Calculation Of Relative Biological Effectiveness Research Articles

Beyond a constant proton relative biological effectiveness: A survey of clinical and research perspectives among proton institutions in Europe and the United States.

Although proton relative biological effectiveness (RBE) depends on factors like linear energy transfer (LET), tissue properties, dose, and biological endpoint, a constant RBE of 1.1 is recommended in clinical practice. This study surveys proton institutions to explore activities using functionalities beyond a constant proton RBE. Research versions of RayStation integrate functionalities considering variable proton RBE, LET, proton track-ends, and dirty dose. A survey of 19 institutions in Europe and the United States, with these functionalities available, investigated clinical adoption and research prospects using a 25-question online questionnaire. Of the 16 institutions that responded (84% response rate), 13 were clinically active. These clinical institutions prescribe RBE=1.1 but also employ planning strategies centered around special beam arrangements to address potentially enhanced RBE effects in serially structured organs at risk (OARs). Clinical plan evaluation encompassed beam angles/spot position (69%), dose-averaged LET (LETd) (46%), and variable RBE distributions (38%). High ratings (discrete scale: 1-5) were reported for the research functionalities using linear LETd-RBE models, LETd, track-end frequency and dirty dose (averages: 4.0-4.8), while LQ-based phenomenological RBE models dependent on LETd scored lower for optimization (average: 2.2) but congruent for evaluation (average: 4.1). The institutions preferred LET reported as LETd (94%), computed in unit-density water (56%), for all protons (63%), and lean toward LETd-based phenomenological RBE models for clinical use (>50%). Proton institutions recognize RBE variability but adhere to a constant RBE while actively mitigating potential enhancements, particularly in serially structured OARs. Research efforts focus on planning techniques that utilize functionalities beyond a constant RBE, emphasizing standardized LET and RBE calculations to facilitate their adoption in clinical practice and improve clinical data collection. LETd calculated in unit-density water for all protons as input to adaptable phenomenological RBE models was the most suggested approach, aligning with predominant clinical LET and variable RBE reporting.

Primary study of the relative and compound biological effectiveness model for boron neutron capture therapy based on nanodosimetry.

The current radiobiological model employed for boron neutron capture therapy (BNCT) treatment planning, which relies on microdosimetry, fails to provide an accurate representation the biological effects of BNCT. The precision in calculating the relative biological effectiveness (RBE) and compound biological effectiveness (CBE) plays a pivotal role in determining the therapeutic efficacy of BNCT. Therefore, this study focuses on how to improve the accuracy of the biological effects of BNCT. The purpose of this study is to propose new radiation biology models based on nanodosimetry to accurately assess RBE and CBE for BNCT. Nanodosimetry, rooted in ionization cluster size distributions (ICSD), introduces a novel approach to characterize radiation quality by effectively delineating RBE through the ion track structure at the nanoscale. In the context of prior research, this study presents a computational model for the nanoscale assessment of RBE and CBE. We establish a simplified model of DNA chromatin fiber using the Monte Carlo code TOPAS-nBio to evaluate the applicability of ICSD to BNCT and compute nanodosimetric parameters. Our investigation reveals that both homogeneous and heterogeneous nanodosimetric parameters, as well as the corresponding biological model coefficients α and β, along with RBE values, exhibit variations in response to varying intracellular 10B concentrations. Notably, the nanodosimetric parameter effectively captures the fluctuations in model coefficients α and RBE. Our model facilitates a nanoscale analysis of BNCT, enabling predictions of nanodosimetric quantities for secondary ions as well as RBE, CBE, and other essential biological metrics related to the distribution of boron. This contribution significantly enhances the precision of RBE calculations and holds substantial promise for future applications in treatment planning.

Mechanistic modelling of relative biological effectiveness of carbon ion beams and comparison with experiments

Objective. Relative biological effectiveness (RBE) plays a vital role in carbon ion radiotherapy, which is a promising treatment method for reducing toxic effects on normal tissues and improving treatment efficacy. It is important to have an effective and precise way of obtaining RBE values to support clinical decisions. A method of calculating RBE from a mechanistic perspective is reported. Approach. Ratio of dose to obtain the same number of double strand breaks (DSBs) between different radiation types was used to evaluate RBE. Package gMicroMC was used to simulate DSB yields. The DSB inductions were then analyzed to calculate RBE. The RBE values were compared with experimental results. Main results. Furusawa's experiment yielded RBE values of 1.27, 2.22, 3.00 and 3.37 for carbon ion beam with dose-averaged LET of 30.3 keV μm−1, 54.5 keV μm−1, 88 keV μm−1 and 137 keV μm−1, respectively. RBE values computed from gMicroMC simulations were 1.75, 2.22, 2.87 and 2.97. When it came to a more sophisticated carbon ion beam with 6 cm spread-out Bragg peak, RBE values were 1.61, 1.63, 2.19 and 2.36 for proximal, middle, distal and distal end part, respectively. Values simulated by gMicroMC were 1.50, 1.87, 2.19 and 2.34. The simulated results were in reasonable agreement with the experimental data. Significance. As a mechanistic way for the evaluation of RBE for carbon ion radiotherapy by combining the macroscopic simulation of energy spectrum and microscopic simulation of DNA damages, this work provides a promising tool for RBE calculation supporting clinical applications such as treatment planning.

An inter-comparison between radiobiological characteristics of a commercial low-energy IORT system by Geant4-DNA and MCDS Monte Carlo codes

Introduction The need for accurate relative biological effectiveness (RBE) estimation for low energy therapeutic X-rays (corresponding to 50 kV nominal energy of a commercial low-energy IORT system (INTRABEAM)) is a crucial issue due to increased radiobiological effects, respect to high energy photons. Modeling of radiation-induced DNA damage through Monte Carlo (MC) simulation approaches can give useful information. Hence, this study aimed to evaluate and compare RBE of low energy therapeutic X-rays using Geant4-DNA toolkit and Monte Carlo damage simulation (MCDS) code. Materials and methods RBE calculations were performed considering the emitted secondary electron spectra through interactions of low energy X-rays inside the medium. In Geant4-DNA, the DNA strand breaks were obtained by employing a B-DNA model in physical stage with 10.79 eV energy-threshold and the probability of hydroxyl radical’s chemical reactions of about 0.13%. Furthermore, RBE estimations by MCDS code were performed under fully aerobic conditions. Results Acquired results by two considered MC codes showed that the same trend is found for RBEDSB and RBESSB variations. Totally, a reasonable agreement between the calculated RBE values (both RBESSB and RBEDSB) existed between the two considered MC codes. The mean differences of 9.2% and 1.8% were obtained between the estimated RBESSB and RBEDSB values by two codes, respectively. Conclusion Based on the obtained results, it can be concluded that a tolerable accordance is found between the calculated RBEDSB values through MCDS and Geant4-DNA, a fact which appropriates both codes for RBE evaluations of low energy therapeutic X-rays, especially in the case of RBEDSB where lethal damages are regarded.

Variable RBE in proton radiotherapy: a comparative study with the predictive Mayo Clinic Florida microdosimetric kinetic model and phenomenological models of cell survival

Objectives. (1) To examine to what extent the cell- and exposure- specific information neglected in the phenomenological proton relative biological effectiveness (RBE) models could influence the computed RBE in proton therapy. (2) To explore similarities and differences in the formalism and the results between the linear energy transfer (LET)-based phenomenological proton RBE models and the microdosimetry-based Mayo Clinic Florida microdosimetric kinetic model (MCF MKM). (3) To investigate how the relationship between the RBE and the dose-mean proton LET is affected by the proton energy spectrum and the secondary fragments. Approach. We systematically compared six selected phenomenological proton RBE models with the MCF MKM in track-segment simulations, monoenergetic proton beams in a water phantom, and two spread-out Bragg peaks. A representative comparison with in vitro data for human glioblastoma cells (U87 cell line) is also included. Main results. Marked differences were observed between the results of the phenomenological proton RBE models, as reported in previous studies. The dispersion of these models’ results was found to be comparable to the spread in the MCF MKM results obtained by varying the cell-specific parameters neglected in the phenomenological models. Furthermore, while single cell-specific correlation between RBE and the dose-mean proton LET seems reasonable above 2 keV μm−1, caution is necessary at lower LET values due to the relevant contribution of secondary fragments. The comparison with in vitro data demonstrates comparable agreement between the MCF MKM predictions and the results of the phenomenological models. Significance. The study highlights the importance of considering cell-specific characteristics and detailed radiation quality information for accurate RBE calculations in proton therapy. Furthermore, these results provide confidence in the use of the MCF MKM for clonogenic survival RBE calculations in proton therapy, offering a more mechanistic approach compared to phenomenological models.

A time-resolved clonogenic assay for improved cell survival and RBE measurements.

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. 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 250kV X-rays in the range 0-8Gy and carbon ions of high LET (100keV/μm, dose-averaged) in the range 0-2Gy. 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. 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 2Gy.Determining clonogenicity based on growth curves has an accuracy of 95% on average. 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.

A methodology to abridge microdosimetric distributions without a significant loss of the spectral information needed for the RBE computation in carbon ion therapy.

In order to compute the relative biological effectiveness (RBE) of ion radiation therapy with the Mayo Clinic Florida microdosimetric kinetic model (MCF MKM), it is necessary to process entire microdosimetric distributions. Therefore, a posteriori RBE recalculations (i.e., for a different cell line or another biological endpoint) would require whole spectral information. It is currently not practical to compute and store all this data for each clinical voxel. To develop a methodology that allows to store a limited amount of physical information without losing accuracy in the RBE calculations nor the possibility of a posteriori RBE recalculations. Computer simulations for four monoenergetic 12 C ion beams and a 12 C ion spread-out Bragg peak (SOBP) were performed to assess lineal energy distributions as a function of the depth within a water phantom. These distributions were used in combination with the MCF MKM to compute the in vitro clonogenic survival RBE for human salivary gland tumor cells (HSG cell line) and human skin fibroblasts (NB1RGB cell line). The RBE values were also calculated with a new abridged microdosimetric distribution methodology (AMDM) and compared with the reference RBE calculations using the entire distributions. The maximum relative deviation between the RBE values computed using the entire distributions and the AMDM was 0.61% (monoenergetic beams) and 0.49% (SOBP) for the HSG cell line, while 0.45% (monoenergetic beams) and 0.26% (SOBP) for the NB1RGB cell line. The excellent agreement between the RBE values computed using the entire lineal energy distributions and the AMDM represents a milestone for the clinical implementation of the MCF MKM.

Clonogenic Survival RBE Calculations in Carbon Ion Therapy: The Importance of the Absolute Values of α and β in the Photon Dose-Response Curve and a Strategy to Mitigate Their Anticorrelation

The computation of the relative biological effectiveness (RBE) is a fundamental step in the planning of cancer radiotherapy treatments with accelerated ions. Numerical parameters derived analyzing the dose response of the chosen cell line after irradiation to photons (i.e., α and β, namely the linear and quadratic terms of the linear-quadratic model of cell survival) are generally used as input to biophysical models to predict the ion RBE. The α/β ratio for the photon exposure is generally regarded as an indicator of cell radiosensitivity. However, previous studies suggest that α/β might not be a sufficient parameter to model the RBE of relatively high linear energy transfer (LET) radiation such as carbon ions. For a fixed α/β, the effect of the absolute values of α and β on the computed RBE is underexplored. Furthermore, since α and β are anticorrelated during the fit of the photon-exposed in vitro survival data, different linear-quadratic fits could produce different sets of α and β, thus affecting the RBE calculations. This article reports the combined effect of the α/β ratio and the absolute values α and β on the RBE computed with the Mayo Clinic Florida microdosimetric kinetic model (MCF MKM) for 12C ions of different LET. Furthermore, we introduce a theory-based strategy to potentially mitigate the anticorrelation between α and β during the fit of the photon dose-response biological data.

Clinical dose assessment for scanned carbon-ion radiotherapy using linear energy transfer measurements and Monte Carlo simulations

Objective. Dosimetric commissioning of treatment planning systems (TPS) focuses on validating the agreement of the physical dose with experimental data. For carbon-ion radiotherapy, the commissioning of the relative biological effectiveness (RBE) is necessary to predict the clinical outcome based on the radiation quality of the mixed radiation field. In this study, we proposed a approach for RBE commissioning using Monte Carlo (MC) simulations, which was further strengthen by RBE validation based on linear energy transfer (LET) measurements. Approach. First, we tuned the MC simulation based on the results of dosimetric experiments including the beam ranges, beam sizes, and MU calibrations. Furthermore, we compared simulated results to measured depth- and radial-LET distributions of the 430 MeV u−1 carbon-ion spot beam with a 1.5 mm2, 36 μm thick silicon detector. The measured dose-averaged LET (LETd) and RBE were compared with the simulated results. The RBE was calculated based on the mixed beam model with linear-quadratic parameters depending on the LET. Finally, TPS-calculated clinical dose profiles were validated through the tuned MC-based calculations. Main results. A 10 keV μm−1 and 0.15 agreement for LETd and RBE, respectively, were found between simulation and measurement results obtained for a 2σ lateral size of 430 MeV u−1 carbon-ion spot beam in water. These results suggested that the tuned MC simulation can be used with acceptable precision for the RBE and LET calculations of carbon-ion spot beam within the clinical energy range. For physical and clinical doses, the TPS- and MC-based calculations showed good agreements within 1.0% at the centre of the spread-out Bragg peaks. Significance. The tuned MC simulation can accurately reproduce the actual carbon-ion beams, and it can be used to validate the physical and clinical dose distributions calculated by TPS. Moreover, the MC simulation can be used for dosimetric commissioning, including clinical doses, without LET measurements.

Verification Studies Confirm Reproducibility of Post-Hysterectomy Pelvic Proton Radiotherapy

<h3>Purpose/Objective(s)</h3> Post-hysterectomy radiotherapy (RT) is associated with urinary, gastrointestinal, and hematologic toxicity. Concern for organ and target motion has limited exploration of proton RT as a tool to reduce toxicity. Attention to planning and treatment delivery is paramount given sensitivity of protons to small changes in soft tissue in the beam path. We sought to evaluate the consistency of target coverage and organ at risk (OAR) sparing in post-hysterectomy proton RT. <h3>Materials/Methods</h3> The first 10 patients treated with proton RT on an institutional prospective non-randomized trial of proton post-hysterectomy RT for endometrial cancer were included. CT simulation was performed with pelvic immobilization and a rectal balloon, which was also used for treatment. Full and empty bladder and IV contrast scans were obtained. Clinical target volumes (CTV) included the vaginal cuff, proximal 3 cm of vagina, and pelvic lymph nodes to the level of L4/L5. Prescription was 45 Gy (relative biological effectiveness (RBE) 1.1) in 25 fractions. Planning was multi-field optimization with two posterior oblique beams and a posterior beam. Plans were evaluated for robustness to ensure CTV coverage in worst case scenarios of ±5 mm isocenter shifts in x, y, and z directions and ±5% range uncertainty. A variable RBE calculation assuming a linear relationship between RBE and linear energy transfer was used to evaluate for target coverage and increased RBE within OARs. If needed, the plan was modified to limit hot spots without compromising coverage in the calculation with uniform 1.1 RBE. Patients underwent weekly CT-on-rails verification scans. Target coverage and dose to OARs were assessed at each verification and replanning was done if target coverage or OAR constraints did not meet original planning objectives. <h3>Results</h3> The first patient on the study required replan after first verification due to excess air in the rectum at simulation and verification, resulting in rectum V30Gy 90% and V40Gy 81%. After replan, subsequent verifications met objectives. Subsequent patients were planned with air in the rectum or bowel accounted for by evaluation of plans with air overridden to HU = -300 to -450 and HU = 0. Target coverage met acceptable planning parameters in all cases (Table 1). There was no statistical difference in bladder mean, V30Gy, and V45Gy; sigmoid V45Gy; rectum mean, V30Gy, and V40Gy; and small bowel V40% and V45Gy. All patients were successfully treated with protons for all planned fractions. <h3>Conclusion</h3> Proton post-hysterectomy pelvic RT with robust optimization is feasible, reproducible, and associated with appropriate target coverage and acceptable dose to organs at risk as assessed with weekly verification scans.

The Mayo Clinic Florida Microdosimetric Kinetic Model of Clonogenic Survival: Application to Various Repair-Competent Rodent and Human Cell Lines.

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.

First application of the BIANCA biophysical model to carbon-ion patient cases

Objective. The main objective of this work consists of applying, for the first time, the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model to the RBE calculation for C-ion cancer patients, and comparing the outcomes with those obtained by the LEM I model, which is applied in clinics. Indeed, the continuous development of heavy-ion cancer therapy requires modelling of biological effects of ion beams on tumours and normal tissues. The relative biological effectiveness (RBE) of heavy ions is higher than that of protons, with a significant variation along the beam path. Therefore, it requires a precise modelling, especially for the pencil-beam scanning technique. Currently, two radiobiological models, LEM I and MKM, are in use for heavy ions in scanned pencil-beam facilities. Approach. Utilizing an interface with the FLUKA Particle Therapy Tool, BIANCA was applied to re-calculate the RBE-weighted dose distribution for carbon-ion treatment of three patients (chordoma, head-and-neck and prostate) previously irradiated at CNAO, where radiobiological optimization was based on LEM I. The predictions obtained by BIANCA were based either on chordoma cell survival (RBE surv ), or on dicentric aberrations in peripheral blood lymphocytes (RBE ab ), which are indicators of late normal tissue damage, including secondary tumours. The simulation outcomes were then compared with those provided by LEM I. Main results. While in the target and in the entrance channel BIANCA predictions were lower than those obtained by LEM I, the two models provided very similar results in the considered OAR. The observed differences between RBE surv and RBE ab (which were also dependent on fractional dose and LET) suggest that in normal tissues the information on cell survival should be integrated by information more closely related to the induction of late damage, such as chromosome aberrations. Significance. This work showed that BIANCA is suitable for treatment plan optimization in ion-beam therapy, especially considering that it can predict both cell survival and chromosome aberrations and has previously shown good agreement with carbon-ion experimental data.

Clinical use and future requirements of relative biological effectiveness: Survey among all European proton therapy centres

Background and purposeThe relative biological effectiveness (RBE) varies along the treatment field. However, in clinical practice, a constant RBE of 1.1 is assumed, which can result in undesirable side effects. This study provides an accurate overview of current clinical practice for considering proton RBE in Europe. Materials and methodsA survey was devised and sent to all proton therapy centres in Europe that treat patients. The online questionnaire consisted of 39 questions addressing various aspects of RBE consideration in clinical practice, including treatment planning, patient follow-up and future demands. ResultsAll 25 proton therapy centres responded. All centres prescribed a constant RBE of 1.1, but also applied measures (except for one eye treatment centre) to counteract variable RBE effects such as avoiding beams stopping inside or in front of an organ at risk and putting restrictions on the minimum number and opening angle of incident beams for certain treatment sites. For the future, most centres (16) asked for more retrospective or prospective outcome studies investigating the potential effect of the effect of a variable RBE. To perform such studies, 18 centres asked for LET and RBE calculation and visualisation tools developed by treatment planning system vendors. ConclusionAll European proton centres are aware of RBE variability but comply with current guidelines of prescribing a constant RBE. However, they actively mitigate uncertainty and risk of side effects resulting from increased RBE by applying measures and restrictions during treatment planning. To change RBE-related clinical guidelines in the future more clinical data on RBE are explicitly demanded.

On the calculation of the relative biological effectiveness of ion radiation therapy using a biological weighting function, the microdosimetric kinetic model (MKM) and subsequent corrections (non-Poisson MKM and modified MKM)

Objective. To investigate similarities and differences in the formalism, processing, and the results of relative biological effectiveness (RBE) calculations with a biological weighting function (BWF), the microdosimetric kinetic model (MKM) and subsequent modifications (non-Poisson MKM, modified MKM). This includes: (a) the extension of the V79-RBE10% BWF to model the RBE for other clonogenic survival levels; (b) a novel implementation of MKMs as weighting functions; (c) a benchmark against Chinese Hamster lung fibroblast (V79) in vitro data; (d) a study on the effect of pre- or post- processing the average biophysical quantities used for the RBE calculations; (e) a possible modification of the modified MKM parameters to improve the model accuracy at high linear energy transfer (LET). Methodology. Lineal energy spectra were simulated for two spherical targets (diameter = 0.464 or 1.0 μm) using PHITS for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe and 132Xe ions. The results of the in silico calculations were compared with published in vitro data. Main results. All models appear to underestimate the RBE α of hydrogen ions. All MKMs generally overestimate the RBE50%, RBE10% and RBE1% for ions with an LET greater than ∼200 keV μm−1. This overestimation is greater for small surviving fractions and is likely due to the assumption of a radiation-independent quadratic term of clonogenic survival (ß). The overall RBE trends seem to be best described by the novel ‘post-processing average’ implementation of the non-Poisson MKM. In case of calculations with the non-Poisson MKM, pre- or post- processing the average biophysical quantities affects the computed RBE values significantly. Significance. This study presents a systematic analysis of the formalism and results of widely used microdosimetric models of clonogenic survival for ions relevant for cancer particle therapy and space radiation protection. Points for improvements were highlighted and will contribute to the development of upgraded biophysical models.

Technical note: Impact of beamline-specific particle energy spectra on clinical plans in carbon ion beam therapy.

PurposeThe Local Effect Model version one (LEM I) is applied clinically across Europe to quantify the relative biological effectiveness (RBE) of carbon ion beams. It requires the full particle fluence spectrum differential in energy in each voxel as input parameter. Treatment planning systems (TPSs) use beamline‐specific look‐up tables generated with Monte Carlo (MC) codes. In this study, the changes in RBE weighted dose were quantified using different levels of details in the simulation or different MC codes.MethodsThe particle fluence differential in energy was simulated with FLUKA and Geant4 at 500 depths in water in 1‐mm steps for 58 initial carbon ion energies (between 120.0 and 402.8 MeV/u). A dedicated beam model was applied, including the full description of the Nozzle using GATE‐RTionV1.0 (Geant4.10.03p03). In addition, two tables generated with FLUKA were compared. The starting points of the FLUKA simulations were phase space (PhS) files from, firstly, the Geant4 nozzle simulations, and secondly, a clinical beam model where an analytic approach was used to mimic the beamline. Treatment plans (TPs) were generated with RayStation 8B (RaySearch Laboratories AB, Sweden) for cubic targets in water and 10 clinical patient cases using the clinical beam model. Subsequently, the RBE weighted dose was re‐computed using the two other fluence tables (FLUKA PhS or Geant4).ResultsThe fluence spectra of the primary and secondary particles simulated with Geant4 and FLUKA generally agreed well for the primary particles. Differences were mainly observed for the secondary particles. Interchanging the two energy spectra (FLUKA vs. GEANT4) to calculate the RBE weighted dose distributions resulted in average deviations of less than 1% in the entrance up to the end of the target region, with a maximum local deviation at the distal edge of the target. In the fragment tail, larger discrepancies of up to 5% on average were found for deep‐seated targets. The patient and water phantom cases demonstrated similar results.ConclusionRBE weighted doses agreed well within all tested setups, confirming the clinical beam model provided by the TPS vendor. Furthermore, the results showed that the open source and generally available MC code Geant4 (in particular using GATE or GATE‐RTion) can also be used to generate basic beam data required for RBE calculation in carbon ion therapy.

Handling of beam spectra in training and application of proton RBE models

Published data from cell survival experiments are frequently used as training data for models of proton relative biological effectiveness (RBE). The publications rarely provide full information about the primary particle spectrum of the used beam, or its content of heavy secondary particles. The purpose of this paper is to assess to what extent heavy secondary particles may have been present in published cell survival experiments, and to investigate the impact of non-primary protons for RBE calculations in treatment planning. We used the Monte Carlo code Geant4 to calculate the occurrence of non-primary protons and heavier secondary particles for clinical protons beams in water for four incident energies in the [100, 250] MeV interval. We used the resulting spectra together with a conservative RBE parameterization and an RBE model to map both the rise of RBE at the beam entry surface due to heavy secondary particle buildup, and the difference in estimated RBE if non-primary protons are included or not in the beam quality metric. If included, non-primary protons cause a difference of 2% of the RBE in the plateau region of an spread out Bragg peak and 1% in the Bragg peak. Including non-primary protons specifically for RBE calculations will consequently have a negligible impact and can be ignored. A buildup distance in water of one millimeter was sufficient to reach an equilibrium state of RBE for the four incident energies selected. For the investigated experimental data, 83 out of the 86 data points were found to have been determined with at least that amount of buildup material. Hence, RBE model training data should be interpreted to include the contribution of heavy secondaries.

Evaluating very high energy electron RBE from nanodosimetric pBR322 plasmid DNA damage

This paper presents the first plasmid DNA irradiations carried out with Very High Energy Electrons (VHEE) over 100–200 MeV at the CLEAR user facility at CERN to determine the Relative Biological Effectiveness (RBE) of VHEE. DNA damage yields were measured in dry and aqueous environments to determine that ~ 99% of total DNA breaks were caused by indirect effects, consistent with other published measurements for protons and photons. Double-Strand Break (DSB) yield was used as the biological endpoint for RBE calculation, with values found to be consistent with established radiotherapy modalities. Similarities in physical damage between VHEE and conventional modalities gives confidence that biological effects of VHEE will also be similar—key for clinical implementation. Damage yields were used as a baseline for track structure simulations of VHEE plasmid irradiation using GEANT4-DNA. Current models for DSB yield have shown reasonable agreement with experimental values. The growing interest in FLASH radiotherapy motivated a study into DSB yield variation with dose rate following VHEE irradiation. No significant variations were observed between conventional and FLASH dose rate irradiations, indicating that no FLASH effect is seen under these conditions.

Development of a new microdosimetric biological weighting function for the RBE10 assessment in case of the V79 cell line exposed to ions from 1H to 238U

An improved biological weighting function (IBWF) is proposed to phenomenologically relate microdosimetric lineal energy probability density distributions with the relative biological effectiveness (RBE) for the in vitro clonogenic cell survival (surviving fraction = 10%) of the most commonly used mammalian cell line, i.e. the Chinese hamster lung fibroblasts (V79). The IBWF, intended as a simple and robust tool for a fast RBE assessment to compare different exposure conditions in particle therapy beams, was determined through an iterative global-fitting process aimed to minimize the average relative deviation between RBE calculations and literature in vitro data in case of exposure to various types of ions from 1H to 238U. By using a single particle- and energy- independent function, it was possible to establish an univocal correlation between lineal energy and clonogenic cell survival for particles spanning over an unrestricted linear energy transfer range of almost five orders of magnitude (0.2 keV µm−1 to 15 000 keV µm−1 in liquid water). The average deviation between IBWF-derived RBE values and the published in vitro data was ∼14%. The IBWF results were also compared with corresponding calculations (in vitro RBE10 for the V79 cell line) performed using the modified microdosimetric kinetic model (modified MKM). Furthermore, RBE values computed with the reference biological weighting function (BWF) for the in vivo early intestine tolerance in mice were included for comparison and to further explore potential correlations between the BWF results and the in vitro RBE as reported in previous studies. The results suggest that the modified MKM possess limitations in reproducing the experimental in vitro RBE10 for the V79 cell line in case of ions heavier than 20Ne. Furthermore, due to the different modelled endpoint, marked deviations were found between the RBE values assessed using the reference BWF and the IBWF for ions heavier than 2H. Finally, the IBWF was unchangingly applied to calculate RBE values by processing lineal energy density distributions experimentally measured with eight different microdosimeters in 19 1H and 12C beams at ten different facilities (eight clinical and two research ones). Despite the differences between the detectors, irradiation facilities, beam profiles (pristine or spread out Bragg peak), maximum beam energy, beam delivery (passive or active scanning), energy degradation system (water, PMMA, polyamide or low-density polyethylene), the obtained IBWF-based RBE trends were found to be in good agreement with the corresponding ones in case of computer-simulated microdosimetric spectra (average relative deviation equal to 0.8% and 5.7% for 1H and 12C ions respectively).

Robust radiobiological optimization of ion beam therapy utilizing Monte Carlo and microdosimetric kinetic model

To develop a Monte Carlo (MC)-based and robust ion beam therapy optimization system that separates the optimization algorithm from the relative biological effectiveness (RBE) modeling. Robustly optimized dose distributions were calculated and compared across three ion therapy beams (proton, helium, carbon). The effect of different averaging techniques in calculating RBE in mixed beams was also investigated. Ion particles were transported in TOPAS MC. The microdosimetric-kinetic model (MKM) parameter, saturation corrected specific energy (), was calculated with a customized MKM implementation in TOPAS MC. Intensity modulated ion therapy robust optimization was performed by a quasi-Newton iterative method based on dose-volume objective function. The robust optimization took setup and range uncertainties into account. In the present work, the biological dose for each individual spot was calculated, and then summed together to calculate total biological dose. In other published works, radiosensitive parameters, such as , were first averaged over all beam spots within a mixed-beam field, after which biological dose was calculated using the averaged radiosensitive parameters. The difference between the two mixed-beam biological dose calculations was quantified. Robust plans were achieved with the three particle types. The effect of averaging depended on particle type. The difference between biological doses calculated with individual and averaged may be greater than 3% for a carbon beam. MC based radiobiological and robust optimization was made flexible to incorporate dose-volume histogram constraints and to be independent of RBE models. Iterative optimization with RBE models was feasible. Evaluation of the RBE calculation for mixed beam could be necessary if better accuracy was demanded.

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 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 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.