Benchmarking proton RBE models.

Objective.To biologically optimise proton therapy, models which can accurately predict variations in proton relative biological effectiveness (RBE) are essential. Current phenomenological models show large disagreements in RBE predictions, due to different model assumptions and differences in the data to which they were fit. In this work, thirteen RBE models were benchmarked against a comprehensive proton RBE dataset to evaluate predictions when all models are fit using the same data and fitting techniques, and to assess the statistical robustness of the models.Approach.Model performance was initially evaluated by fitting to the full dataset, and then a cross-validation approach was applied to assess model generalisability and robustness. The impact of weighting the fit and the choice of biological endpoint (either single or multiple survival levels) was also evaluated.Main results.Fitting the models to a common dataset reduced differences between their predictions, however significant disagreements remained due to different underlying assumptions. All models performed poorly under cross-validation in the weighted fits, suggesting that some uncertainties on the experimental data were significantly underestimated, resulting in over-fitting and poor performance on unseen data. The simplest model, which depends linearly on the LET but has no tissue or dose dependence, performed best for a single survival level. However, when fitting to multiple survival levels simultaneously, more complex models with tissue dependence performed better. All models had significant residual uncertainty in their predictions compared to experimental data.Significance.This analysis highlights that poor quality of error estimation on the dose response parameters introduces substantial uncertainty in model fitting. The significant residual error present in all approaches illustrates the challenges inherent in fitting to large, heterogeneous datasets and the importance of robust statistical validation of RBE models.

Targeting OGG1 and PARG radiosensitises head and neck cancer cells to high-LET protons through complex DNA damage persistence.

Complex DNA damage (CDD), containing two or more DNA lesions within one or two DNA helical turns, is a signature of ionising radiation (IR) and contributes significantly to the therapeutic effect through cell killing. The levels and complexity of CDD increases with linear energy transfer (LET), however, the specific cellular response to this type of DNA damage and the critical proteins essential for repair of CDD is currently unclear. We performed an siRNA screen of ~240 DNA damage response proteins to identify those specifically involved in controlling cell survival in response to high-LET protons at the Bragg peak, compared to low-LET entrance dose protons which differ in the amount of CDD produced. From this, we subsequently validated that depletion of 8-oxoguanine DNA glycosylase (OGG1) and poly(ADP-ribose) glycohydrolase (PARG) in HeLa and head and neck cancer cells leads to significantly increased cellular radiosensitivity specifically following high-LET protons, whilst no effect was observed after low-LET protons and X-rays. We subsequently confirmed that OGG1 and PARG are both required for efficient CDD repair post-irradiation with high-LET protons. Importantly, these results were also recapitulated using specific inhibitors for OGG1 (TH5487) and PARG (PDD00017273). Our results suggest OGG1 and PARG play a fundamental role in the cellular response to CDD and indicate that targeting these enzymes could represent a promising therapeutic strategy for the treatment of head and neck cancers following high-LET radiation.

Radium deposition in human brain tissue: A Geant4-DNA Monte Carlo toolkit study.

NASA has encouraged studies on 226Ra deposition in the human brain to investigate the effects of exposure to alpha particles with high linear energy transfer, which could mimic some of the exposure astronauts face during space travel. However, this approach was criticized, noting that radium is a bone-seeker and accumulates in the skull, which means that the radiation dose from alpha particles emitted by 226Ra would be heavily concentrated in areas close to cranial bones rather than uniformly distributed throughout the brain. In the high background radiation areas of Ramsar, Iran, extremely high levels of 226Ra in soil contribute to a large proportion of the inhabitants' radiation exposure. A prospective study on Ramsar residents with a calcium-rich diet was conducted to improve the dose uniformity due to 226Ra throughout the cerebral and cerebellar parenchyma. The study found that exposure of the human brain to alpha particles did not significantly affect working memory but was significantly associated with increased reaction times. This finding is crucial because astronauts on deep space missions may face similar cognitive impairments due to exposure to high charge and energy particles. The current study was aimed to evaluate the validity of the terrestrial model using the Geant4 Monte Carlo toolkit to simulate the interactions of alpha particles and representative cosmic ray particles, acknowledging that these radiation types are only a subset of the complete space radiation environment.

The contribution of high-LET track to DNA damage formation and cell death for Monoenergy and SOBP carbon ion irradiation.

Carbon ion radiotherapy (CIRT) is a heavy ion charge particle therapy with 29 years of prominent use. Despite advantages like high relative biological effectiveness (RBE), improved quality of life, and reduced treatment time, challenges persist, especially regarding heavy nuclear fragments. Our research addresses these challenges in horizontal irradiation, aiming to comprehend Monoenergetic and Spread-Out Bragg peak (SOBP) carbon ion beam trajectories using cell survival analysis and visualizing biological effects through DNA damage (γ-H2AX). This reveals repair-related protein foci near the Bragg peak. CR-39, a plastic nuclear track detector, was explored to understand high-linear energy transfer (LET) tracks and radiation quality near the Bragg peak. Findings unveil high-LET DNA damage signatures through aligned γ-H2AX foci, correlating with LET values in SOBP. CR-39 visualized high-LET particle exposure, indicating comet-type etch-pits at the Bragg peak and suggesting carbon ion fragmentation. Unexpectedly, dot-type etch-pits in irradiated and post-Bragg peak regions indicated high-LET neutron production. This investigation highlights the intricate interplay of carbon ion beams, stressing the importance of understanding LET variations, DNA damage patterns, and undesired secondary exposure.

Investigation on the physical dose filtered by linear energy transfer for treatment plan evaluation in carbon ion therapy.

BACKGROUND: Large tumor size has been reported as a predicting factor for inferior clinical outcome in carbon ion radiotherapy (CIRT). Besides the clinical factors accompanied with such tumors, larger tumors receive typically more low linear energy transfer (LET) contributions than small ones which may be the underlying physical cause. Although dose averaged LET is often used as a single parameter descriptor to quantify the beam quality, there is no evidence that this parameter is the optimal clinical predictor for the complex mixed radiation fields in CIRT. PURPOSE: Purpose of this study was to investigate on a novel dosimetric quantity, namely high-LET-dose ( D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the physical dose filtered based on an LET threshold) as a single parameter estimator to differentiate between carbon ion treatment plans (cTP) with a small and large tumor volume. METHODS: Ten cTPs with a planning target volume, PTV ≥ 500 cm 3 $\mathrm{PTV}\ge {500}\,{{\rm cm}^{3}}$ (large) and nine with a PTV < 500 cm 3 $\mathrm{PTV}<{500}\,{{\rm cm}^{3}}$ (small) were selected for this study. To find a reasonable LET threshold ( L thr $\textrm {L}_{\textrm {thr}}$ ) that results in a significant difference in terms of D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the voxel based normalized high-LET-dose ( D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) distribution in the clinical target volume (CTV) was studied on a subset (12 out of 19 cTPs) for 18 LET thresholds, using standard distribution descriptors (mean, variance and skewness). The classical dose volume histogram concept was used to evaluate the D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ distributions within the target of all 19 cTPs at the before determined L thr $\textrm {L}_{\textrm {thr}}$ . Statistical significance of the difference between the two groups in terms of mean D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ volume histogram parameters was evaluated by means of (two-sided) t-test or Mann-Whitney-U-test. In addition, the minimum target coverage at the above determined L thr $\textrm {L}_{\textrm {thr}}$ was compared and validated against three other thresholds to verify its potential in differentiation between small and large volume tumors. RESULTS: An L thr $\textrm {L}_{\textrm {thr}}$ of approximately 30 keV / µ m ${30}\,{\rm keV/}\umu {\rm m}$ was found to be a reasonable threshold to classify the two groups. At this threshold, the D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ were significantly larger ( p < 0.05 $p<0.05$ ) in small CTVs. For the small tumor group, the near-minimum and median D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ (and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) in the CTV were in average 9.3 ± 1.5 Gy $9.3\pm {1.5}\,{\rm Gy}$ (0.31 ± 0.08) and 13.6 ± 1.6 Gy $13.6\pm {1.6}\,{\rm Gy}$ (0.46 ± 0.06), respectively. For the large tumors, these parameters were 6.6 ± 0.2 Gy $6.6\pm {0.2}\,{\rm Gy}$ (0.20 ± 0.01) and 8.6 ± 0.4 Gy $8.6\pm {0.4}\,{\rm Gy}$ (0.28 ± 0.02). The difference between the two groups in terms of mean near-minimum and median D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ ( D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) was 2.7 Gy (11%) and 5.0 Gy (18%), respectively. CONCLUSIONS: The feasibility of high-LET-dose based evaluation was shown in this study where a lower D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ was found in cTPs with a large tumor size. Further investigation is needed to draw clinical conclusions. The proposed methodology in this work can be utilized for future high-LET-dose based studies.

Incorporating variable RBE in IMPT optimization for ependymoma.

PURPOSE: To study the dosimetric impact of incorporating variable relative biological effectiveness (RBE) of protons in optimizing intensity-modulated proton therapy (IMPT) treatment plans and to compare it with conventional constant RBE optimization and linear energy transfer (LET)-based optimization. METHODS: This study included 10 pediatric ependymoma patients with challenging anatomical features for treatment planning. Four plans were generated for each patient according to different optimization strategies: (1) constant RBE optimization (ConstRBEopt) considering standard-of-care dose requirements; (2) LET optimization (LETopt) using a composite cost function simultaneously optimizing dose-averaged LET (LETd ) and dose; (3) variable RBE optimization (VarRBEopt) using a recent phenomenological RBE model developed by McNamara et al.; and (4) hybrid RBE optimization (hRBEopt) assuming constant RBE for the target and variable RBE for organs at risk. By normalizing each plan to obtain the same target coverage in either constant or variable RBE, we compared dose, LETd , LET-weighted dose, and equivalent uniform dose between the different optimization approaches. RESULTS: We found that the LETopt plans consistently achieved increased LET in tumor targets and similar or decreased LET in critical organs compared to other plans. On average, the VarRBEopt plans achieved lower mean and maximum doses with both constant and variable RBE in the brainstem and spinal cord for all 10 patients. To compensate for the underdosing of targets with 1.1 RBE for the VarRBEopt plans, the hRBEopt plans achieved higher physical dose in targets and reduced mean and especially maximum variable RBE doses compared to the ConstRBEopt and LETopt plans. CONCLUSION: We demonstrated the feasibility of directly incorporating variable RBE models in IMPT optimization. A hybrid RBE optimization strategy showed potential for clinical implementation by maintaining all current dose limits and reducing the incidence of high RBE in critical normal tissues in ependymoma patients.

The dirty and clean dose concept: Towards creating proton therapy treatment plans with a photon-like dose response.

BACKGROUND: Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1. PURPOSE: This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon-like dose response for OAR and, thus, less uncertainties when applying photon-based tolerance doses. METHODS: The concept divides the 1.1-weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon-like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1-weighted dose, variable RBE-weighted dose using the Wedenberg RBE model and dose-average LETd distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives. RESULTS: In the water phantom studies, LET thresholds between 1.5 and 2.5 keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1-weighted dose in the OARs was slightly increased (patient 1: 0.45 Gy(RBE), patient 2: 0.08 Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1-weighted dose in healthy brain tissue was observed (patient 1: 0.81 Gy(RBE), patient 2: 0.53 Gy(RBE)). The variation of NTCP values due to variation of α/ß from 2 to 3 Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp). CONCLUSIONS: The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon-like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon-based tolerance doses for OAR.

Most DNA repair defects do not modify the relationship between relative biological effectiveness and linear energy transfer in CRISPR-edited cells.

BACKGROUND: Cancer is a highly heterogeneous disease, driven by frequent genetic alterations which have significant effects on radiosensitivity. However, radiotherapy for a given cancer type is typically given with a standard dose determined from population-level trials. As a result, a proportion of patients are under- or over-dosed, reducing the clinical benefit of radiotherapy. Biological optimization would not only allow individual dose prescription but also a more efficient allocation of limited resources, such as proton and carbon ion therapy. Proton and ion radiotherapy offer an advantage over photons due to their elevated Relative Biological Effectiveness (RBE) resulting from their elevated Linear Energy Transfer (LET). Despite significant interest in optimizing LET by tailoring radiotherapy plans, RBE's genetic dependence remains unclear. PURPOSE: The aim of this study is to better define the RBE/LET relationship in a panel of cell lines with different defects in DSB repair pathways, but otherwise identical biological features and genetic background to isolate these effects. METHODS: Normal human cells (RPE1), genetically modified to introduce defects in DNA double-strand break (DSB) repair genes, ATM, BRCA1, DCLRE1C, LIG4, PRKDC and TP53, were used to map the RBE-LET relationship. Cell survival was measured with clonogenic assays after exposure to photons, protons (LET 1 and 12 keV/µm) and alpha particles (129 keV/µm). Gene knockout sensitizer enhancement ratio (SER) values were calculated as the ratio of the mean inactivation dose (MID) of wild-type cells to repair-deficient cells, and RBE values were calculated as the ratio of the MID of X-ray and particle irradiated cells. 53BP1 foci were used to quantify radiation-induced DSBs and their repair following irradiation. RESULTS: Deletion of NHEJ genes had the greatest impact on photon sensitivity (ATM-/- SER = 2.0 and Lig4-/- SER = 1.8), with genes associated with HR having smaller effects (BRCA1-/- SER = 1.2). Wild-type cells showed RBEs of 1.1, 1.3, 5.0 for low- and high-LET protons and alpha particles respectively. SERs for different genes were independent of LET, apart from NHEJ knockouts which proved to be markedly hypersensitive across all tested LETs. Due to this hypersensitivity, the impact of high LET was reduced in cell models lacking the NHEJ repair pathway. HR-defective cells had moderately increased sensitivity across all tested LETs, but, notably, the contribution of HR pathway to survival appeared independent of LET. Analysis of 53BP1 foci shows that NHEJ-defective cells had the least DSB repair capacity after low LET exposure, and no visible repair after high LET exposure. HR-defective cells also had slower repair kinetics, but the impact of HR defects is not as severe as NHEJ defects. CONCLUSIONS: DSB repair defects, particularly in NHEJ, conferred significant radiosensitivity across all LETs. This sensitization appeared independent of LET, suggesting that the contribution of different DNA repair pathways to survival does not depend on radiation quality.

Deep learning-based synthetic dose-weighted LET map generation for intensity modulated proton therapy.

The advantage of proton therapy as compared to photon therapy stems from the Bragg peak effect, which allows protons to deposit most of their energy directly at the tumor while sparing healthy tissue. However, even with such benefits, proton therapy does present certain challenges. The biological effectiveness differences between protons and photons are not fully incorporated into clinical treatment planning processes. In current clinical practice, the relative biological effectiveness (RBE) between protons and photons is set as constant 1.1. Numerous studies have suggested that the RBE of protons can exhibit significant variability. Given these findings, there is a substantial interest in refining proton therapy treatment planning to better account for the variable RBE. Dose-average linear energy transfer (LETd) is a key physical parameter for evaluating the RBE of proton therapy and aids in optimizing proton treatment plans. Calculating precise LETddistributions necessitates the use of intricate physical models and the execution of specialized Monte-Carlo simulation software, which is a computationally intensive and time-consuming progress. In response to these challenges, we propose a deep learning based framework designed to predict the LETddistribution map using the dose distribution map. This approach aims to simplify the process and increase the speed of LETdmap generation in clinical settings. The proposed CycleGAN model has demonstrated superior performance over other GAN-based models. The mean absolute error (MAE), peak signal-to-noise ratio and normalized cross correlation of the LETdmaps generated by the proposed method are 0.096 ± 0.019 keVµm-1, 24.203 ± 2.683 dB, and 0.997 ± 0.002, respectively. The MAE of the proposed method in the clinical target volume, bladder, and rectum are 0.193 ± 0.103, 0.277 ± 0.112, and 0.211 ± 0.086 keVµm-1, respectively. The proposed framework has demonstrated the feasibility of generating synthetic LETdmaps from dose maps and has the potential to improve proton therapy planning by providing accurate LETdinformation.

Spectral composition of secondary electrons based on the Kiefer-Straaten ion track structure model.

The major part of energy deposition of ionizing radiation is caused by secondary electrons, independent of the primary radiation type. However, their spatial concentration and their spectral properties strongly depend on the primary radiation type and finally determine the pattern of molecular damage e.g. to biological targets as the DNA, and thus the final effect of the radiation exposure. To describe the physical and to predict the biological consequences of charged ion irradiation, amorphous track structure approaches have proven to be pragmatic and helpful. There, the local dose deposition in the ion track is equated by considering the emission and slowing down of the secondary electrons from the primary particle track. In the present work we exploit the model of Kiefer and Straaten and derive the spectral composition of secondary electrons as function of the distance to the track center. The spectral composition indicates differences to spectra of low linear energy transfer (LET) photon radiation, which we confirm by a comparison with Monte Carlo studies. We demonstrate that the amorphous track structure approach provides a simple tool for evaluating the spectral electron properties within the track structure. Predictions of the LET of electrons across the track structure as well as the electronic dose build-up effect are derived. Implications for biological effects and corresponding predicting models based on amorphous track structure are discussed.

Linear energy transfer (LET) distribution outside small radiotherapy field edges produced by 6 MV X-rays.

In modern radiotherapy with photons, the absorbed dose outside the radiation field is generally investigated. But it is well known that the biological damage depends not only on the absorbed dose but also on LET. This work investigated the dose-average LET (LΔ,D) outside several small radiotherapy fields to provide information that can help for better evaluating the biological effect in organs at risk close to the tumour volume. The electron fluences produced in liquid water by a 6 MV X-rays Varian iX linac were calculated using the EGSnrc Monte Carlo code. With the electron spectra, LΔ,D calculations were made for eight open small square fields and the reference field at water depths of 0.15 cm, 1.35 cm, 9.85 cm and 19.85 cm and several off-axis distances. The variation of LΔ,D from the centre of the beam to 2 cm outside the field's edge depends on the field size and water depth. Using radiobiological data reported in the literature for chromosomal aberrations as an endpoint for the induction of dicentrics determined in Human Lymphocytes, we estimated the maximum low-dose relative biological effectiveness, (RBEM) finding an increase of up to 100% from the centre of the beam to 2 cm from the field's edge.

Effect of Linear Energy Transfer on Cystamine's Radioprotective Activity: A Study Using the Fricke Dosimeter with 6-500 MeV per Nucleon Carbon Ions-Implication for Carbon Ion Hadrontherapy.

(1) Background: Radioprotective agents have garnered considerable interest due to their prospective applications in radiotherapy, public health medicine, and situations of large-scale accidental radiation exposure or impending radiological emergencies. Cystamine, an organic diamino-disulfide compound, is recognized for its radiation-protective and antioxidant properties. This study aims to utilize the aqueous ferrous sulfate (Fricke) dosimeter to measure the free-radical scavenging capabilities of cystamine during irradiation by fast carbon ions. This analysis spans an energy range from 6 to 500 MeV per nucleon, which correlates with "linear energy transfer" (LET) values ranging from approximately 248 keV/µm down to 9.3 keV/µm. (2) Methods: Monte Carlo track chemistry calculations were used to simulate the radiation-induced chemistry of aerated Fricke-cystamine solutions across a broad spectrum of cystamine concentrations, ranging from 10-6 to 1 M. (3) Results: In irradiated Fricke solutions containing cystamine, cystamine is observed to hinder the oxidation of Fe2+ ions, an effect triggered by oxidizing agents from the radiolysis of acidic water, resulting in reduced Fe3+ ion production. Our simulations, conducted both with and without accounting for the multiple ionization of water, confirm cystamine's ability to capture free radicals, highlighting its strong antioxidant properties. Aligning with prior research, our simulations also indicate that the protective and antioxidant efficiency of cystamine diminishes with increasing LET of the radiation. This result can be attributed to the changes in the geometry of the track structures when transitioning from lower to higher LETs. (4) Conclusions: If we can apply these fundamental research findings to biological systems at a physiological pH, the use of cystamine alongside carbon-ion hadrontherapy could present a promising approach to further improve the therapeutic ratio in cancer treatments.

Shoot-through proton FLASH irradiation lowers linear energy transfer in organs at risk for neurological tumors and is robust against density variations.

Objective. The goal of the study was to test the hypothesis that shoot-through FLASH proton beams would lead to lower dose-averaged LET (LETD) values in critical organs, while providing at least equal normal tissue sparing as clinical proton therapy plans.Approach. For five neurological tumor patients, pencil beam scanning (PBS) shoot-through plans were made, using the maximum energy of 227 MeV and assuming a hypothetical FLASH protective factor (FPF) of 1.5. The effect of different FPF ranging from 1.2 to 1.8 on the clinical goals were also considered. LETDwas calculated for the clinical plan and the shoot-through plan, applying a 2 Gy total dose threshold (RayStation 8 A/9B and 9A-IonRPG). Robust evaluation was performed considering density uncertainty (±3% throughout entire volume).Main results.Clinical plans showed large LETDvariations compared to shoot-through plans and the maximum LETDin OAR is 1.2-8 times lower for the latter. Although less conformal, shoot-through plans met the same clinical goals as the clinical plans, for FLASH protection factors above 1.4. The FLASH shoot-through plans were more robust to density uncertainties with a maximum OAR D2%increase of 0.6 Gy versus 5.7 Gy in the clinical plans.Significance.Shoot-through proton FLASH beams avoid uncertainties in LETDdistributions and proton range, provide adequate target coverage, meet planning constraints and are robust to density variations.

A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose.

Objective. While integration of variable relative biological effectiveness (RBE) has not reached full clinical implementation, the importance of having the ability to recalculate proton treatment plans in a flexible, dedicated Monte Carlo (MC) code cannot be understated . Here we provide a step-wise method for calibrating dose from a MC code to a treatment planning system (TPS), to obtain required parameters for calculating linear energy transfer (LET), variable RBE and in general enabling clinical realistic research studies beyond the capabilities of a TPS.Approach. Initially, Pristine Bragg peaks (PBP) were calculated in both the Eclipse TPS and the FLUKA MC code. A rearranged Bortfeld energy-range relation was applied to the initial energy of the beam to fine-tune the range of the MC code at 80% dose level distal to the PBP. The energy spread was adapted by dividing the TPS range by the MC range for dose level 80%-20% distal to the PBP. Density and relative proton stopping power were adjusted by comparing the TPS and MC for different Hounsfield units. To find the relationship of dose per primary particle from the MC to dose per monitor unit in the TPS, integration was applied to the area of the Bragg curve. The calibration was validated for spread-out Bragg peaks (SOBP) in water and patient treatment plans. Following the validation, variable RBE were calculated using established models.Main results.The PBPs ranges were within ±0.3mm threshold, and a maximum of 5.5% difference for the SOBPs was observed. The patient validation showed excellent dose agreement between the TPS and MC, with the greatest differences for the lung tumor patient.Significance. Aprocedure for calibrating a MC code to a TPS was developed and validated. The procedure enables MC-based calculation of dose, LET, variable RBE, advanced (secondary) particle tracking and more from treatment plans.

High-LET charged particles: radiobiology and application for new approaches in radiotherapy.

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.

Variation of the relative biological effectiveness with fractionation in proton therapy: Analysis of prostate cancer response.

BACKGROUND: In treatment planning for proton therapy a constant Relative Biological Effectiveness (RBE) of 1.1 is used, disregarding variations with linear energy transfer, clinical endpoint, or fractionation. PURPOSE: To present a methodology to analyze the variation of RBE with fractionation from clinical data of tumor control probability (TCP) and to apply it to study the response of prostate cancer to proton therapy. METHODS AND MATERIALS: We analyzed the dependence of the RBE on the dose per fraction by using the LQ model and the Poisson TCP formalism. Clinical tumor control probabilities for prostate cancer (low and intermediate risk) treated with photon and proton therapy for conventional fractionation (2 Gy(RBE)×37 fractions), moderate hypofractionation (3 Gy(RBE)×20 fractions) and hypofractionation (7.25 Gy(RBE)×5 fractions) were obtained from the literature and analyzed aiming at obtaining the RBE and its dependence on the dose per fraction. RESULTS: The theoretical analysis of the dependence of the RBE on the dose per fraction showed three distinct regions with RBE monotonically decreasing, increasing or staying constant with the dose per fraction, depending on the change of (α, ß) values between photon and proton irradiation (the equilibrium point being at (αp /ßp ) = (αX /ßX )(αX /αp )). An analysis of the clinical data showed RBE values that decline with increasing dose per fraction: for low risk RBE≈1.124, 1.119, and 1.102 for 1.82 Gy, 2.73 Gy and 6.59 Gy per fraction (physical proton doses), respectively; for intermediate risk RBE≈1.119 and 1.102 for 1.82 Gy and 6.59 Gy per fraction (physical proton doses), respectively. These values are nonetheless very close to the nominal 1.1 value. CONCLUSIONS: In this study, we have presented a methodology to analyze the RBE for different fractionations, and we used it to study clinical data for prostate cancer and evaluate the RBE versus dose per fraction. The analysis shows a monotonically decreasing RBE with increasing dose per fraction, which is expected from the LQ formalism and the changes in (α, ß) values between photon and proton irradiation. However, the calculations in this study have to be considered with care as they may be biased by limitations in the modeling assumptions and/or by the clinical data set used for the analysis.

Energy imparted and ionisation yield at the nanometre scale: results for extended beams.

The metrological problem of interpreting ionisation-based micro- and nanodosimetric measurements in terms of quantities proportional to energy imparted becomes particularly relevant when the sensitive volume (SV) size is in the nanometre range. At these scales, a constant W-value cannot be assumed, and the stochastics of the energy transfer per single collision could play a more important role. This problem was recently analysed by our group by means of track-structure Monte Carlo simulations with the Geant4-DNA code, finding a strong correlation between the energy imparted and ionisation yield also for SV diameters of 1 nm. As the previous study was limited to primary beams of radius zero crossing the sensitive sphere along its diameter, it is the aim of the present work to extend the analysis to beams with a radius larger than the dimensions of the SV, to better assess the role played by secondary electrons.

The LET trilemma: Conflicts between robust target coverage, uniform dose, and dose-averaged LET in carbon therapy.

BACKGROUND: Linear energy transfer (LET) is closely related to the biological effect of ionizing radiation. Increasing the dose-averaged LET (LETd ) within the target volume has been proposed as a means to improve clinical outcome for hypoxic tumors. However, doing so can lead to reduced robustness to range uncertainty. PURPOSE: To quantify the relationship between robust target coverage, target dose uniformity, and LETd , we employ robust optimization using dose-based and LETd -based functions and allow varying amounts of target non-uniformity. METHODS AND MATERIALS: Robust carbon therapy optimization is used to create plans for phantom cases with increasing target sizes (radii 1, 3, and 5 cm). First, the influence of respectively range and setup uncertainty on the LETd in the target is studied. Second, we employ strategies allowing overdosage in the clinical target volume (CTV) or gross tumor volume (GTV), which enable increased LETd in the target. The relationship between robust target coverage and LETd in the target is illustrated by tradeoff curves generated by optimization using varying weights for the LETd -based functions. RESULTS: As the range uncertainty used in the robust optimization increased from 0% to 5%, the near-minimum nominal LETd decreased by 17%-29% (9-21 keV/µm) for the different target sizes. The effect of increasing setup uncertainty was marginal. Allowing 10% overdosage in the CTV enabled 9%-29% (6-12 keV/µm) increased near-minimum worst case LETd for the different target sizes, compared to uniform dose plans. When 10% overdosage was allowed in the GTV only, the increase was 1%-20% (1-8 keV/µm). CONCLUSIONS: There is an inherent conflict between range uncertainty robustness and high LETd in the target, which is aggravated with increasing target size. For large tumors, it is possible to simultaneously achieve two of the three qualities range robustness, uniform dose, and high LETd in the target.

Lethal and mutagenic effects of different LET radiations on Bacillus subtilis spores.

New, useful microorganism resources have been generated by ionizing radiation breeding technology. However, the mutagenic effects of ionizing radiation on microorganisms have not been systematically clarified. For a deeper understanding and characterization of ionizing radiation-induced mutations in microorganisms, we investigated the lethal effects of seven different linear energy transfer (LET) radiations based on the survival fraction (SF) and whole-genome sequencing analysis of the mutagenic effects of a dose resulting in an SF of around 1% in Bacillus subtilis spores. Consequently, the lower LET radiations (gamma [surface LET: 0.2 keV/µm] and 4He2+ [24 keV/µm]) showed low lethality and high mutation frequency (MF), resulting in the major induction of single-base substitutions. Whereas higher LET radiations (12C5+ [156 keV/µm] and 12C6+ [179 keV/µm]) showed high lethality and low MF, resulting in the preferential induction of deletion mutations. In addition, 12C6+ (111) ion beams likely possess characteristics of both low- and high-LET radiations simultaneously. A decrease in the relative biological effectiveness and an evaluation of the inactivation cross section indicated that 20Ne8+ (468 keV/µm) and 40Ar13+ (2214 keV/µm) ion beams had overkill effects. In conclusion, in the mutation breeding of microorganisms, it should be possible to regulate the proportions, types, and frequencies of induced mutations by selecting an ionizing radiation of an appropriate LET in accordance with the intended purpose.