clinical decisions. Methods: Our aim was to discuss planning strategies minimizing those discrepancies, ultimately striving for more accurate and robust treatments. Evaluations were conducted in a virtual water phantom and patient CT‐geometry, optimizing LEM RBE‐weighted dose first and recomputing MKM thereafter. Dose‐averaged linear energy transfer (LETd) distributions were also assessed. Results: Results demonstrate how various parameters influence LEM/MKM translation. Similar LEM‐dose distributions lead to markedly different MKM‐dose distributions and variations in LETd. Generally, a homogeneous LEM RBE‐weighted dose aligns with lower MKM values in most of the target volume. Nevertheless, paradoxical MKM hotspots may emerge (at the end of the range), potentially influencing clinical outcomes. Therefore, translation between models requires great caution. Conclusions: Understanding the relationship between these two clinical standards enables combining European and Japanese based experiences. The implementation of optimal planning strategies ensures the safety and acceptability of the clinical plan for both models and therefore enhances plan robustness from the RBE‐weighted dose and LETd distribution point of view. This study emphasizes the importance of optimal planning strategies and the need for comprehensive CIRT plan quality assessment tools. In situations where simultaneous LEM and MKM computation capabilities are lacking, it can provide guidance in plan design, ultimately contributing to enhanced CIRT outcomes. [ABSTRACT FROM AUTHOR]

Objective. To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP).Approach. Our model provides for selection of preferred ID parameters (Ip) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopicIpand macroscopic RTP. Selection ofIpis demonstrated using published cell survival measurements for protons through argon, comparing results for nineteenIp:Nk,k= 2, 3, …, 10, the number of ionizations in clusters ofkor more per particle, andFk,k= 1, 2, …, 10, the number of clusters ofkor more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation.Main results. The preferredIpwereN4andF5for aerobic cells,N5andF7for hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferredNk. Conversely, there was no significant difference forF5for aerobic cells andF7for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for theseIphad the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert thatIpexist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation.Significance. Our model provides a practical means to select preferredIpfrom radiobiological data, and to convertIpto the macroscopic cluster dose for particle RTP.

Abstract The study aimed to determine the specific relative biological effectiveness (RBE) of various cells in the hippocampus following proton irradiation. Sixty Sprague–Dawley rats were randomly allocated to 5 groups receiving 20 or 30 Gy of proton or photon irradiation. Pathomorphological neuronal damage in the hippocampus was assessed using Hematoxylin–eosin (HE) staining. The expression level of NeuN, Nestin, Caspase-3, Olig2, CD68 and CD45 were determined by immunohistochemistry (IHC). The RBE range established by comparing the effects of proton and photon irradiation at equivalent biological outcomes. Proton20Gy induced more severe damage to neurons than photon20Gy, but showed no difference compared to photon30Gy. The RBE of neuron was determined to be 1.65. Similarly, both proton20Gy and proton30Gy resulted in more inhibition of oligodendrocytes and activation of microglia in the hippocampal regions than photon20Gy and photon30Gy. However, the expression of Olig2 was higher and CD68 was lower in the proton20Gy group than in the photon30Gy group. The RBE of oligodendrocyte and microglia was estimated to be between 1.1 to 1.65. For neural stem cells (NSCs) and immune cells, there were no significant difference in the expression of Nestin and CD45 between proton and photon irradiation (both 20 and 30 Gy). Therefore, the RBE for NSCs and immune cell was determined to be 1.1. These findings highlight the varying RBE values of different cells in the hippocampus in vivo. Moreover, the actual RBE of the hippocampus may be higher than 1.1, suggesting that using as RBE value of 1.1 in clinical practice may underestimate the toxicities induced by proton radiation.

Simple Summary: Proton therapy is a crucial tool for head and neck and skull-base cancers, offering benefits over photon therapy by lowering the risk of adverse effects. However, its full potential could be further explored by better characterizing the uncertainties related to its relative biological effectiveness. Addressing these uncertainties is crucial for maximizing the potential of proton therapy. We explore the significance of proton therapy's biological impact in these cancers, review relative biological effectiveness uncertainties and modeling, and examine clinical outcomes and evidence linking specific biological factors to patient adverse effects. Additionally, we review the current clinical practices and provide insights into innovative developments and their future clinical implementation. Proton therapy has emerged as a crucial tool in the treatment of head and neck and skull-base cancers, offering advantages over photon therapy in terms of decreasing integral dose and reducing acute and late toxicities, such as dysgeusia, feeding tube dependence, xerostomia, secondary malignancies, and neurocognitive dysfunction. Despite its benefits in dose distribution and biological effectiveness, the application of proton therapy is challenged by uncertainties in its relative biological effectiveness (RBE). Overcoming the challenges related to RBE is key to fully realizing proton therapy's potential, which extends beyond its physical dosimetric properties when compared with photon-based therapies. In this paper, we discuss the clinical significance of RBE within treatment volumes and adjacent serial organs at risk in the management of head and neck and skull-base tumors. We review proton RBE uncertainties and its modeling and explore clinical outcomes. Additionally, we highlight technological advancements and innovations in plan optimization and treatment delivery, including linear energy transfer/RBE optimizations and the development of spot-scanning proton arc therapy. These advancements show promise in harnessing the full capabilities of proton therapy from an academic standpoint, further technological innovations and clinical outcome studies, however, are needed for their integration into routine clinical practice. [ABSTRACT FROM AUTHOR]

Background: The Relative Biological Effectiveness (RBE) of kilovoltage photon beams has been previously investigated in vitro and in silico using analytical methods. The estimated values range from 1.03 to 1.82 depending on the methodology and beam energies examined. Purpose: The focus of this work was to independently estimate RBE values for a range of clinically used kilovoltage beams (70–200 kVp) while investigating the suitability of using TOPAS‐nBio for this task. Methods: Previously validated spectra of clinical beams were used to generate secondary electron spectra at several depths in a water tank phantom via TOPAS Monte Carlo (MC) simulations. Cell geometry was irradiated with the secondary electrons in TOPAS‐nBio MC simulations. The deposited dose and the calculated number of DNA strand breaks were used to estimate RBE values. Results: Monoenergetic secondary electron simulations revealed the highest direct and indirect double strand break yield at approximately 20 keV. The average RBE value for the kilovoltage beams was calculated to be 1.14. Conclusions: TOPAS‐nBio was successfully used to estimate the RBE values for a range of clinical radiotherapy beams. The calculated value was in agreement with previous estimates, providing confidence in its clinical use in the future. [ABSTRACT FROM AUTHOR]

Neutron capture therapy (NCT) with various concentrations of gadolinium (157Gd) is one of the treatment modalities for glioblastoma (GBM) tumors. Current study aims to evaluate how variations of 157Gd concentration and cell oxygen levels can affect the relative biological effectiveness (RBE) of gadolinium neutron capture therapy (GdNCT) technique through a hybrid Monte Carlo (MC) simulation approach. At first, Snyder phantom including a spherical tumor was simulated by Geant4 MC code and relevant energy electron spectra to different 157Gd concentrations including 100, 250, 500, and 1000 ppm were calculated following the neutron irradiation of simulated phantom. Scored energy electron spectra were then imported to Monte Carlo damage simulation (MCDS) code to estimate RBE values (both RBESSB and RBEDSB) at different gadolinium concentrations and oxygen levels from 10 to 100%. The results indicate that variations of 157Gd can affect the energy spectrum of released secondary electrons including Auger electrons. Variation of gadolinium concentration from 100 to 1000 ppm in tumor region can change RBESSB and RBEDSB values by about 0.1% and 0.5%, respectively. Besides, maximum variations of 4.3% and 2% were calculated for RBEDSB and RBESSB when cell oxygen level changed from 10 to 100%. From the results, variations of considered gadolinium and oxygen concentrations during GdNCT can influence RBE values. Nevertheless, due to the not remarkable changes in the intensity of Auger electrons, a slight difference in RBE values would be expected at various 157Gd concentrations, although considerable RBE changes were calculated relevant to the oxygen alternations inside tumor tissue. [ABSTRACT FROM AUTHOR]

PurposeEmpirical relative biological effectiveness (RBE) models have been used to estimate the biological dose in proton therapy but do not adequately capture the factors influencing RBE values for treatment planning. We reformulate the McNamara RBE model such that it can be added as a linear biological dose fidelity term within our previously developed sensitivity-regularized and heterogeneity-weighted beam orientation optimization (SHBOO) framework.MethodsBased on our SHBOO framework, we formulated the biological optimization problem to minimize total McNamara RBE dose to OARs. We solve this problem using two optimization algorithms: FISTA (McNam-FISTA) and Chambolle-Pock (McNam-CP). We compare their performances with a physical dose optimizer assuming RBE = 1.1 in all structures (PHYS-FISTA) and an LET-weighted dose model (LET-FISTA). Three head and neck patients were planned with the four techniques and compared on dosimetry and robustness.ResultsCompared to Phys-FISTA, McNam-CP was able to match CTV [HI, Dmax, D95%, D98%] by [0.00, 0.05%, 1.4%, 0.8%]. McNam-FISTA and McNam-CP were able to significantly improve overall OAR [Dmean, Dmax] by an average of [36.1%,26.4%] and [29.6%, 20.3%], respectively. Regarding CTV robustness, worst [Dmax, V95%, D95%, D98%] improvement of [-6.6%, 6.2%, 6.0%, 4.8%] was reported for McNam-FISTA and [2.7%, 2.7%, 5.3%, -4.3%] for McNam-CP under combinations of range and setup uncertainties. For OARs, worst [Dmax, Dmean] were improved by McNam-FISTA and McNam-CP by an average of [25.0%, 19.2%] and [29.5%, 36.5%], respectively. McNam-FISTA considerably improved dosimetry and CTV robustness compared to LET-FISTA, which achieved better worst-case OAR doses.ConclusionThe four optimization techniques deliver comparable biological doses for the head and neck cases. Besides modest CTV coverage and robustness improvement, OAR biological dose and robustness were substantially improved with both McNam-FISTA and McNam-CP, showing potential benefit for directly incorporating McNamara RBE in proton treatment planning.

The number of patients treated with charged-particle radiotherapy as well as the number of treatment centers is increasing worldwide, particularly regarding protons. However, high-linear energy transfer (LET) particles, mainly carbon ions, are of special interest for application in radiotherapy, as their special physical features result in high precision and hence lower toxicity, and at the same time in increased efficiency in cell inactivation in the target region, i.e., the tumor. The radiobiology of high-LET particles differs with respect to DNA damage repair, cytogenetic damage, and cell death type, and their increased LET can tackle cells' resistance to hypoxia. Recent developments and perspectives, e.g., the return of high-LET particle therapy to the US with a center planned at Mayo clinics, the application of carbon ion radiotherapy using cost-reducing cyclotrons and the application of helium is foreseen to increase the interest in this type of radiotherapy. However, further preclinical research is needed to better understand the differential radiobiological mechanisms as opposed to photon radiotherapy, which will help to guide future clinical studies for optimal exploitation of high-LET particle therapy, in particular related to new concepts and innovative approaches. Herein, we summarize the basics and recent progress in high-LET particle radiobiology with a focus on carbon ions and discuss the implications of current knowledge for charged-particle radiotherapy. We emphasize the potential of high-LET particles with respect to immunogenicity and especially their combination with immunotherapy. [ABSTRACT FROM AUTHOR]

Radiation therapy plays an important role in the multidisciplinary management of breast cancer. Recent years have seen improvements in breast cancer survival and a greater appreciation of potential long-term morbidity associated with the dose and volume of irradiated organs. Proton therapy reduces the dose to nontarget structures while optimizing target coverage. However, there remain additional financial costs associated with proton therapy, despite reductions over time, and studies have yet to demonstrate that protons improve upon the treatment outcomes achieved with photon radiation therapy. There remains considerable heterogeneity in proton patient selection and techniques, and the rapid technological advances in the field have the potential to affect evidence evaluation, given the long latency period for breast cancer radiation therapy recurrence and late effects. In this consensus statement, we assess the data available to the radiation oncology community of proton therapy for breast cancer, provide expert consensus recommendations on indications and technique, and highlight ongoing trials cost-effectiveness analyses and key areas for future research.

Proton therapy has emerged as a crucial tool in the treatment of head and neck and skull-base cancers, offering advantages over photon therapy in terms of decreasing integral dose and reducing acute and late toxicities, such as dysgeusia, feeding tube dependence, xerostomia, secondary malignancies, and neurocognitive dysfunction. Despite its benefits in dose distribution and biological effectiveness, the application of proton therapy is challenged by uncertainties in its relative biological effectiveness (RBE). Overcoming the challenges related to RBE is key to fully realizing proton therapy’s potential, which extends beyond its physical dosimetric properties when compared with photon-based therapies. In this paper, we discuss the clinical significance of RBE within treatment volumes and adjacent serial organs at risk in the management of head and neck and skull-base tumors. We review proton RBE uncertainties and its modeling and explore clinical outcomes. Additionally, we highlight technological advancements and innovations in plan optimization and treatment delivery, including linear energy transfer/RBE optimizations and the development of spot-scanning proton arc therapy. These advancements show promise in harnessing the full capabilities of proton therapy from an academic standpoint, further technological innovations and clinical outcome studies, however, are needed for their integration into routine clinical practice.

Introduction: Tumor hypoxia is associated with poor treatment outcome. Hypoxic regions are more radioresistant than well‐oxygenated regions, as quantified by the oxygen enhancement ratio (OER). In optimization of proton therapy, including OER in addition to the relative biological effectiveness (RBE) could therefore be used to adapt to patient‐specific radioresistance governed by intrinsic radiosensitivity and hypoxia. Methods: A combined RBE and OER weighted dose (ROWD) calculation method was implemented in a FLUKA Monte Carlo (MC) based treatment planning tool. The method is based on the linear quadratic model, with α and β parameters as a function of the OER, and therefore a function of the linear energy transfer (LET) and partial oxygen pressure (pO2). Proton therapy plans for two head and neck cancer (HNC) patients were optimized with pO2 estimated from [18F]‐EF5 positron emission tomography (PET) images. For the ROWD calculations, an RBE of 1.1 (RBE1.1,OER) and two variable RBE models, Rørvik (ROR) and McNamara (MCN), were used, alongside a reference plan without incorporation of OER (RBE1.1). Results: For the HNC patients, treatment plans in line with the prescription dose and with acceptable target ROWD could be generated with the established tool. The physical dose was the main factor modulated in the ROWD. The impact of incorporating OER during optimization of HNC patients was demonstrated by the substantial difference found between ROWD and physical dose in the hypoxic tumor region. The largest physical dose differences between the ROWD optimized plans and the reference plan was 12.2 Gy. Conclusion: The FLUKA MC based tool was able to optimize proton treatment plans taking the tumor pO2 distribution from hypoxia PET images into account. Independent of RBE‐model, both elevated LET and physical dose were found in the hypoxic regions, which shows the potential to increase the tumor control compared to a conventional optimization approach. [ABSTRACT FROM AUTHOR]

PurposeWe sought to investigate the tumor control probability (TCP) of vestibular schwannomas after single-fraction stereotactic radiosurgery (SRS) or hypofractionated SRS over 2 to 5 fractions (fSRS).Methods and materialsStudies (PubMed indexed from 1993-2017) were eligible for data extraction if they contained dosimetric details of SRS/fSRS correlated with local tumor control. The rate of tumor control at 5 years (or at 3 years if 5-year data were not available) were collated. Poisson modeling estimated the TCP per equivalent dose in 2 Gy per fraction (EQD2) and in 1, 3, and 5 fractions.ResultsData were extracted from 35 publications containing a total of 5162 patients. TCP modeling was limited by the absence of analyzable data of 12 Gy. Using linear-quadratic-based dose conversion, the 3- to 5-year TCP was estimated at 95% at an EQD2 of 25 Gy, corresponding to 1-, 3-, and 5-fraction doses of 13.8 Gy, 19.2 Gy, and 21.5 Gy, respectively. Single-fraction doses of 10 Gy, 11 Gy, 12 Gy, and 13 Gy predicted a TCP of 85.0%, 88.4%, 91.2%, and 93.5%, respectively. For fSRS, 18 Gy in 3 fractions (EQD2 of 23.0 Gy) and 25 Gy in 5 fractions (EQD2 of 30.2 Gy) corresponded to TCP of 93.6% and 97.2%. Overall, the quality of dosimetric reporting was poor; recommended reporting guidelines are presented.ConclusionsWith current typical SRS doses of 12 Gy in 1 fraction, 18 Gy in 3 fractions, and 25 Gy in 5 fractions, 3- to 5-year TCP exceeds 91%. To improve pooled data analyses to optimize treatment outcomes for patients with vestibular schwannoma, future reports of SRS should include complete dosimetric details with well-defined tumor control and toxicity endpoints.

Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE + NTE model to analyze data on APC(1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4He, 12C, 16O, 28Si or 56Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose-response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

We present a novel mathematical formalism to predict the kinetics of DNA damage repair after exposure to both low- and high-LET radiation (X rays; 350 MeV/n 40Ar; 600 MeV/n 56Fe). Our method is based on monitoring DNA damage repair protein 53BP1 that forms radiation-induced foci (RIF) at locations of DNA double-strand breaks (DSB) in the nucleus and comparing its expression in primary skin fibroblasts isolated from 15 mice strains. We previously reported strong evidence for clustering of nearby DSB into single repair units as opposed to the classic "contact-first" model where DSB are considered immobile. Here we apply this clustering model to evaluate the number of remaining RIF over time. We also show that the newly introduced kinetic metrics can be used as surrogate biomarkers for in vivo radiation toxicity, with potential applications in radiotherapy and human space exploration. In particular, we observed an association between the characteristic time constant of RIF repair measured in vitro and survival levels of immune cells collected from irradiated mice. Moreover, the speed of DNA damage repair correlated not only with radiation-induced cellular survival in vivo, but also with spontaneous cancer incidence data collected from the Mouse Tumor Biology database, suggesting a relationship between the efficiency of DSB repair after irradiation and cancer risk.

Purpose: The in vitro clonogenic assay (IVCA) is the mainstay of quantitative radiobiology. Here, we investigate the benefit of a time-resolved IVCA version (trIVCA) to improve the quantification of clonogenic survival and relative biological effectiveness (RBE) by analyzing cell colony growth behavior. Materials & Methods: In the IVCA, clonogenicity classification of cell colonies is performed based on a fixed colony size threshold after incubation. In contrast, using trIVCA, we acquire time-lapse microscopy images during incubation and track the growth of each colony using neural-net-based image segmentation. Attributes of the resulting growth curves are then used as predictors for a decision tree classifier to determine clonogenicity of each colony. The method was applied to three cell lines, each irradiated with 250 kV X-rays in the range 0–8 Gy and carbon ions of high LET (100 keV/μm, dose-averaged) in the range 0–2 Gy. We compared the cell survival curves determined by trIVCA to those from the classical IVCA across different size thresholds and incubation times. Further, we investigated the impact of the assaying method on RBE determination. Results: Size distributions of abortive and clonogenic colonies overlap consistently, rendering perfect separation via size threshold unfeasible at any readout time. This effect is dose-dependent, systematically inflating the steepness and curvature of cell survival curves. Consequently, resulting cell survival estimates show variability between 3% and 105%. This uncertainty propagates into RBE calculation with variability between 8% and 25% at 2 Gy.Determining clonogenicity based on growth curves has an accuracy of 95% on average. Conclusion: The IVCA suffers from substantial uncertainty caused by the overlap of size distributions of delayed abortive and clonogenic colonies. This impairs precise quantification of cell survival and RBE. By considering colony growth over time, our method improves assaying clonogenicity.

Background and Purpose: Radiation-induced brainstem necrosis after proton therapy is a severe toxicity with potential association to uncertainties in the proton relative biological effectiveness (RBE). A constant RBE of 1.1 is assumed clinically, but the RBE is known to vary with linear energy transfer (LET). LET-inclusive predictive models of toxicity may therefore be beneficial during proton treatment planning. Hence, we aimed to construct models describing the association between brainstem necrosis and LET in the brainstem. Materials and methods: A matched case-control cohort (n = 28, 1:3 case-control ratio) of symptomatic brainstem necrosis was selected from 954 paediatric ependymoma brain tumour patients treated with passively scattered proton therapy. Dose-averaged LET (LETd) parameters in restricted volumes (L50%, L10% and L0.1cm3, the cumulative LETd) within high-dose thresholds were included in linear- and logistic regression normal tissue complication probability (NTCP) models. Results: A 1 keV/µm increase in L10% to the brainstem volume receiving dose over 54 Gy(RBE) led to an increased brainstem necrosis risk [95% confidence interval] of 2.5 [0.0, 7.8] percentage points. The corresponding logistic regression model had area under the receiver operating characteristic curve (AUC) of 0.76, increasing to 0.84 with the anterior pons substructure as a second parameter. 19 [7, 350] patients with toxicity were required to associate the L10% (D > 54 Gy(RBE)) and brainstem necrosis with 80% statistical power. Conclusion: The established models of brainstem necrosis illustrate a potential impact of high LET regions in patients receiving high doses to the brainstem, and thereby support LET mitigation during clinical treatment planning.

There has been some controversy over the use of radiobiological models when modeling the dose-response curves of ionizing radiation (IR)-induced chromosome aberration and tumor prevalence, as those curves usually show obvious non-targeted effects (NTEs) at low doses of high linear energy transfer (LET) radiation. The lack of understanding the contribution of NTEs to IR-induced carcinogenesis can lead to distinct deviations of relative biological effectiveness (RBE) estimations of carcinogenic potential, which are widely used in radiation risk assessment and radiation protection. In this work, based on the initial pattern of two classes of IR-induced DNA double-strand breaks (DSBs) clustering in chromatin domains and the subsequent incorrect repair processes, we proposed a novel radiobiological model to describe the dose-response curves of two carcinogenic-related endpoints within the same theoretical framework. The representative experimental data was used to verify the consistency and validity of the present model. The fitting results indicated that, compared with targeted effect (TE) and NTE models, the current model has better fitting ability when dealing with the experimental data of chromosome aberration and tumor prevalence induced by multiple types of IR with different LETs. Notably, the present model without introducing an NTE term was adequate to describe the dose-response curves of IR-induced chromosome aberration and tumor prevalence with NTEs in low-dose regions. Based on the fitting parameters, the LET-dependent RBE values were calculated for three given low doses. Our results showed that the RBE values predicted by the current model gradually decrease with the increase of doses for the endpoints of chromosome aberration and tumor prevalence. In addition, the calculated RBE was also compared with those evaluated from other models. These analyses show that the proposed model can be used as an alternative tool to well describe dose-response curves of multiple carcinogenic-related endpoints and effectively estimate RBE in low-dose regions.

Monte Carlo (MC) simulations can be used to accurately simulate dose and linear energy transfers (LET) distributions, thereby allowing for the calculation of the relative biological effectiveness (RBE) of protons. We present hereby the validation and implementation of a workflow for the Monte Carlo modelling of the double scattered and pencil beam scanning proton beamlines at our institution. The TOPAS/Geant4 MC model of the clinical nozzle has been comprehensively validated against measurements. The validation also included a comparison between simulated clinical treatment plans for four representative patients and the clinical treatment planning system (TPS). Moreover, an in-house tool implemented in Python was tested to assess the variable RBE-weighted dose in proton plans, which was illustrated for a patient case with a developing radiation-induced toxicity. The simulated range and modulation width closely matches the measurements. Gamma-indexes (3%/3 mm 3D), which compare the TPS and MC computations, showed a passing rate superior to 98%. The calculated RBE-weighted dose presented a slight increase at the necrosis location, within the PTV margins. This indicates the need for reporting on the physical and biological effects of irradiation in high dose regions, especially at the healthy tissues and increased LET distributions location. The results demonstrate that the Monte Carlo method can be used to independently validate a TPS calculation, and to estimate LET distributions. The features of the in-house tool can be used to correlate LET and RBE-weighted dose distributions with the incidence of radiation-induced toxicities following proton therapy treatments. [ABSTRACT FROM AUTHOR]

When an ion beam penetrates deeply into the body, its kinetic energy decreases, and its biological effect increases due to the change of the beam quality. To give a uniform biological effect to the target, it is necessary to reduce the absorbed dose with the depth. A bio-physical model estimating the relationship between ion beam quality and biological effect is necessary to determine the relative biological effectiveness (RBE) of the ion beam that changes with depth. For this reason, Lawrence Berkeley Laboratory, National Institute of Radiological Sciences (NIRS) and GSI have each developed their own model at the starting of the ion beam therapy. Also, NIRS developed a new model at the starting of the scanning irradiation. Although the Local Effect Model (LEM) at the GSI and the modified Microdosimetric Kinetic Model (MKM) at the NIRS, the both are currently used, can similarly predict radiation quality-induced changes in surviving fraction of cultured cell, the clinical RBE-weighted doses for the same absorbed dose are different. This is because the LEM uses X-rays as a reference for clinical RBE, whereas the modified MKM uses carbon ion beam as a reference and multiplies it by a clinical factor of 2.41. Therefore, both are converted through the absorbed dose. In PART 2, I will describe the development of such a bio-physical model, as well as the birth and evolution of a treatment planning system and image guided radiotherapy. [ABSTRACT FROM AUTHOR]

Background/Aim: This study aimed to confirm the relative biological effectiveness (RBE) values of the proton beam therapy (PBT) system installed in Shonan Kamakura General Hospital. Materials and Methods: Clonogenic cellsurvival assays were performed with a human salivary gland (HSG) cell line, a human tongue squamous-cell carcinoma cell line (SAS), and a human osteosarcoma cell line (MG-63). Cells were irradiated with proton beams and X-rays with different doses (1.8, 3.6, 5.5, and 7.3 Gy for proton beams, and 2, 4, 6, and 8 Gy for X-rays). Proton beam irradiation used spot-scanning methods and three different depths (at the proximal, center, and distal sides of the spread-out Bragg peak). RBE values were obtained from a comparison of the dose that resulted in a surviving fraction of 10% (D10). Results: D10 of proton beams at the proximal, center, and distal sides and X-rays in HSG were 4.71, 4.71, 4.51, and 5.25 Gy, respectively; those in SAS were 5.08, 5.04, 5.01, and 5.59 Gy, respectively; and those in MG-63 were 5.36, 5.42, 5.12, and 6.06 Gy, respectively. The RBE10 values at the proximal, center, and distal sides in HSG were 1.11, 1.11, and 1.16 respectively; those in SAS were 1.10, 1.11, and 1.12, respectively; and those in MG-63 were 1.13, 1.12, and 1.18, respectively. Conclusion: RBE10 values of 1.10-1.18 were confirmed by in vitro experiments using the PBT system. These results are considered acceptable for clinical use in terms of therapeutic efficacy and safety. [ABSTRACT FROM AUTHOR]

The most recent publicly available data on all solid cancer incidence from the Life Span Study (LSS) of Japanese A-bomb survivors provides colon dose contributions weighted with a relative biological effectiveness (RBE) of 10 for neutrons, relative to gammas. However, there is evidence from several investigations that the neutron RBE for A-bomb survivors may be higher than 10. The change in the shape of the corresponding dose–response curves was evaluated by Hafner and co-workers in a previous study by applying sex-specific linear-quadratic dose models to previous LSS data for all solid cancer incidence that include separate neutron and gamma absorbed doses for several organs, in contrast to the most recent data. The resulting curvature change became significantly negative for males at an RBE of 140 for colon, 100 for liver, and 80 for organ averaged dose. For females, the corresponding RBE values were 110, 80, and 60 for colon, liver, and organ averaged doses. The present study compares three different methods to calculate the 95% confidence intervals in an analysis of the curvature with increasing RBE. Further, the impact of a higher neutron RBE on the work of the International Commission on Radiological Protection, and the importance of including uncertainties and performing sensitivity analysis of different parameters in radiation risk assessment are discussed. [ABSTRACT FROM AUTHOR]

Long-term human space missions such as a future journey to Mars could be characterized by several hazards, among which radiation is one the highest-priority problems for astronaut health. In this work, exploiting a pre-existing interface between the BIANCA biophysical model and the FLUKA Monte Carlo transport code, a study was performed to calculate astronaut absorbed doses and equivalent doses following GCR exposure under different shielding conditions. More specifically, the interface with BIANCA allowed us to calculate both the RBE for cell survival, which is related to non-cancer effects, and that for chromosome aberrations, related to the induction of stochastic effects, including cancer. The results were then compared with cancer and non-cancer astronaut dose limits. Concerning the stochastic effects, the equivalent doses calculated by multiplying the absorbed dose by the RBE for chromosome aberrations ("high-dose method") were similar to those calculated using the Q-values recommended by ICRP. For a 650-day mission at solar minimum (representative of a possible Mars mission scenario), the obtained values are always lower than the career limit recommended by ICRP (1 Sv), but higher than the limit of 600 mSv recently adopted by NASA. The comparison with the JAXA limits is more complex, since they are age and sex dependent. Concerning the deterministic limits, even for a 650-day mission at solar minimum, the values obtained by multiplying the absorbed dose by the RBE for cell survival are largely below the limits established by the various space agencies. Following this work, BIANCA, interfaced with an MC transport code such as FLUKA, can now predict RBE values for cell death and chromosome aberrations following GCR exposure. More generally, both at solar minimum and at solar maximum, shielding of 10 g/cm2 Al seems to be a better choice than 20 g/cm2 for astronaut protection against GCR. [ABSTRACT FROM AUTHOR]

Proton (p) and carbon (C) ion beams are in clinical use for cancer treatment, although other particles such as He, Be, and B ions have more recently gained attention. Identification of the most optimal ion beam for radiotherapy is a challenging task involving, among others, radiobiological characterization of a beam, which is depth-, energy-, and cell type- dependent. This study uses the FLUKA and MCDS Monte Carlo codes in order to estimate the relative biological effectiveness (RBE) for several ions of potential clinical interest such as p, 4He, 7Li, 10Be, 10B, and 12C forming a spread-out Bragg peak (SOBP). More specifically, an energy spectrum of the projectiles corresponding to a 5-cm SOBP at a depth of 8 cm was used. All secondary particles produced by the projectiles were considered and RBE was determined based on radiation-induced Double Strand Breaks (DSBs), as calculated by MCDS. In an attempt to identify the most optimal ion beam, using the latter data, biological optimization was performed and the obtained depth–dose distributions were inter-compared. The results showed that 12C ions are more effective inside the SOBP region, which comes at the expense of higher dose values at the tail (i.e., after the SOBP). In contrast, p beams exhibit a higher D S O P B / D E n t r a n c e ratio, if physical doses are considered. By performing a biological optimization in order to obtain a homogeneous biological dose (i.e., dose × RBE) in the SOBP, the corresponding advantages of p and 12C ions are moderated. 7Li ions conveniently combine a considerably lower dose tail and a D S O P B / D E n t r a n c e ratio similar to 12C. This work contributes towards identification of the most optimal ion beam for cancer therapy. The overall results of this work suggest that 7Li ions are of potential interest, although more studies are needed to demonstrate the relevant advantages. Future work will focus on studying more complex beam configurations. [ABSTRACT FROM AUTHOR]

Purpose: We quantified the effect of various forward‐based treatment‐planning strategies in proton therapy on dose‐weighted linear energy transfer (LETd). By maintaining the dosimetric quality at a clinically acceptable level, we aimed to evaluate the differences in LETd among various treatment‐planning approaches and their practicality in minimizing biologic uncertainties associated with LETd. Method: Eight treatment‐planning strategies that are achievable in commercial treatment‐planning systems were applied on a cylindrical water phantom and four pediatric brain tumor cases. Each planning strategy was compared to either an opposed lateral plan (phantom study) or original clinical plan (patient study). Deviations in mean and maximum LETd from clinically acceptable dose distributions were compared. Results: In the phantom study, using a range shifter and altering the robust scenarios during optimization had the largest effect on the mean clinical target volume LETd, which was reduced from 4.5 to 3.9 keV/μm in both cases. Variations in the intersection angle between beams had the largest effect on LETd in a ring defined 3 to 5 mm outside the target. When beam intersection angles were reduced from opposed laterals (180°) to 120°, 90°, and 60°, corresponding maximum LETd increased from 7.9 to 8.9, 10.9, and 12.2 keV/μm, respectively. A clear trend in mean and maximum LETd variations in the clinical cases could not be established, though spatial distribution of LETd suggested a strong dependence on patient anatomy and treatment geometry. Conclusion: Changes in LETd from treatment‐plan setup follow intuitive trends in a controlled phantom experiment. Anatomical and other patient‐specific considerations, however, can preclude generalizable strategies in clinical cases. For pediatric cranial radiation therapy, we recommend using opposed lateral treatment fields to treat midline targets. [ABSTRACT FROM AUTHOR]

Microdosimetric energy depositions have been suggested as a key variable for the modeling of the relative biological effectiveness (RBE) in proton and ion radiation therapy. However, microdosimetry has been underutilized in radiation therapy. Recent advances in detector technology allow the design of new mico- and nano-dosimeters. At the same time Monte Carlo (MC) simulations have become more widely used in radiation therapy. In order to address the growing interest in the field, a microdosimetric extension was developed in TOPAS. The extension provides users with the functionality to simulate microdosimetric spectra as well as the contribution of secondary particles to the spectra, calculate microdosimetric parameters, and determine RBE with a biological weighting function approach or with the microdosimetric kinetic (MK) model. Simulations were conducted with the extension and the results were compared with published experimental data and other simulation results for three types of microdosimeters, a spherical tissue equivalent proportional counter (TEPC), a cylindrical TEPC and a solid state microdosimeter. The corresponding microdosimetric spectra obtained with TOPAS from the plateau region to the distal tail of the Bragg curve generally show good agreement with the published data.

Experimental studies reporting murine Harderian gland (HG) tumourigenesis have been a NASA concern for many years. Studies used particle accelerators to produce beams that, on beam entry, consist of a single isotope also present in the galactic cosmic ray (GCR) spectrum. In this paper synergy theory is described, potentially applicable to corresponding mixed-field experiments, in progress, planned, or hypothetical. The "obvious" simple effect additivity (SEA) approach of comparing an observed mixture dose-effect relationship (DER) to the sum of the components' DERs is known from other fields of biology to be unreliable when the components' DERs are highly curvilinear. Such curvilinearity may be present at low fluxes such as those used in the one-ion HG experiments due to non-targeted ('bystander') effects, in which case a replacement for SEA synergy theory is needed. This paper comprises in silico modeling of published experimental data using a recently introduced, arguably optimal, replacement for SEA: incremental effect additivity (IEA). Customized open-source software is used. IEA is based on computer numerical integration of non-linear ordinary differential equations. To illustrate IEA synergy theory, possible rapidly-sequential-beam mixture experiments are discussed, including tight 95% confidence intervals calculated by Monte-Carlo sampling from variance-covariance matrices. The importance of having matched one-ion and mixed-beam experiments is emphasized. Arguments are presented against NASA over-emphasizing accelerator experiments with mixed beams whose dosing protocols are standardized rather than being adjustable to take biological variability into account. It is currently unknown whether mixed GCR beams sometimes have statistically significant synergy for the carcinogenesis endpoint. Synergy would increase risks for prolonged astronaut voyages in interplanetary space.

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.

Inverse treatment planning in intensity modulated particle therapy (IMPT) with scanned carbon-ion beams is currently based on the optimization of RBE-weighted dose to satisfy requirements of target coverage and limited toxicity to organs-at-risk (OARs) and healthy tissues. There are many feasible IMPT plans that meet these requirements, which allows the introduction of further criteria to narrow the selection of a biologically optimal treatment plan. We propose a novel treatment planning strategy based on the simultaneous optimization of RBE-weighted dose and nanometric ionization details (ID) as a new physical characteristic of the delivered plan beyond LET. In particular, we focus on the distribution of large ionization clusters (more than 3 ionizations) to enhance the biological effect across the target volume while minimizing biological effect in normal tissues. Carbon-ion treatment plans for different patient geometries and beam configurations generated with the simultaneous optimization strategy were compared against reference plans obtained with RBE-weighted dose optimization alone. Quality indicators, inhomogeneity index and planning volume histograms of RBE-weighted dose and large ionization clusters were used to evaluate the treatment plans. We show that with simultaneous optimization, ID distributions can be optimized in carbon-ion radiotherapy without compromising the RBE-weighted dose distributions. This strategy can potentially be used to account for optimization of endpoints closely related to radiation quality to achieve better tumor control and reduce risks of complications.

The authors present a review of new experimental data on the relative biological effectiveness (RBE) of the impact on the body of fast neutrons and accelerated multicharged ions (AMIs) in small, absorbed doses of 0.01–0.5 Gy, which are allowed by modern radiation safety standards for the career of astronauts to limit the risk of delayed adverse effects. According to new radiobiological data for low doses and their rates, the literature presents higher (2–3 times) maximum values of the RBE coefficients for cytogenetic disorders that persist in the long-term period; malignant transformation of cells and the risk of developing tumors of different tissues; reduction in life expectancy; disorders of neurons in the cerebral cortex and damage to individual organs; and the degree of clouding of the lens and the formation of cataracts. Based on the analysis performed, a new dependence of quality factors on linear energy transfer is presented, from which it follows that the estimated values of equivalent doses in relation to the effects of galactic cosmic rays and fast neutrons, as well as the calculated values of the total radiation risk during the life of astronauts, will increase significantly. [ABSTRACT FROM AUTHOR]

• We assessed the prognostic factors for sacrum insufficiency fractures (SIFs) in carbon-ion RT. • Median RBE-weighted dose to the sacrum was a risk factor for SIF. • Neither LET nor physical dose parameters were significant risk factors for SIF. The correlation between dose-averaged linear energy transfer (LETd) and its therapeutic or adverse effects, especially in carbon-ion radiotherapy (CIRT), remains controversial. This study aimed to investigate the effects of LETd and dose on pelvic insufficiency fractures after CIRT. Among patients who underwent CIRT for uterine carcinoma, 101 who were followed up for > 6 months without any other therapy were retrospectively analyzed. The sacrum insufficiency fractures (SIFs) were graded according to the Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer toxicity criteria. The correlations between the relative biological effectiveness (RBE)-weighted dose, LETd, physical dose, clinical factors, and SIFs were evaluated. In addition, we analyzed the association of SIF with LETd, physical dose, and clinical factors in cases where the sacrum D50% RBE-weighted dose was above the median dose. At the last follow-up, 19 patients developed SIFs. Receiver operating characteristic curve analysis revealed that the sacrum D50% RBE-weighted dose was a valuable predictor of SIF. Univariate analyses suggested that LETd V10 keV/µm, physical dose V5 Gy, and smoking status were associated with SIF. Cox regression analysis in patients over 50 years of age validated that current smoking habit was the sole risk factor for SIF. Therefore, LETd or physical dose parameters were not associated with SIF prediction. The sacrum D50% RBE-weighted dose was identified as a risk factor for SIF. Additionally, neither LETd nor physical dose parameters were associated with SIF prediction. [ABSTRACT FROM AUTHOR]

To compare biochemical recurrence free survival (BCRFS) and cancer-specific survival (CSS) after brachytherapy using the AUA and the Phoenix definitions. 2634 men with T1-T4N0M0 prostate cancer were treated with brachytherapy with or without neoadjuvant hormonal therapy or external beam radiation therapy. Five, 10, and 15- year BCRFS and CSS were estimated with Kaplan-Meier estimates with log rank. Multivariate analysis of survival was performed with Cox regression analysis. Median age was 66, follow-up was 8.6 years, and prostate specific antigen was 6.9. Overall, 11.1% (n = 293) of patients experienced Phoenix BCR and 17.48% (n = 457) experienced AUA BCR. The rates of AUA BCR and Phoenix BCR were significantly different at 5 and 10-years but not at 15 years. Patients treated with BED ≤ 200 Gy were more likely to experience AUA BCR (22.5% vs. 12.4%, OR 1.44, p < 0.001) and Phoenix BCR (14.3% and 8.3%, OR 1.37, p < 0.001) than patients treated with a BED > 200 Gy. Compared to the Phoenix definition, the AUA definition of BCR after brachytherapy is associated with significantly worse BCRFS for the first 15 years after treatment. Receiving a BED > 200, which cannot be achieved without the addition of brachytherapy, is associated with better BCRFS and CSS. Our findings reaffirm the importance of dose in the management of prostate cancer [ABSTRACT FROM AUTHOR]

The outcome of the exposure of living organisms to ionizing radiation is determined by the distribution of the associated energy deposition at different spatial scales. Radiation proceeds through ionizations and excitations of hit molecules with an ~ nm spacing. Approaches such as nanodosimetry/microdosimetry and Monte Carlo track-structure simulations have been successfully adopted to investigate radiation quality effects: they allow to explore correlations between the spatial clustering of such energy depositions at the scales of DNA or chromosome domains and their biological consequences at the cellular level. Physical features alone, however, are not enough to assess the entity and complexity of radiation-induced DNA damage: this latter is the result of an interplay between radiation track structure and the spatial architecture of chromatin, and further depends on the chromatin dynamic response, affecting the activation and efficiency of the repair machinery. The heterogeneity of radiation energy depositions at the single-cell level affects the trade-off between cell inactivation and induction of viable mutations and hence influences radiation-induced carcinogenesis. In radiation therapy, where the goal is cancer cell inactivation, the delivery of a homogenous dose to the tumour has been the traditional approach in clinical practice. However, evidence is accumulating that introducing heterogeneity with spatially fractionated beams (mini- and microbeam therapy) can lead to significant advantages, particularly in sparing normal tissues. Such findings cannot be explained in merely physical terms, and their interpretation requires considering the scales at play in the underlying biological mechanisms, suggesting a systemic response to radiation. [ABSTRACT FROM AUTHOR]

The relative biological effectiveness (RBE) calculations used during the planning of ion therapy treatments are generally based on the microdosimetric kinetic model (MKM) and the local effect model (LEM). The Mayo Clinic Florida MKM (MCF MKM) was recently developed to overcome the limitations of previous MKMs in reproducing the biological data and to eliminate the need for ion-exposed in vitro data as input for the model calculations. Since we are considering to implement the MCF MKM in clinic, this article presents (a) an extensive benchmark of the MCF MKM predictions against corresponding in vitro clonogenic survival data for 4 rodent and 10 cell lines exposed to ions from 1H to 238U, and (b) a systematic comparison with published results of the latest version of the LEM (LEM IV). Additionally, we introduce a novel approach to derive an approximate value of the MCF MKM model parameters by knowing only the animal species and the mean number of chromosomes. The overall good agreement between MCF MKM predictions and in vitro data suggests the MCF MKM can be reliably used for the RBE calculations. In most cases, a reasonable agreement was found between the MCF MKM and the LEM IV. [ABSTRACT FROM AUTHOR]

Plasmid DNA is useful for investigating the DNA damaging effects of ionizing radiation. In this study, we have explored the feasibility of plasmid DNA-based detectors to assess the DNA damaging effectiveness of two radiotherapy X-ray beam qualities after undergoing return shipment of ~8000 km between two institutions. The detectors consisted of 18   μ L of pBR322 DNA enclosed with an aluminum seal in nine cylindrical cavities drilled into polycarbonate blocks. We shipped them to Toronto, Canada for irradiation with either 100   kVp   or 6   MV   X-ray beams to doses of 10, 20, and 30 Gy in triplicate before being shipped back to San Diego, USA. The Toronto return shipment also included non-irradiated controls and we kept a separate set of controls in San Diego. In San Diego, we quantified DNA single strand breaks (SSBs), double strand breaks (DSBs), and applied Nth and Fpg enzymes to quantify oxidized base damage. The rate of DSBs/Gy/plasmid was 2.8 ± 0.7   greater for the 100 kVp than the 6 MV irradiation. The 100   kVp irradiation also resulted in 5 ± 2 times more DSBs/SSB than the 6   MV beam, demonstrating that the detector is sensitive enough to quantify relative DNA damage effectiveness, even after shipment over thousands of kilometers. [ABSTRACT FROM AUTHOR]

• Translation between European and Japanese RBE modelling for constraint validation. • Potential pitfalls for constraint definition in carbon ion radiotherapy of CNS. • RBE model translation trend outliers and their association with clinical toxicities. • Decision making process based on two RBE models, triggered by CNS toxicities. Carbon ion radiotherapy (CIRT) treatment planning is based on relative biological effectiveness (RBE) weighted dose calculations. A large amount of clinical evidence for CIRT was collected in Japan with RBE estimated by the modified microdosimetric kinetic model (MKM) while all European centres apply the first version of the local effect model (LEM). Japanese schedules have been used in Europe with adapted prescription dose and organs at risk (OAR) dose constraints. Recently, less conservative adapted LEM constraints have been implemented in clinical practice. The aim of this study was to analyse the new set of LEM dose constraints for brain parenchyma, brainstem and optic system considering both RBE models and evaluating early clinical data. 31 patients receiving CIRT at MedAustron were analysed using the RayStation v9A planning system by recalculating clinical LEM-based plans in MKM. Dose statistics (D1cm3, D5cm3, D0.1cm3, D0.7cm3, D10%, D20%) were extracted for relevant critical OARs. Curve fitting for those values was performed, resulting in linear quadratic translation models. Clinical and radiological toxicity was evaluated. Based on derived fits, currently applied LEM constraints matched recommended MKM constraints with deviations between −8% and +3.9%. For particular cases, data did not follow the expected LEM vs MKM trends resulting in outliers. Radiological (asymptomatic) toxicity was detected in two outlier cases. Respecting LEM constraints does not automatically ensure that MKM constraints are met. Constraints for both RBE models need to be fulfilled for future CIRT patients at MedAustron. Careful selection of planning strategies is essential. [ABSTRACT FROM AUTHOR]

The advantageous depth dose profile of ion beams together with state of the art beam delivery and treatment planning systems allow for highly conformal tumor treatments in patients. First treatments date back to 1954 at the Lawrence Berkeley Laboratory (LBL) and in Europe, ion beam therapy started in the mid-1990s at the Paul-Scherrer Institute (PSI) with protons and at the Helmholtz Center for Heavy Ion Research (GSI) with carbon ions, followed by the Heidelberg Ion Therapy Center (HIT) in Heidelberg. This review describes the historical development of ion beam therapy in Germany based on the pioneering work at LBL and in the context of simultaneous developments in other countries as well as recent developments.

A thin diamond membrane energy-dispersive dosimeter 50 μm thick was fabricated for estimating clinical dose distribution. In contrast to conventional semiconductors, diamond wide-bandgap semiconductors are expected to have excellent radiation tolerance and biological compatibility based on the linear relationship of stopping power ratio for clinical carbon particles. Linear energy transfer (LET) spectra were obtained along with the Bragg curve for a clinical carbon beam generated at Gunma University Heavy Ion Medical Center. The relative biological effectiveness (RBE) distributions were estimated from the LET spectra for both the mono-energy and spread-out Bragg peak irradiation configurations. The diamond detector was also used as a solid ionization chamber to obtain the radiation-induced current (RIC) distribution, which represents the physical dose distribution. The clinical dose distribution was estimated from the RIC and RBE distributions as proof of concept for the clinical carbon beam therapy field with a single-chip diamond energy-dispersive dosimeter. [ABSTRACT FROM AUTHOR]

PURPOSE: Proton therapy can allow for superior avoidance of normal tissues. A widespread consensus has been reached that proton therapy should be used for patients with curable pediatric brain tumor to avoid critical central nervous system structures. Brainstem necrosis is a potentially devastating, but rare, complication of radiation. Recent reports of brainstem necrosis after proton therapy have raised concerns over the potential biological differences among radiation modalities. We have summarized findings from the National Cancer Institute Workshop on Proton Therapy for Children convened in May 2016 to examine brainstem injury. METHODS AND MATERIALS: Twenty-seven physicians, physicists, and researchers from 17 institutions with expertise met to discuss this issue. The definition of brainstem injury, imaging of this entity, clinical experience with photons and photons, and potential biological differences among these radiation modalities were thoroughly discussed and reviewed. The 3 largest US pediatric proton therapy centers collectively summarized the incidence of symptomatic brainstem injury and physics details (planning, dosimetry, delivery) for 671 children with focal posterior fossa tumors treated with protons from 2006 to 2016. RESULTS: The average rate of symptomatic brainstem toxicity from the 3 largest US pediatric proton centers was 2.38%. The actuarial rate of grade ≥2 brainstem toxicity was successfully reduced from 12.7% to 0% at 1 center after adopting modified radiation guidelines. Guidelines for treatment planning and current consensus brainstem constraints for proton therapy are presented. The current knowledge regarding linear energy transfer (LET) and its relationship to relative biological effectiveness (RBE) are defined. We review the current state of LET-based planning. CONCLUSIONS: Brainstem injury is a rare complication of radiation therapy for both photons and protons. Substantial dosimetric data have been collected for brainstem injury after proton therapy, and established guidelines to allow for safe delivery of proton radiation have been defined. Increased capability exists to incorporate LET optimization; however, further research is needed to fully explore the capabilities of LET- and RBE-based planning.

The quality factor (Q) is formally linked to the stochastic (e.g., carcinogenic) risk of diverse ionizing radiations at low doses and/or low dose rates. Q can be a function of the non-stochastic physical quantity Linear Energy Transfer (LET) or the microdosimetric parameter lineal energy (y). These two physical quantities can be calculated either by Monte Carlo (MC) track-structure simulations or by analytic models. In this work, various generalized analytical models were utilized and combined to determine the proton lineal energy spectra in liquid water spheres of various sizes (i.e., 10–3000 nm diameter) over the proton energy range of 1–250 MeV. The calculated spectra were subsequently used within the Theory of Dual Radiation Action (TDRA) and the ICRU Report 40 microdosimetric methodologies to determine the variation of Q ¯ with proton energy. The results revealed that the LET-based Q values underestimated the microdosimetric-based Q ¯ values for protons with energy below ~100 MeV. At energies relevant to the Bragg peak region (<20–30 MeV), the differences were larger than 20–50%, while reaching 200–500% at ~5 MeV. It was further shown that the microdosimetric-based Q ¯ values for protons below ~100 MeV were sensitive to the sphere size. Finally, condensed-phase effects had a very small (<5%) influence on the calculated microdosimetric-based Q ¯ over the proton energy range considered here. [ABSTRACT FROM AUTHOR]

Purpose: Targeting the prostate-specific membrane antigen (PSMA) using lutetium-177-labeled PSMA-specific tracers has become a very promising novel therapy option for prostate cancer (PCa). The efficacy of this therapy might be further improved by replacing the β-emitting lutetium-177 with the α-emitting actinium-225. Actinium-225 is thought to have a higher therapeutic efficacy due to the high linear energy transfer (LET) of the emitted α-particles, which can increase the amount and complexity of the therapy induced DNA double strand breaks (DSBs). Here we evaluated the relative biological effectiveness of [225Ac]Ac-PSMA-I&T and [177Lu]Lu-PSMA-I&T by assessing in vitro binding characteristics, dosimetry, and therapeutic efficacy. Methods and results: The PSMA-expressing PCa cell line PC3-PIP was used for all in vitro assays. First, binding and displacement assays were performed, which revealed similar binding characteristics between [225Ac]Ac-PSMA-I&T and [177Lu]Lu-PSMA-I&T. Next, the assessment of the number of 53BP1 foci, a marker for the number of DNA double strand breaks (DSBs), showed that cells treated with [225Ac]Ac-PSMA-I&T had slower DSB repair kinetics compared to cells treated with [177Lu]Lu-PSMA-I&T. Additionally, clonogenic survival assays showed that specific targeting with [225Ac]Ac-PSMA-I&T and [177Lu]Lu-PSMA-I&T caused a dose-dependent decrease in survival. Lastly, after dosimetric assessment, the relative biological effectiveness (RBE) of [225Ac]Ac-PSMA-I&T was found to be 4.2 times higher compared to [177Lu]Lu-PSMA-I&T. Conclusion: We found that labeling of PSMA-I&T with lutetium-177 or actinium-225 resulted in similar in vitro binding characteristics, indicating that the distinct biological effects observed in this study are not caused by a difference in uptake of the two tracers. The slower repair kinetics of [225Ac]Ac-PSMA-I&T compared to [177Lu]Lu-PSMA-I&T correlates to the assumption that irradiation with actinium-225 causes more complex, more difficult to repair DSBs compared to lutetium-177 irradiation. Furthermore, the higher RBE of [225Ac]Ac-PSMA-I&T compared to [177Lu]Lu-PSMA-I&T underlines the therapeutic potential for the treatment of PCa. [ABSTRACT FROM AUTHOR]

Background: Proton relative biological effectiveness (RBE) is known to depend on physical factors of the proton beam, such as its linear energy transfer (LET), as well as on cell‐line specific biological factors, such as their ability to repair DNA damage. However, in a clinical setting, proton RBE is still considered to have a fixed value of 1.1 despite the existence of several empirical models that can predict proton RBE based on how a cell's survival curve (linear‐quadratic model [LQM]) parameters α and β vary with the LET of the proton beam. Part of the hesitation to incorporate variable RBE models in the clinic is due to the great noise in the biological datasets on which these models are trained, often making it unclear which model, if any, provides sufficiently accurate RBE predictions to warrant a departure from RBE = 1.1. Purpose: Here, we introduce a novel model of proton RBE based on how a cell's intrinsic radiosensitivity varies with LET, rather than its LQM parameters. Methods and materials: We performed clonogenic cell survival assays for eight cell lines exposed to 6 MV x‐rays and 1.2, 2.6, or 9.9 keV/µm protons, and combined our measurements with published survival data (n = 397 total cell line/LET combinations). We characterized how radiosensitivity metrics of the form DSF%, (the dose required to achieve survival fraction [SF], e.g., D10%) varied with proton LET, and calculated the Bayesian information criteria associated with different LET‐dependent functions to determine which functions best described the underlying trends. This allowed us to construct a six‐parameter model that predicts cells' proton survival curves based on the LET dependence of their radiosensitivity, rather than the LET dependence of the LQM parameters themselves. We compared the accuracy of our model to previously established empirical proton RBE models, and implemented our model within a clinical treatment plan evaluation workflow to demonstrate its feasibility in a clinical setting. Results: Our analyses of the trends in the data show that DSF% is linearly correlated between x‐rays and protons, regardless of the choice of the survival level (e.g., D10%, D37%, or D50% are similarly correlated), and that the slope and intercept of these correlations vary with proton LET. The model we constructed based on these trends predicts proton RBE within 15%–30% at the 68.3% confidence level and offers a more accurate general description of the experimental data than previously published empirical models. In the context of a clinical treatment plan, our model generally predicted higher RBE‐weighted doses than the other empirical models, with RBE‐weighted doses in the distal portion of the field being up to 50.7% higher than the planned RBE‐weighted doses (RBE = 1.1) to the tumor. Conclusions: We established a new empirical proton RBE model that is more accurate than previous empirical models, and that predicts much higher RBE values in the distal edge of clinical proton beams. [ABSTRACT FROM AUTHOR]

Purpose: We assessed whether adding sodium borocaptate (BSH) or 4‐borono‐l‐phenylalanine (BPA) to cells irradiated with proton beams influenced the biological effectiveness of those beams against prostate cancer cells to investigate if the alpha particles generated through proton–boron nuclear reactions would be sufficient to enhance the biological effectiveness of the proton beams. Methods: We measured clonogenic survival in DU145 cells treated with 80.4‐ppm BSH or 86.9‐ppm BPA, or their respective vehicles, after irradiation with 6‐MV X‐rays, 1.2‐keV/μm (low linear energy transfer [LET]) protons, or 9.9‐keV/μm (high‐LET) protons. We also measured γH2AX and 53BP1 foci in treated cells at 1 and 24 h after irradiation with the same conditions. Results: We found that BSH radiosensitized DU145 cells across all radiation types. However, no difference was found in relative radiosensitization, characterized by the sensitization enhancement ratio or the relative biological effectiveness, for vehicle‐ versus BSH‐treated cells. No differences were found in numbers of γH2AX or 53BP1 foci or γH2AX/53BP1 colocalized foci for vehicle‐ versus BSH‐treated cells across radiation types. BPA did not radiosensitize DU145 cells nor induced any significant differences when comparing vehicle‐ versus BPA‐treated cells for clonogenic cell survival or γH2AX and 53BP1 foci or γH2AX/53BP1 colocalized foci. Conclusions: Treatment with 11B, at concentrations of 80.4 ppm from BSH or 86.9 ppm from BPA, had no effect on the biological effectiveness of proton beams in DU145 prostate cancer cells. Our results agree with published theoretical calculations indicating that the contribution of alpha particles from such reactions to the total absorbed dose and biological effectiveness is negligible. We also found that BSH radiosensitized DU145 cells to X‐rays, low‐LET protons, and high‐LET protons but that the radiosensitization was not related to DNA damage. [ABSTRACT FROM AUTHOR]

Background: Ion beam therapy allows for substantial sparing of normal tissues. Besides deterministic normal‐tissue complications, stochastic long‐term effects like secondary cancer (SC) induction are of importance when comparing different treatment modalities. Purpose: To develop a modeling approach for comparison of SC risk in proton and carbon ion therapy. Methods and Materials: The local effect model (LEM) is used to predict the relative biological effectiveness (RBE) of SC induction after particle therapy. A key feature of the new approach is the double use of the LEM, reflecting the competition between the two processes of mutation induction (leading to cancer development) and cell inactivation (leading to suppression of cancer development). Based on previous investigations, treatment plans were in this work analyzed for an idealized geometry in order to assess the underlying systematic dependencies of cancer induction. In a further step, relative SC risks were predicted for proton and carbon ion treatment plans prepared for 10 prostate cancer patients. Results: We investigated the impact of factors such as treatment plan geometry, fractionation scheme, and tissue radiosensitivity to photon irradiation on the ion beam SC risk. Our model studies do not result in a clear preference for either protons or carbon ions, but rather indicate a complex interplay of different aspects. Reduced lateral scattering leads to a lower SC risk for carbon ions compared to protons at the lateral field margins in the entrance channel, while an increased risk was found closely behind the tumor due to projectile fragmentation. The fractionation scheme had little impact on the expected risk ratio. With respect to sensitivity parameters, those characterizing RBE for cell killing of potentially cancerous cells as well as of the primary tumor had the most significant impact. The observed general systematic dependencies are in agreement with results from previous model studies. The prostate patient study reveals reduced SC risks predictions for skin and bones for carbon ions as compared to protons, but higher mean risks for bladder and rectum. Conclusion: The methods established in this work provide a basis for further investigating treatment optimizing strategies for ion beam therapy with regard to SC risk comparisons. [ABSTRACT FROM AUTHOR]

Background: The effectiveness of ionizing radiation regarding DNA damage induction depends on its spatial energy deposition pattern. For electrons an increased effectiveness is observed at low kinetic energies due to the enhanced density of energy deposition events at electron track ends. Purpose: A model is presented, which enables the calculation of the double‐strand‐break (DSB) yield and the relative biological effectiveness (RBE) for DSB induction of electrons. Methods: The model applies the mean free path between two ionizations and the assumption that two ionizations within a certain threshold distance are necessary to potentially lead to a DSB. Next to an expression for the electron RBE according to its common definition, a local RBE is determined, which describes the electrons' local effectiveness at a defined point on their track. Results: This local RBE allows a better understanding of microscopic processes resulting from radiation and can be used, for instance, to describe the mean effectiveness of the mixed electron radiation field as a function of the radial distance to the center of an ion track. Conclusions: The presented model reflects the experimentally observed increased effectiveness of low‐energetic electrons. It will be used in a future work to improve RBE predictions for ions performed with the local effect model. [ABSTRACT FROM AUTHOR]