Dose and DNA damage modelling of diffusing alpha-emitters radiation therapy using Geant4.

PURPOSE: Diffusing alpha-emitters radiation therapy (DaRT) is a brachytherapy technique using α-particles to treat solid tumours. The high linear energy transfer (LET) and short range of α-particles make them good candidates for the targeted treatment of cancer. Treatment planning of DaRT requires a good understanding of the dose from α-particles and the other particles released in the 224Ra decay chain. METHODS: The Geant4 Monte Carlo toolkit has been used to simulate a DaRT seed to better understand the dose contribution from all particles and simulate the DNA damage due to this treatment. RESULTS: Close to the seed α-particles deliver the majority of dose, however at radial distances greater than 4 mm, the contribution of ß-particles is greater. The RBE has been estimated as a function of number of double strand breaks (DSBs) and complex DSBs. A maximum seed spacing of 5.5 mm and 6.5 mm was found to deliver at least 20 Gy RBE weighted dose between the seeds for RBEDSB and RBEcDSB respectively. CONCLUSIONS: The DNA damage changes with radial distance from the seed and has been found to become less complex with distance, which is potentially easier for the cell to repair. Close to the seed α-particles contribute the majority of dose, however the contribution from other particles cannot be neglected and may influence the choice of seed spacing.

RadPhysBio: A Radiobiological Database for the Prediction of Cell Survival upon Exposure to Ionizing Radiation.

Based on the need for radiobiological databases, in this work, we mined experimental ionizing radiation data of human cells treated with X-rays, γ-rays, carbon ions, protons and α-particles, by manually searching the relevant literature in PubMed from 1980 until 2024. In order to calculate normal and tumor cell survival α and ß coefficients of the linear quadratic (LQ) established model, as well as the initial values of the double-strand breaks (DSBs) in DNA, we used WebPlotDigitizer and Python programming language. We also produced complex DNA damage results through the fast Monte Carlo code MCDS in order to complete any missing data. The calculated α/ß values are in good agreement with those valued reported in the literature, where α shows a relatively good association with linear energy transfer (LET), but not ß. In general, a positive correlation between DSBs and LET was observed as far as the experimental values are concerned. Furthermore, we developed a biophysical prediction model by using machine learning, which showed a good performance for α, while it underscored LET as the most important feature for its prediction. In this study, we designed and developed the novel radiobiological 'RadPhysBio' database for the prediction of irradiated cell survival (α and ß coefficients of the LQ model). The incorporation of machine learning and repair models increases the applicability of our results and the spectrum of potential users.

A perspective on tumor radiation resistance following high-LET radiation treatment.

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.

NF-κB in the Radiation Response of A549 Non-Small Cell Lung Cancer Cells to X-rays and Carbon Ions under Hypoxia.

Cellular hypoxia, detectable in up to 80% of non-small cell lung carcinoma (NSCLC) tumors, is a known cause of radioresistance. High linear energy transfer (LET) particle radiation might be effective in the treatment of hypoxic solid tumors, including NSCLC. Cellular hypoxia can activate nuclear factor κB (NF-κB), which can modulate radioresistance by influencing cancer cell survival. The effect of high-LET radiation on NF-κB activation in hypoxic NSCLC cells is unclear. Therefore, we compared the effect of low (X-rays)- and high (12C)-LET radiation on NF-κB responsive genes' upregulation, as well as its target cytokines' synthesis in normoxic and hypoxic A549 NSCLC cells. The cells were incubated under normoxia (20% O2) or hypoxia (1% O2) for 48 h, followed by irradiation with 8 Gy X-rays or 12C ions, maintaining the oxygen conditions until fixation or lysis. Regulation of NF-κB responsive genes was evaluated by mRNA sequencing. Secretion of NF-κB target cytokines, IL-6 and IL-8, was quantified by ELISA. A greater fold change increase in expression of NF-κB target genes in A549 cells following exposure to 12C ions compared to X-rays was observed, regardless of oxygenation status. These genes regulate cell migration, cell cycle, and cell survival. A greater number of NF-κB target genes was activated under hypoxia, regardless of irradiation status. These genes regulate cell migration, survival, proliferation, and inflammation. X-ray exposure under hypoxia additionally upregulated NF-κB target genes modulating immunosurveillance and epithelial-mesenchymal transition (EMT). Increased IL-6 and IL-8 secretion under hypoxia confirmed NF-κB-mediated expression of pro-inflammatory genes. Therefore, radiotherapy, particularly with X-rays, may increase tumor invasiveness in surviving hypoxic A549 cells.

Robustness of carbon-ion radiotherapy against DNA damage repair associated radiosensitivity variation based on a biophysical model.

BACKGROUND: Interpatient variation of tumor radiosensitivity is rarely considered during the treatment planning process despite its known significance for the therapeutic outcome. PURPOSE: To apply our mechanistic biophysical model to investigate the biological robustness of carbon ion radiotherapy (CIRT) against DNA damage repair interference (DDRi) associated patient-to-patient variability in radiosensitivity and its potential clinical advantages against conventional radiotherapy approaches. METHODS AND MATERIALS: The "UNIfied and VERSatile bio response Engine" (UNIVERSE) was extended by carbon ions and its predictions were compared to a panel of in vitro and in vivo data including various endpoints and DDRi settings within clinically relevant dose and linear energy transfer (LET) ranges. The implications of UNIVERSE predictions were then assessed in a clinical patient scenario considering DDRi variance. RESULTS: UNIVERSE tests well against the applied benchmarks. While in vitro survival curves were predicted with an R2 > 0.92, deviations from in vivo RBE data were less than 5.6% The conducted paradigmatic patient plan study implies a markedly reduced significance of DDRi based radiosensitivity variability in CIRT (13% change of D 50 ${{D}_{50}}$ in target) compared to conventional radiotherapy (62%) and that boosting the LET within the target further amplifies this robustness of CIRT (8%). In the case of heightened tumor radiosensitivity, a dose de-escalation strategy for photons allows a reduction of the maximum effective dose within the normal tissue (NT) from a D 2 ${{D}_2}$ of 2.65 to 1.64 Gy, which lies below the level found for CIRT ( D 2 ${{D}_2}$  = 2.41 Gy) for the analyzed plan and parameters. However, even after de-escalation, the integral effective dose in the NT is found to be substantially higher for conventional radiotherapy in comparison to CIRT ( D m e a n ${{D}_{mean}}$ of 0.75, 0.46, and 0.24 Gy for the conventional plan, its de-escalation and CIRT, respectively). CONCLUSIONS: The framework offers adequate predictions of in vitro and in vivo radiation effects of CIRT while allowing the consideration of DRRi based solely on parameters derived from photon data. The results of the patient planning study underline the potential of CIRT to minimize important sources of interpatient divergence in therapy outcome, especially when combined with techniques that allow to maximize the LET within the tumor. Despite the potential of de-escalation strategies for conventional radiotherapy to reduce the maximum effective dose in the NT, CIRT appears to remain a more favorable option due to its ability to reduce the integral effective dose within the NT.

Health Effects of Ionizing Radiation on the Human Body.

Radioactivity is a process in which the nuclei of unstable atoms spontaneously decay, producing other nuclei and releasing energy in the form of ionizing radiation in the form of alpha (α) and beta (ß) particles as well as the emission of gamma (γ) electromagnetic waves. People may be exposed to radiation in various forms, as casualties of nuclear accidents, workers in power plants, or while working and using different radiation sources in medicine and health care. Acute radiation syndrome (ARS) occurs in subjects exposed to a very high dose of radiation in a very short period of time. Each form of radiation has a unique pathophysiological effect. Unfortunately, higher organisms-human beings-in the course of evolution have not acquired receptors for the direct "capture" of radiation energy, which is transferred at the level of DNA, cells, tissues, and organs. Radiation in biological systems depends on the amount of absorbed energy and its spatial distribution, particularly depending on the linear energy transfer (LET). Photon radiation with low LET leads to homogeneous energy deposition in the entire tissue volume. On the other hand, radiation with a high LET produces a fast Bragg peak, which generates a low input dose, whereby the penetration depth into the tissue increases with the radiation energy. The consequences are mutations, apoptosis, the development of cancer, and cell death. The most sensitive cells are those that divide intensively-bone marrow cells, digestive tract cells, reproductive cells, and skin cells. The health care system and the public should raise awareness of the consequences of ionizing radiation. Therefore, our aim is to identify the consequences of ARS taking into account radiation damage to the respiratory system, nervous system, hematopoietic system, gastrointestinal tract, and skin.

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.

Dose-averaged LET optimized carbon-ion radiotherapy for head and neck cancers.

This feasibility study confirmed the initial safety and efficacy of a novel carbon-ion radiotherapy (CIRT) using linear energy transfer (LET) painting for head and neck cancer. This study is the first step toward establishing CIRT with LET painting in clinical practice and making it a standard practice in the future.

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.

Induction of Chromosomal Aberrations after Exposure to the Auger Electron Emitter Iodine-125, the ß--emitter Tritium and Cesium-137 γ rays.

High-LET-type cell survival curves have been observed in cells that were allowed to incorporate 125I-UdR into their DNA. Incorporation of tritiated thymidine into the DNA of cells has also been shown to result in an increase in relative biological effectiveness in cell survival experiments, but the increase is smaller than observed after incorporation of 125I-UdR. These findings are explained in the literature by the overall complexity of the induced DNA damage resulting from energies of the ejected electron(s) during the decay of 3H and 125I. Chromosomal aberrations (CA) are defined as morphological or structural changes of one or more chromosomes, and can be induced by ionizing radiation. Whether the number of CA is associated with the linear energy transfer (LET) of the radiation and/or the actual complexity of the induced DNA double-strand breaks (DSB) remains elusive. In this study, we investigated whether DNA lesions induced at different cell cycle stages and by different radiation types [Auger-electrons (125I), ß- particles (3H), or γ radiation (137Cs)] have an impact on the number of CA induced after induction of the same number of DSB as determined by the γ-H2AX foci assay. Cells were synchronized and pulse-labeled in S phase with low activities of 125I-UdR or tritiated thymidine. For decay accumulation, cells were cryopreserved either after pulse-labeling in S phase or after progression to G2/M or G1 phase. Experiments with γ irradiation (137Cs) were performed with synchronized and cryopreserved cells in S, G2/M or G1 phase. After thawing, a CA assay was performed. All experiments were performed after a similar number of DSB were induced. CA induction after 125I-UdR was incorporated was 2.9-fold and 1.7-fold greater compared to exposure to γ radiation and radiation from incorporated tritiated thymidine, respectively, when measured in G2/M cells. In addition, measurement of CA in G2/M cells after incorporation of 125I-UdR was 2.5-fold greater when compared to cells in G1 phase. In contrast, no differences were observed between the three radiation qualities with respect to exposure after cryopreservation in S or G1 phase. The data indicate that the 3D organization of replicated DNA in G2/M cells seems to be more sensitive to induction of more complex DNA lesions compared to the DNA architecture in S or G1 cells. Whether this is due to the DNA organization itself or differences in DNA repair capability remains unclear.

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.

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.

A linear energy transfer distributions computation method for inhomogeneous medium by using the water equivalent ratio approximation.

Dose-averaged linear energy transfer (LET), LETd is widely used in proton therapy. Compared with analytical models, Monte Carlo (MC) simulations are more accurate in obtaining LETd distributions, but they are time-consuming. This study used the 3D LETd distributions of proton beam spots in water by MC simulations as a benchmark data set. Subsequently, by combining the water equivalent ratio of various human tissues, the 3D LETd distributions of clinical cases could be quickly obtained. Our method was applied to a single spot of 160 MeV proton beam in a water-bone phantom and a pelvic case. We also computed the 3D LETd distributions for multiple proton beam spots in the pelvic case and a lung case. The results of our method were compared with the results of MC simulations, demonstrating that our method can rapidly provide 3D LETd distributions of clinical cases with acceptable differences from MC simulations.

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.

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.

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.