Exploring the LET dependence of DNA DSB repair kinetics using the DR DNA database.

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.

Enhanced IDOL segmentation framework using personalized hyperspace learning IDOL.

BACKGROUND: Adaptive radiotherapy (ART) workflows have been increasingly adopted to achieve dose escalation and tissue sparing under shifting anatomic conditions, but the necessity of recontouring and the associated time burden hinders a real-time or online ART workflow. In response to this challenge, approaches to auto-segmentation involving deformable image registration, atlas-based segmentation, and deep learning-based segmentation (DLS) have been developed. Despite the particular promise shown by DLS methods, implementing these approaches in a clinical setting remains a challenge, namely due to the difficulty of curating a data set of sufficient size and quality so as to achieve generalizability in a trained model. PURPOSE: To address this challenge, we have developed an intentional deep overfit learning (IDOL) framework tailored to the auto-segmentation task. However, certain limitations were identified, particularly the insufficiency of the personalized dataset to effectively overfit the model. In this study, we introduce a personalized hyperspace learning (PHL)-IDOL segmentation framework capable of generating datasets that induce the model to overfit specific patient characteristics for medical image segmentation. METHODS: The PHL-IDOL model is trained in two stages. In the first, a conventional, general model is trained with a diverse set of patient data (n = 100 patients) consisting of CT images and clinical contours. Following this, the general model is tuned with a data set consisting of two components: (a) selection of a subset of the patient data (m < n) using the similarity metrics (mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and the universal quality image index (UQI) values); (b) adjust the CT and the clinical contours using a deformed vector generated from the reference patient and the selected patients using (a). After training, the general model, the continual model, the conventional IDOL model, and the proposed PHL-IDOL model were evaluated using the volumetric dice similarity coefficient (VDSC) and the Hausdorff distance 95% (HD95%) computed for 18 structures in 20 test patients. RESULTS: Implementing the PHL-IDOL framework resulted in improved segmentation performance for each patient. The Dice scores increased from 0.81 ± $ \pm $ 0.05 with the general model, 0.83 ± 0.04 $ \pm 0.04$ for the continual model, 0.83 ± 0.04 $ \pm 0.04$ for the conventional IDOL model to an average of 0.87 ± 0.03 $ \pm 0.03$ with the PHL-IDOL model. Similarly, the Hausdorff distance decreased from 3.06 ± 0.99 $ \pm 0.99$ with the general model, 2.84 ± 0.69 $ \pm 0.69$ for the continual model, 2.79 ± 0.79 $ \pm 0.79$ for the conventional IDOL model and 2.36 ± 0.52 $ \pm 0.52$ for the PHL-IDOL model. All the standard deviations were decreased by nearly half of the values comparing the general model and the PHL-IDOL model. CONCLUSION: The PHL-IDOL framework applied to the auto-segmentation task achieves improved performance compared to the general DLS approach, demonstrating the promise of leveraging patient-specific prior information in a task central to online ART workflows.

LET-based approximation of the microdosimetric kinetic model for proton radiotherapy.

BACKGROUND: Phenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose-averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory-based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry-based models in LET-based proton therapy treatment planning systems poses challenges. PURPOSE: This work presents a LET-based version of the MKM that is practical for clinical use in proton radiotherapy. METHODS: At first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively-sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons. RESULTS: A simple allometric function was found able to describe the relationship between the dose-averaged LET of protons and the dose-mean lineal energy, which includes the contributions of secondary particles. The LET-based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread-out Bragg peak (SOBP) proton beams. The results of the LET-based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed. CONCLUSIONS: The LET-based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose-averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.

Radiation-induced DNA double-strand breaks in cortisol exposed fibroblasts as quantified with the novel foci-integrated damage complexity score (FIDCS).

Without the protective shielding of Earth's atmosphere, astronauts face higher doses of ionizing radiation in space, causing serious health concerns. Highly charged and high energy (HZE) particles are particularly effective in causing complex and difficult-to-repair DNA double-strand breaks compared to low linear energy transfer. Additionally, chronic cortisol exposure during spaceflight raises further concerns, although its specific impact on DNA damage and repair remains unknown. This study explorers the effect of different radiation qualities (photons, protons, carbon, and iron ions) on the DNA damage and repair of cortisol-conditioned primary human dermal fibroblasts. Besides, we introduce a new measure, the Foci-Integrated Damage Complexity Score (FIDCS), to assess DNA damage complexity by analyzing focus area and fluorescent intensity. Our results show that the FIDCS captured the DNA damage induced by different radiation qualities better than counting the number of foci, as traditionally done. Besides, using this measure, we were able to identify differences in DNA damage between cortisol-exposed cells and controls. This suggests that, besides measuring the total number of foci, considering the complexity of the DNA damage by means of the FIDCS can provide additional and, in our case, improved information when comparing different radiation qualities.

Assessment of fluence- and dose-averaged linear energy transfer with passive luminescence detectors in clinical proton beams.

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.

Variation of the relative biological effectiveness in the penumbra of ion therapy beams estimated using different microdosimetric approaches.

Background and Purpose: The effort to translate clinical findings across institutions employing different relative biological effectiveness (RBE) models of ion radiotherapy has rapidly grown in recent years. Nevertheless, even for a chosen RBE model, different implementations exist. These approaches might consider or disregard the dose-dependence of the RBE and the radial variation of the radiation quality around the beam axis. This study investigated the theoretical impact of disregarding these effects during the RBE calculations. Materials and Methods: Microdosimetric simulations were carried out using the Monte Carlo code PHITS along the spread out Bragg peaks of 1H, 4He, 12C, 16O, and 20Ne ions in a water phantom. The RBE was computed using different implementations of the Mayo Clinic Florida microdosimetric kinetic model (MCF MKM) and the modified MKM, considering or not the radial variation of the radiation quality in the penumbra of the ion beams and the dose-dependence of the RBE. Results: For an OAR located 5 mm laterally from the target volume, disregarding the radial variation of the radiation quality or the dose-dependence of the RBE could result in an overestimation of the RBE-weighted dose up to a factor of âˆ¼ 3.5 or âˆ¼ 1.7, respectively. Conclusions: The RBE-weighted dose to OARs close to the tumor volume was substantially impacted by the approach employed for the RBE calculations, even when using the same RBE model and cell line. Therefore, care should be taken in considering these differences while translating clinical findings between institutions with dissimilar approaches.

DNA Double-Strand Break Repair Kinetics after Exposure to Photons and Ions: A Systematic Review.

This study offers a review of published data on DNA double strand break (DSB) repair kinetics after exposure to ionizing radiation. By compiling a database, which currently includes 285 DNA DSB repair experiments utilizing both photons and ions, we investigate the impact of distinct experimental parameters on the kinetics of DNA DSB repair. Methodological differences and inconsistencies in reporting make the comparison of data generated by different research groups challenging. Nevertheless, by implementing filtering criteria, we can compare repair kinetics obtained with normal and tumor cells derived from human or animal tissues, as well as cells exposed to photons or ions ranging from hydrogen to iron ions. In addition, several repair curves of repair deficient cell lines were included. The study aims to provide researchers with a comprehensive overview of experimental factors that may confound results and emphasize the importance of precise reporting of experimental parameters. Moreover, we identify gaps in the literature that require attention in future studies, aiming to address clinically relevant questions related to radiotherapy. The database can be freely accessed at: https://github.com/weradstake/DRDNA.

Lost in Space? Unmasking the T Cell Reaction to Simulated Space Stressors.

The space environment will expose astronauts to stressors like ionizing radiation, altered gravity fields and elevated cortisol levels, which pose a health risk. Understanding how the interplay between these stressors changes T cells' response is important to better characterize space-related immune dysfunction. We have exposed stimulated Jurkat cells to simulated space stressors (1 Gy, carbon ions/1 Gy photons, 1 µM hydrocortisone (HC), Mars, moon, and microgravity) in a single or combined manner. Pro-inflammatory cytokine IL-2 was measured in the supernatant of Jurkat cells and at the mRNA level. Results show that alone, HC, Mars gravity and microgravity significantly decrease IL-2 presence in the supernatant. 1 Gy carbon ion irradiation showed a smaller impact on IL-2 levels than photon irradiation. Combining exposure to different simulated space stressors seems to have less immunosuppressive effects. Gene expression was less impacted at the time-point collected. These findings showcase a complex T cell response to different conditions and suggest the importance of elevated cortisol levels in the context of space flight, also highlighting the need to use simulated partial gravity technologies to better understand the immune system's response to the space environment.

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

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

The effect of fitting the reference photon dose-response on the clonogenic survival predicted with the Mayo Clinic Florida microdosimetric kinetic model in case of accelerated ions.

The Mayo Clinic Florida microdosimetric kinetic model (MCF MKM) is a recently developed clonogenic survival model. Since the MCF MKM relies on novel strategies to a priori determine the cell-specific model parameters, the only experiment-specific input values are the α and ß terms of the linear-quadratic model (LQM) of clonogenic survival for the reference photon exposure. Because the two LQM terms are anti-correlated, the fitting process of the reference photon survival curve was found to significantly influence the MCF MKM calculations. This article reports this effect for two clinically relevant cell lines (human brain glioblastoma A-172, human healthy foreskin fibroblasts AG01522) and ions (1H and 12C ions).

A high-resolution cone beam computed tomography (HRCBCT) reconstruction framework for CBCT-guided online adaptive therapy.

BACKGROUND: Kilo-voltage cone-beam computed tomography (CBCT) is a prevalent modality used for adaptive radiotherapy (ART) due to its compatibility with linear accelerators and ability to provide online imaging. However, the widely-used Feldkamp-Davis-Kress (FDK) reconstruction algorithm has several limitations, including potential streak aliasing artifacts and elevated noise levels. Iterative reconstruction (IR) techniques, such as total variation (TV) minimization, dictionary-based methods, and prior information-based methods, have emerged as viable solutions to address these limitations and improve the quality and applicability of CBCT in ART. PURPOSE: One of the primary challenges in IR-based techniques is finding the right balance between minimizing image noise and preserving image resolution. To overcome this challenge, we have developed a new reconstruction technique called high-resolution CBCT (HRCBCT) that specifically focuses on improving image resolution while reducing noise levels. METHODS: The HRCBCT reconstruction technique builds upon the conventional IR approach, incorporating three components: the data fidelity term, the resolution preservation term, and the regularization term. The data fidelity term ensures alignment between reconstructed values and measured projection data, while the resolution preservation term exploits the high resolution of the initial Feldkamp-Davis-Kress (FDK) algorithm. The regularization term mitigates noise during the IR process. To enhance convergence and resolution at each iterative stage, we applied Iterative Filtered Backprojection (IFBP) to the data fidelity minimization process. RESULTS: We evaluated the performance of the proposed HRCBCT algorithm using data from two physical phantoms and one head and neck patient. The HRCBCT algorithm outperformed all four different algorithms; FDK, Iterative Filtered Back Projection (IFBP), Compressed Sensing based Iterative Reconstruction (CSIR), and Prior Image Constrained Compressed Sensing (PICCS) methods in terms of resolution and noise reduction for all data sets. Line profiles across three line pairs of resolution revealed that the HRCBCT algorithm delivered the highest distinguishable line pairs compared to the other algorithms. Similarly, the Modulation Transfer Function (MTF) measurements, obtained from the tungsten wire insert on the CatPhan 600 physical phantom, showed a significant improvement with HRCBCT over traditional algorithms. CONCLUSION: The proposed HRCBCT algorithm offers a promising solution for enhancing CBCT image quality in adaptive radiotherapy settings. By addressing the challenges inherent in traditional IR methods, the algorithm delivers high-definition CBCT images with improved resolution and reduced noise throughout each iterative step. Implementing the HR CBCT algorithm could significantly impact the accuracy of treatment planning during online adaptive therapy.

Improvement of the hybrid approach between Monte Carlo simulation and analytical function for calculating microdosimetric probability densities in macroscopic matter.

Objective. Estimation of the probability density of the microdosimetric quantities in macroscopic matter is indispensable for applying the concept of microdosimetry to medical physics and radiological protection. The Particle and Heavy Ion Transport code System (PHITS) enables estimating the microdosimetric probability densities due to its unique hybrid modality between the Monte Carlo and analytical approaches called the microdosimetric function. It can convert the deposition energies calculated by the macroscopic Monte Carlo radiation transport simulation to microdosimetric probability densities in water using an analytical function based on the track-structure simulations.Approach. In this study, we improved this function using the latest track-structure simulation codes implemented in PHITS. The improved function is capable of calculating the probability densities of not only the conventional microdosimetric quantities such as lineal energy but also the number of ionization events occurring in a target site, the so-called ionization cluster size distribution, for arbitrary site diameters from 3 nm to 1µm.Main results. The accuracy of the improved function was well verified by comparing the microdosimetric probability densities measured by tissue-equivalent proportional counters with the corresponding data calculated in this study. Test calculations for clonogenic cell survival using the improved function coupled with the modified microdosimetric kinetic model suggested a slight increase of its relative biological effectiveness compared with our previous estimations. As a new application of the improved function, we calculated the relative biological effectiveness of the single-strand break and double-strand break yields for proton irradiations using the updated PHITS coupled with the simplified DNA damage estimation model, and confirmed its equivalence in accuracy and its superiority in computational time compared to our previously proposed method based on the track-structure simulation.Significance. From these features, we concluded that the improved function could expand the application fields of PHITS by bridging the gap between microdosimetry and macrodosimetry.

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

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

The Effects of Combined Exposure to Simulated Microgravity, Ionizing Radiation, and Cortisol on the In Vitro Wound Healing Process.

Human spaceflight is associated with several health-related issues as a result of long-term exposure to microgravity, ionizing radiation, and higher levels of psychological stress. Frequent reported skin problems in space include rashes, itches, and a delayed wound healing. Access to space is restricted by financial and logistical issues; as a consequence, experimental sample sizes are often small, which limits the generalization of the results. Earth-based simulation models can be used to investigate cellular responses as a result of exposure to certain spaceflight stressors. Here, we describe the development of an in vitro model of the simulated spaceflight environment, which we used to investigate the combined effect of simulated microgravity using the random positioning machine (RPM), ionizing radiation, and stress hormones on the wound-healing capacity of human dermal fibroblasts. Fibroblasts were exposed to cortisol, after which they were irradiated with different radiation qualities (including X-rays, protons, carbon ions, and iron ions) followed by exposure to simulated microgravity using a random positioning machine (RPM). Data related to the inflammatory, proliferation, and remodeling phase of wound healing has been collected. Results show that spaceflight stressors can interfere with the wound healing process at any phase. Moreover, several interactions between the different spaceflight stressors were found. This highlights the complexity that needs to be taken into account when studying the effect of spaceflight stressors on certain biological processes and for the aim of countermeasures development.

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

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

Application of a simple DNA damage model developed for electrons to proton irradiation.

Proton beam therapy allows irradiating tumor volumes with reduced side effects on normal tissues with respect to conventional x-ray radiotherapy. Biological effects such as cell killing after proton beam irradiations depend on the proton kinetic energy, which is intrinsically related to early DNA damage induction. As such, DNA damage estimation based on Monte Carlo simulations is a research topic of worldwide interest. Such simulation is a mean of investigating the mechanisms of DNA strand break formations. However, past modellings considering chemical processes and DNA structures require long calculation times. Particle and heavy ion transport system (PHITS) is one of the general-purpose Monte Carlo codes that can simulate track structure of protons, meanwhile cannot handle radical dynamics simulation in liquid water. It also includes a simple model enabling the efficient estimation of DNA damage yields only from the spatial distribution of ionizations and excitations without DNA geometry, which was originally developed for electron track-structure simulations. In this study, we investigated the potential application of the model to protons without any modification. The yields of single-strand breaks, double-strand breaks (DSBs) and the complex DSBs were assessed as functions of the proton kinetic energy. The PHITS-based estimation showed that the DSB yields increased as the linear energy transfer (LET) increased, and reproduced the experimental and simulated yields of various DNA damage types induced by protons with LET up to about 30 keVµm-1. These results suggest that the current DNA damage model implemented in PHITS is sufficient for estimating DNA lesion yields induced after protons irradiation except at very low energies (below 1 MeV). This model contributes to evaluating early biological impacts in radiation therapy.

The Mayo Clinic Florida microdosimetric kinetic model of clonogenic survival: formalism and first benchmark againstin vitroandin silicodata.

Objective. To develop a new model (Mayo Clinic Florida microdosimetric kinetic model, MCF MKM) capable of accurately describing thein vitroclonogenic survival at low and high linear energy transfer (LET) using single-event microdosimetric spectra in a single target.Methodology. The MCF MKM is based on the 'post-processing average' implementation of the non-Poisson microdosimetric kinetic model and includes a novel expression to compute the particle-specific quadratic-dependence of the cell survival with respect to dose (ßof the linear-quadratic model). A new methodology toa prioricalculate the mean radius of the MCF MKM subnuclear domains is also introduced. Lineal energy spectra were simulated with the Particle and Heavy Ion Transport code System (PHITS) for1H,4He,12C,20Ne,40Ar,56Fe, and132Xe ions and used in combination with the MCF MKM to calculate the ion-specific LET-dependence of the relative biological effectiveness (RBE) for Chinese hamster lung fibroblasts (V79 cell line) and human salivary gland tumor cells (HSG cell line). The results were compared within vitrodata from the Particle Irradiation Data Ensemble (PIDE) andin silicoresults of different models. The possibility of performing experiment-specific predictions to explain the scatter in thein vitroRBE data was also investigated. Finally, a sensitivity analysis on the model parameters is also included.Main results. The RBE values predicted with the MCF MKM were found to be in good agreement with thein vitrodata for all tested conditions. Though all MCF MKM model parameters were determineda priori, the accuracy of the MCF MKM was found to be comparable or superior to that of other models. The model parameters determineda prioriwere in good agreement with the ones obtained by fitting all availablein vitrodata.Significance. The MCF MKM will be considered for implementation in cancer radiotherapy treatment planning with accelerated ions.

Investigation of beam delivery time for synchrotron-based proton pencil beam scanning system with novel scanning mode.

Objective.To investigate synchrotron-based proton pencil beam scanning (PBS) beam delivery time (BDT) using novel continuous scanning mode.Approach.A BDT calculation model was developed for the Hitachi particle therapy system. The model was validated against the measured BDT of 36 representative clinical proton PBS plans with discrete spot scanning (DSS) in the current Hitachi proton therapy system. BDTs were calculated with the next generation using Mayo Clinic Florida system operating parameters for conventional DSS, and novel dose driven continuous scanning (DDCS). BDTs of DDCS with and without Break Spots were investigated.Main results.For DDCS without Break Spots, the use of Stop Ratio to control the transit dose largely reduced the beam intensity and consequently, severely prolonged the BDT. DDCS with Break Spots was able to maintain a sufficiently high beam intensity while controlling transit dose. In DDCS with Break Spots, tradeoffs were made between beam intensity and number of Break Spots. Therefore, BDT decreased with increased beam intensity but reached a plateau for beam intensity larger than 10 MU s-1. Averaging over all clinical plans, BDT was reduced by 10% for DDCS with Break Spots compared to DSS.Significance.DDCS with Break Spots reduced BDT. DDCS has the potential to further reduce BDT under the ideal scenario which requests both stable beam intensity extraction and accurately modelling the transit dose. Further investigation is warranted.

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

Objective. To investigate similarities and differences in the formalism, processing, and the results of relative biological effectiveness (RBE) calculations with a biological weighting function (BWF), the microdosimetric kinetic model (MKM) and subsequent modifications (non-Poisson MKM, modified MKM). This includes: (a) the extension of the V79-RBE10%BWF to model the RBE for other clonogenic survival levels; (b) a novel implementation of MKMs as weighting functions; (c) a benchmark against Chinese Hamster lung fibroblast (V79)in vitrodata; (d) a study on the effect of pre- or post- processing the average biophysical quantities used for the RBE calculations; (e) a possible modification of the modified MKM parameters to improve the model accuracy at high linear energy transfer (LET).Methodology. Lineal energy spectra were simulated for two spherical targets (diameter = 0.464 or 1.0µm) using PHITS for1H,4He,12C,20Ne,40Ar,56Fe and132Xe ions. The results of thein silicocalculations were compared with publishedin vitrodata.Main results. All models appear to underestimate the RBEαof hydrogen ions. All MKMs generally overestimate the RBE50%, RBE10%and RBE1%for ions with an LET greater than ∼200 keVµm-1. This overestimation is greater for small surviving fractions and is likely due to the assumption of a radiation-independent quadratic term of clonogenic survival (ß). The overall RBE trends seem to be best described by the novel 'post-processing average' implementation of the non-Poisson MKM. In case of calculations with the non-Poisson MKM, pre- or post- processing the average biophysical quantities affects the computed RBE values significantly.Significance. This study presents a systematic analysis of the formalism and results of widely used microdosimetric models of clonogenic survival for ions relevant for cancer particle therapy and space radiation protection. Points for improvements were highlighted and will contribute to the development of upgraded biophysical models.

Track-structure modes in particle and heavy ion transport code system (PHITS): application to radiobiological research.

PURPOSE: In radiation physics, Monte Carlo radiation transport simulations are powerful tools to evaluate the cellular responses after irradiation. When investigating such radiation-induced biological effects, it is essential to perform track structure simulations by explicitly considering each atomic interaction in liquid water at the sub-cellular and DNA scales. The Particle and Heavy-Ion Transport code System (PHITS) is a Monte Carlo code which enables to calculate track structure at DNA scale by employing the track-structure modes for electrons, protons and carbon ions. In this paper, we review the recent development status and future prospects of the track-structure modes in the PHITS code. CONCLUSIONS: To date, the physical features of these modes have been verified using the available experimental data and Monte Carlo simulation results reported in literature. These track-structure modes can be used for calculating microdosimetric distributions to estimate cell survival and for estimating initial DNA damage yields. The use of PHITS track-structure mode is expected not only to clarify the underlying mechanisms of radiation effects but also to predict curative effects in radiation therapy. The results of PHITS simulations coupled with biophysical models will contribute to the radiobiological studies by precisely predicting radiation-induced biological effects based on the Monte Carlo approach.