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The repair of DNA double-strand breaks is a crucial yet delicate process which is affected by a multitude of factors. In this study, our goal is to analyse the influence of the linear energy transfer (LET) on the DNA repair kinetics. By utilizing the database of repair of DNA and aggregating the results of 84 experiments, we conduct various model fits to evaluate and compare different hypothesis regarding the effect of LET on the rejoining of DNA ends. Despite the considerable research efforts dedicated to this topic over the past decades, our findings underscore the complexity of the relationship between LET and DNA repair kinetics. This study leverages big data analysis to capture overall trends that single experimental studies might miss, providing a valuable model for understanding how radiation quality impacts DNA damage and subsequent biological effects. Our results highlight the gaps in our current understanding, emphasizing the pressing need for further investigation into this phenomenon.

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BACKGROUND: Ultra high dose rate (UHDR) radiotherapy using ridge filter is a new treatment modality known as conformal FLASH that, when optimized for dose, dose rate (DR), and linear energy transfer (LET), has the potential to reduce damage to healthy tissue without sacrificing tumor killing efficacy via the FLASH effect. PURPOSE: Clinical implementation of conformal FLASH proton therapy has been limited by quality assurance (QA) challenges, which include direct measurement of UHDR and LET. Voxel DR distributions and LET spectra at planning target margins are paramount to the DR/LET-related sparing of organs at risk. We hereby present a methodology to achieve experimental validation of these parameters. METHODS: Dose, DR, and LET were measured for a conformal FLASH treatment plan involving a 250-MeV proton beam and a 3D-printed ridge filter designed to uniformly irradiate a spherical target. We measured dose and DR simultaneously using a 4D multi-layer strip ionization chamber (MLSIC) under UHDR conditions. Additionally, we developed an "under-sample and recover (USRe)" technique for a high-resolution pixelated semiconductor detector, Timepix3, to avoid event pile-up and to correct measured LET at high-proton-flux locations without undesirable beam modifications. Confirmation of these measurements was done using a MatriXX PT detector and by Monte Carlo (MC) simulations. RESULTS: MC conformal FLASH computed doses had gamma passing rates of >95% (3 mm/3% criteria) when compared to MatriXX PT and MLSIC data. At the lateral margin, DR showed average agreement values within 0.3% of simulation at 100 Gy/s and fluctuations ∼10% at 15 Gy/s. LET spectra in the proximal, lateral, and distal margins had Bhattacharyya distances of <1.3%. CONCLUSION: Our measurements with the MLSIC and Timepix3 detectors shown that the DR distributions for UHDR scenarios and LET spectra using USRe are in agreement with simulations. These results demonstrate that the methodology presented here can be used effectively for the experimental validation and QA of FLASH treatment plans.

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OBJECTIVE: The energy deposition of photons and protons differs. It depends on the position in the proton Bragg peak (BP) and the linear energy transfer (LET) leading to a variable relative biological effectiveness (RBE). Here, we investigate LET dependent alterations on metabolic viability and proliferation of sarcoma and endothelium cell lines following proton irradiation in comparison to photon exposure. Approach: Using a multi-step range shifter (MSRS), each column of a 96-well plate was positioned in a different depth along four BP curves with increasing intensities. The high-throughput experimental setup covers dose, LET, and RBE changes seen in a treatment field. Photon irradiation was performed to calculate the RBE along the BP curve. Two biological information out of one experiment were extracted allowing a correlation between metabolic viability and proliferation of the cells. Main results: The metabolic viability and cellular proliferation were column-wise altered showing a depth-dose profile. Endothelium cell viability recovers within 96 h post BP irradiation while sarcoma cell viability remains reduced. Highest RBE values were observed at the BP distal fall-off regarding proliferation of the sarcoma and endothelial cells. Significance: The high-throughput experimental setup introduced here I) covers dose, LET, and RBE changes seen in a treatment field, II) measures short-term effects within 48 h to 96 h post irradiation, and III) can additionally be transferred to various cell types without time consuming experimental adaptations. Traditionally, RBE values are calculated from clonogenic cell survival. Measured RBE profiles strongly depend on physical characteristics such as dose and LET and biological characteristics for example cell type and time point. Metabolic viability and proliferation proofed to be in a similar effect range compared to clonogenic survival results. Based on limited data of combined irradiation with doxorubicin, future experiments will test combined treatment with systemic therapies applied in clinics e.g. cyclin-dependent inhibitors. .

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PURPOSE: This study aims to elucidate the dependence of the flat-panel detector's response on the linear energy transfer (LET) and evaluate the practical viability of employing flat-panel detectors in proton dosimetry applications through LET-dependent correction factors. METHODS: The study assessed the flat-panel detector's response across varying depths using solid water and distinct 100, 150, and 200 MeV proton beams by comparing the flat-panel readings against reference doses measured with an ionization chamber. A Monte Carlo code was used to derive LET values, and an LET-dependent response correction factor was determined based on the ratio of the uncorrected flat-panel dose to the ionization chamber dose. The implications of this under-response correction were validated by applying it to a measurement involving a spread-out Bragg peak (SOBP), followed by a comparative analysis against doses calculated using the Monte Carlo code and MatriXX ONE measurement. RESULTS: The association between LET and the flat-panel detector's under-response displayed a positive correlation that intensified with increasing LET values. Notably, with a 10 keV/µm LET value, the detector's under-response reached 50 %, while the measurement points in the SOBP demonstrated under-response greater than 20 %. However, post-correction, the adjusted flat-panel profile closely aligned with the Monte Carlo profile, yielding a 2-dimensional 3 %/3mm gamma passing rate of 100 % at various verification depths. CONCLUSION: This study successfully defined the link between LET and the responsiveness of flat-panel detectors for proton dosimetric measurements and established a foundational framework for integrating flat-panel detectors in clinical proton dosimetry applications.

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Objective.This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LETd) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETdis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context.Approach.The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (n= 151). The best-performing model was identified and externally validated on patients from a different center (n= 107). LETdpredictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LETdpredictions to derive RBE-weighted doses, using the Wedenberg RBE model.Main results.We found NNs based solely on the planned dose distribution, i.e. without additional usage of CT images, can approximate MC-based LETddistributions. Root mean squared errors (RMSE) for the median LETdwithin the brain, brainstem, CTV, chiasm, lacrimal glands (ipsilateral/contralateral) and optic nerves (ipsilateral/contralateral) were 0.36, 0.87, 0.31, 0.73, 0.68, 1.04, 0.69 and 1.24 keV µm-1, respectively. Although model predictions showed statistically significant differences from MC outputs, these did not result in substantial changes in NTCP predictions, with RMSEs of at most 3.2 percentage points.Significance.The ability of NNs to predict LETdbased solely on planned dose distributions suggests a viable alternative to compute-intensive MC simulations in a variable-RBE setting. This is particularly useful in scenarios where MC simulation data are unavailable, facilitating resource-constrained proton therapy treatment planning, retrospective patient data analysis and further investigations on the variability of proton RBE.

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The measurement of linear energy transfer (LET) is crucial for the evaluation of the radiation effect in heavy ion therapy. As two detectors which are convenient to implant into the phantom, the performance of CR-39 and thermoluminescence detector (TLD) for LET measurement was compared by experiment and simulation in this study. The results confirmed the applicability of both detectors for LET measurements, but also revealed that the CR-39 detector would lead to potential overestimation of dose-averaged LET compared with the simulation by PHITS, while the TLD would have a large uncertainty measuring ions with LET larger than 20 keVµm-1. The results of this study were expected to improve the detection method of LET for therapeutic carbon beam and would finally be benefit to the quality assurance of heavy ion radiotherapy.

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High-linear energy transfer (LET) radiation is a promising alternative to conventional low-LET radiation for therapeutic gain against cancer owing to its ability to induce complex and clustered DNA lesions. However, the development of radiation resistance poses a significant barrier. The potential molecular mechanisms that could confer resistance development are translesion synthesis (TLS), replication gap suppression (RGS) mechanisms, autophagy, epithelial-mesenchymal transition (EMT) activation, release of exosomes, and epigenetic changes. This article will discuss various types of complex clustered DNA damage, their repair mechanisms, mutagenic potential, and the development of radiation resistance strategies. Furthermore, it highlights the importance of careful consideration and patient selection when employing high-LET radiotherapy in clinical settings.

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Heavy-ion beam, a type of ionizing radiation, has been applied to plant breeding as a powerful mutagen and is a promising tool to induce large deletions and chromosomal rearrangements. The effectiveness of heavy-ion irradiation can be explained by linear energy transfer (LET; keV µm-1). Heavy-ion beams with different LET values induce different types and sizes of mutations. It has been suggested that deletion size increases with increasing LET value, and complex chromosomal rearrangements are induced in higher LET radiations. In this study, we mapped heavy-ion beam-induced deletions detected in Arabidopsis mutants to its genome. We revealed that deletion sizes were similar between different LETs (100 to 290 keV µm-1), that their upper limit was affected by the distribution of essential genes, and that the detected chromosomal rearrangements avoid disrupting the essential genes. We also focused on tandemly arrayed genes (TAGs), where two or more homologous genes are adjacent to one another in the genome. Our results suggested that 100 keV µm-1 of LET is enough to disrupt TAGs and that the distribution of essential genes strongly affects the heritability of mutations overlapping them. Our results provide a genomic view of large deletion inductions in the Arabidopsis genome.

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Objective.There is an increasing interest in calculating and measuring linear energy transfer (LET) spectra in particle therapy in order to assess their impact in biological terms. As such, the accuracy of the particle fluence energy spectra becomes paramount. This study focuses on quantifying energy depositions of distinct proton, helium, carbon, and oxygen ion beams using a silicon pixel detector developed at CERN to determine LET spectra in silicon.Approach.While detection systems have been investigated in this pursuit, the scarcity of detectors capable of providing per-ion data with high spatial and temporal resolution remains an issue. This gap is where silicon pixel detector technology steps in, enabling online tracking of single-ion energy deposition. The used detector consisted of a 300µm thick silicon sensor operated in partial depletion.Main results.During post-processing, artifacts in the acquired signals were identified and methods for their corrections were developed. Subsequently, a correlation between measured and Monte Carlo-based simulated energy deposition distributions was performed, relying on a two-step recalibration approach based on linear and saturating exponential models. Despite the observed saturation effects, deviations were confined below 7% across the entire investigated range of track-averaged LET values in silicon from 0.77 keVµm-1to 93.16 keVµm-1.Significance.Simulated and measured mean energy depositions were found to be aligned within 7%, after applying artifact corrections. This extends the range of accessible LET spectra in silicon to clinically relevant values and validates the accuracy and reliability of the measurements. These findings pave the way towards LET-based dosimetry through an approach to translate these measurements to LET spectra in water. This will be addressed in a future study, extending functionality of treatment planning systems into clinical routine, with the potential of providing ion-beam therapy of utmost precision to cancer patients.

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Objective.This study aims to address the limitations of traditional methods for calculating linear energy transfer (LET), a critical component in assessing relative biological effectiveness (RBE). Currently, Monte Carlo (MC) simulation, the gold-standard for accuracy, is resource-intensive and slow for dose optimization, while the speedier analytical approximation has compromised accuracy. Our objective was to prototype a deep-learning-based model for calculating dose-averaged LET (LETd) using patient anatomy and dose-to-water (DW) data, facilitating real-time biological dose evaluation and LET optimization within proton treatment planning systems.Approach. 275 4-field prostate proton Stereotactic Body Radiotherapy plans were analyzed, rendering a total of 1100 fields. Those were randomly split into 880, 110, and 110 fields for training, validation, and testing. A 3D Cascaded UNet model, along with data processing and inference pipelines, was developed to generate patient-specific LETddistributions from CT images and DW. The accuracy of the LETdof the test dataset was evaluated against MC-generated ground truth through voxel-based mean absolute error (MAE) and gamma analysis.Main results.The proposed model accurately inferred LETddistributions for each proton field in the test dataset. A single-field LETdcalculation took around 100 ms with trained models running on a NVidia A100 GPU. The selected model yielded an average MAE of 0.94 ± 0.14 MeV cm-1and a gamma passing rate of 97.4% ± 1.3% when applied to the test dataset, with the largest discrepancy at the edge of fields where the dose gradient was the largest and counting statistics was the lowest.Significance.This study demonstrates that deep-learning-based models can efficiently calculate LETdwith high accuracy as a fast-forward approach. The model shows great potential to be utilized for optimizing the RBE of proton treatment plans. Future efforts will focus on enhancing the model's performance and evaluating its adaptability to different clinical scenarios.

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Objective.This work investigates the use of passive luminescence detectors to determine different types of averaged linear energy transfer (LET-) for the energies relevant to proton therapy. The experimental results are compared to reference values obtained from Monte Carlo simulations.Approach.Optically stimulated luminescence detectors (OSLDs), fluorescent nuclear track detectors (FNTDs), and two different groups of thermoluminescence detectors (TLDs) were irradiated at four different radiation qualities. For each irradiation, the fluence- (LET-f) and dose-averaged LET (LET-d) were determined. For both quantities, two sub-types of averages were calculated, either considering the contributions from primary and secondary protons or from all protons and heavier, charged particles. Both simulated and experimental data were used in combination with a phenomenological model to estimate the relative biological effectiveness (RBE).Main results.All types ofLET-could be assessed with the luminescence detectors. The experimental determination ofLET-fis in agreement with reference data obtained from simulations across all measurement techniques and types of averaging. On the other hand,LET-dcan present challenges as a radiation quality metric to describe the detector response in mixed particle fields. However, excluding secondaries heavier than protons from theLET-dcalculation, as their contribution to the luminescence is suppressed by ionization quenching, leads to equal accuracy betweenLET-fandLET-d. Assessment of RBE through the experimentally determinedLET-dvalues agrees with independently acquired reference values, indicating that the investigated detectors can determineLET-with sufficient accuracy for proton therapy.Significance.OSLDs, TLDs, and FNTDs can be used to determineLET-and RBE in proton therapy. With the capability to determine dose through ionization quenching corrections derived fromLET-, OSLDs and TLDs can simultaneously ascertain dose,LET-, and RBE. This makes passive detectors appealing for measurements in phantoms to facilitate validation of clinical treatment plans or experiments related to proton therapy.

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Background and purpose: Ion beams exhibit an increased relative biological effectiveness (RBE) with respect to photons. This study determined the RBE of oxygen ion beams as a function of linear energy transfer (LET) and dose in the rat spinal cord. Materials and methods: The spinal cord of rats was irradiated at four different positions of a 6 cm spread-out Bragg-peak (LET: 26, 66, 98 and 141 keV/µm) using increasing levels of single and split oxygen ion doses. Dose-response curves were established for the endpoint paresis grade II and based on ED50 (dose at 50 % effect probability), the RBE was determined and compared to model predictions. Results: When LET increased from 26 to 98 keV/µm, ED50 decreased from 17.2 ± 0.3 Gy to 13.5 ± 0.4 Gy for single and from 21.7 ± 0.4 Gy to 15.5 ± 0.5 Gy for split doses, however, at 141 keV/µm, ED50 rose again to 15.8 ± 0.4 Gy and 17.2 ± 0.4 Gy, respectively. As a result, the RBE increased from 1.43 ± 0.05 to 1.82 ± 0.08 (single dose) and from 1.58 ± 0.04 to 2.21 ± 0.08 (split dose), respectively, before declining again to 1.56 ± 0.06 for single and 1.99 ± 0.06 for split doses at the highest LET. Deviations from RBE-predictions were model-dependent. Conclusion: This study established first RBE data for the late reacting central nervous system after single and split doses of oxygen ions. The data was used to validate the RBE-dependence on LET and dose of three RBE-models. This study extends the existing data base for protons, helium and carbon ions and provides important information for future patient treatments with oxygen ions.

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Purpose: This study develop a novel linear energy transfer (LET) optimization method for intensity-modulated proton therapy (IMPT) with minimum monitor unit (MMU) constraint using the alternating direction method of multipliers (ADMM). Material and methods: The novel LET optimization method (ADMM-LET) was proposed with (1) the dose objective and the LET objective as the optimization objective and (2) the non-convex MMU threshold as a constraint condition. ADMM was used to solve the optimization problem. In the ADMM-LET framework, the optimization process entails iteratively solving the dose sub-problem and the LET sub-problem, simultaneously ensuring compliance with the MMU constraint. Three representative cases, including brain, liver, and prostate cancer, were utilized to evaluate the performance of the proposed method. The dose and LET distributions from ADMM-LET were compared to those obtained using the published iterative convex relaxation (ICR-LET) method. Results: The results demonstrate the superiority of ADMM-LET over ICR-LET in terms of LET distribution while achieving a comparable dose distribution. More specifically, for the brain case, the maximum LET (unit: keV/µm) at the optic nerve decreased from 5.45 (ICR-LET) to 1.97 (ADMM-LET). For the liver case, the mean LET (unit: keV/µm) at the clinical target volume increased from 4.98 (ICR-LET) to 5.50 (ADMM-LET). For the prostate case, the mean LET (unit: keV/µm) at the rectum decreased from 2.65 (ICR-LET) to 2.14 (ADMM-LET). Conclusion: This study establishes ADMM-LET as a new approach for LET optimization with the MMU constraint in IMPT, offering potential improvements in treatment outcomes and biological effects.

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Background and Purpose: Nuclear interaction correction (NIC) and trichrome fragment spectra modelling improve relative biological effectiveness-weighted dose (DRBE) and dose-averaged linear energy transfer (LETd) calculation for carbon ions. The effect of those novel approaches on the clinical dose and LET distributions was investigated. Materials and Methods: The effect of the NIC and trichrome algorithm was assessed, creating single beam plans for a virtual water phantom with standard settings and NIC + trichrome corrections. Reference DRBE and LETd distributions were simulated using FLUKA version 2021.2.9. Thirty clinically applied scanned carbon ion treatment plans were recalculated applying NIC, trichrome and NIC + trichrome corrections, using the LEM low dose approximation and compared to clinical plans (base RS). Four treatment sites were analysed: six prostate adenocarcinoma, ten head and neck, nine locally advanced pancreatic adenocarcinoma and five sacral chordoma. The FLUKA and clinical plans were compared in terms of DRBE deviations for D98%, D50%, D2% for the clinical target volume (CTV) and D50% in ring-like dose regions retrieved from isodose curves in base RS plans. Additionally, region-based median LETd deviations and global gamma parameters were evaluated. Results: Dose deviations comparing base RS and evaluation plans were within ± 1% supported by γ-pass rates over 97% for all cases. No significant LETd deviations were reported in the CTV, but significant median LETd deviations were up to 80% for very low dose regions. Conclusion: Our results showed improved accuracy of the predicted DRBE and LETd. Considering clinically relevant constraints, no significant modifications of clinical protocols are expected with the introduction of NIC + trichrome.

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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.

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Objective. Helium, oxygen, and neon ions in addition to carbon ions will be used for hypofractionated multi-ion therapy to maximize the therapeutic effectiveness of charged-particle therapy. To use new ions in cancer treatments based on the dose-fractionation protocols established in carbon-ion therapy, this study examined the cell-line-specific radioresponse to therapeutic helium-, oxygen-, and neon-ion beams within wide dose ranges.Approach. Response of cells to ions was described by the stochastic microdosimetric kinetic model. First, simulations were made for the irradiation of one-field spread-out Bragg peak beams in water with helium, carbon, oxygen, and neon ions to achieve uniform survival fractions at 37%, 10%, and 1% for human salivary gland tumor (HSG) cells, the reference cell line for the Japanese relative biological effectiveness weighted dose system, within the target region defined at depths from 90 to 150 mm. The HSG cells were then replaced by other cell lines with different radioresponses to evaluate differences in the biological dose distributions of each ion beam with respect to those of carbon-ion beams.Main results. For oxygen- and neon-ion beams, the biological dose distributions within the target region were almost equivalent to those of carbon-ion beams, differing by less than 5% in most cases. In contrast, for helium-ion beams, the biological dose distributions within the target region were largely different from those of carbon-ion beams, more than 10% in several cases.Significance.From the standpoint of tumor control evaluated by the clonogenic cell survival, this study suggests that the dose-fractionation protocols established in carbon-ion therapy could be reasonably applied to oxygen- and neon-ion beams while some modifications in dose prescription would be needed when the protocols are applied to helium-ion beams. This study bridges the gap between carbon-ion therapy and hypofractionated multi-ion therapy.

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BACKGROUND: Predicting biological responses to mixed radiation types is of considerable importance when combining radiation therapies that use multiple radiation types and delivery regimens. These may include the use of both low- and high-linear energy transfer (LET) radiations. A number of theoretical models have been developed to address this issue. However, model predictions do not consistently match published experimental data for mixed radiation exposures. Furthermore, the models are often computationally intensive. Accordingly, there is a need for efficient analytical models that can predict responses to mixtures of low- and high-LET radiations. Additionally, a general formalism to calculate equieffective dose (EQDX) for mixed radiations is needed. PURPOSE: To develop a computationally efficient analytical model that can predict responses to complex mixtures of low- and high-LET radiations as a function of either absorbed dose or EQDX. METHODS: The Zaider-Rossi model (ZRM) was modified by replacing the geometric mean of the quadratic coefficients in the interaction term with the arithmetic mean. This modified ZRM model (mZRM) was then further generalized to any number of radiation types and its validity was tested against published experimental observations. Comparisons between the predictions of the ZRM and mZRM, and other models, were made using two and three radiation types. In addition, a generalized formalism for calculating EQDX for mixed radiations was developed within the context of mZRM and validated with published experimental results. RESULTS: The predictions of biological responses to mixed-LET radiations calculated with the mZRM are in better agreement with experimental observations than ZRM, especially when high- and low-LET radiations are mixed. In these situations, the ZRM overestimated the surviving fraction. Furthermore, the EQDX calculated with mZRM are in better agreement with experimental observations. CONCLUSION: The mZRM is a computationally efficient model that can be used to predict biological response to mixed radiations that have low- and high-LET characteristics. Importantly, interaction terms are retained in the calculation of EQDX for mixed radiation exposures within the mZRM framework. The mZRM has application in a wide range of radiation therapies, including radiopharmaceutical therapy.

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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.

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(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.

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