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.

Estimation of the relative biological effectiveness for double strand break induction of clinical kilovoltage beams using Monte Carlo simulations

BACKGROUND

The Relative Biological Effectiveness (RBE) of kilovoltage photon beams has been previously investigated in vitro and in silico using analytical methods. The estimated values range from 1.03 to 1.82 depending on the methodology and beam energies examined.

PURPOSE

The focus of this work was to independently estimate RBE values for a range of clinically used kilovoltage beams (70-200 kVp) while investigating the suitability of using TOPAS-nBio for this task.

METHODS

Previously validated spectra of clinical beams were used to generate secondary electron spectra at several depths in a water tank phantom via TOPAS Monte Carlo (MC) simulations. Cell geometry was irradiated with the secondary electrons in TOPAS-nBio MC simulations. The deposited dose and the calculated number of DNA strand breaks were used to estimate RBE values.

RESULTS

Monoenergetic secondary electron simulations revealed the highest direct and indirect double strand break yield at approximately 20 keV. The average RBE value for the kilovoltage beams was calculated to be 1.14.

CONCLUSIONS

TOPAS-nBio was successfully used to estimate the RBE values for a range of clinical radiotherapy beams. The calculated value was in agreement with previous estimates, providing confidence in its clinical use in the future.

Calculation of biological effectiveness of SOBP proton beams: a TOPAS Monte Carlo study

Objective.This study aims to investigate the biological effectiveness of Spread-Out Bragg-Peak (SOBP) proton beams with initial kinetic energies 50-250 MeV at different depths in water using TOPAS Monte Carlo code.Approach.The study modelled SOBP proton beams using TOPAS time feature. Various LET-based models and Repair-Misrepair-Fixation model were employed to calculate Relative Biological Effectiveness (RBE) for V79 cell lines at different on-axis depths based on TOPAS. Microdosimetric Kinetic Model and biological weighting function-based models, which utilize microdosimetric distributions, were also used to estimate the RBE. A phase-space-based method was adopted for calculating microdosimetric distributions.Main results.The trend of variation of RBE with depth is similar in all the RBE models, but the absolute RBE values vary based on the calculation models. RBE sharply increases at the distal edge of SOBP proton beams. In the entrance region of all the proton beams, RBE values at 4 Gy i.e. RBE(4 Gy) resulting from different models are in the range of 1.04-1.07, comparable to clinically used generic RBE of 1.1. Moving from the proximal to distal end of the SOBP, RBE(4 Gy) is in the range of 1.15-1.33, 1.13-1.21, 1.11-1.17, 1.13-1.18 and 1.17-1.21, respectively for 50, 100, 150, 200 and 250 MeV SOBP beams, whereas at the distal dose fall-off region, these values are 1.68, 1.53, 1.44, 1.42 and 1.40, respectively.Significance.The study emphasises application of depth-, dose- and energy- dependent RBE values in clinical application of proton beams.

The sensitivity of radiobiological models in carbon ion radiotherapy (CIRT) and its consequences on the clinical treatment plan: Differences between LEM and MKM models

PURPOSE

Carbon ion radiotherapy (CIRT) relies on relative biological effectiveness (RBE)-weighted dose calculations. Japanese clinics predominantly use the microdosimetric kinetic model (MKM), while European centers utilize the local effect model (LEM). Despite both models estimating RBE-distributions in tissue, their physical and mathematical assumptions differ, leading to significant disparities in RBE-weighted doses. Several European clinics adopted Japanese treatment schedules, necessitating adjustments in dose prescriptions and organ at risk (OAR) constraints. In the context of these two clinically used standards for RBE-weighted dose estimation, the objective of this study was to highlight specific scenarios for which the translations between models diverge, as shortcomings between them can influence clinical decisions.

METHODS

Our aim was to discuss planning strategies minimizing those discrepancies, ultimately striving for more accurate and robust treatments. Evaluations were conducted in a virtual water phantom and patient CT-geometry, optimizing LEM RBE-weighted dose first and recomputing MKM thereafter. Dose-averaged linear energy transfer (LETd) distributions were also assessed.

RESULTS

Results demonstrate how various parameters influence LEM/MKM translation. Similar LEM-dose distributions lead to markedly different MKM-dose distributions and variations in LETd. Generally, a homogeneous LEM RBE-weighted dose aligns with lower MKM values in most of the target volume. Nevertheless, paradoxical MKM hotspots may emerge (at the end of the range), potentially influencing clinical outcomes. Therefore, translation between models requires great caution.

CONCLUSIONS

Understanding the relationship between these two clinical standards enables combining European and Japanese based experiences. The implementation of optimal planning strategies ensures the safety and acceptability of the clinical plan for both models and therefore enhances plan robustness from the RBE-weighted dose and LETd distribution point of view. This study emphasizes the importance of optimal planning strategies and the need for comprehensive CIRT plan quality assessment tools. In situations where simultaneous LEM and MKM computation capabilities are lacking, it can provide guidance in plan design, ultimately contributing to enhanced CIRT outcomes.

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

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

Boron-Containing MOF Nanoparticles with Stable Metabolism in U87-MG Cells Combining Microdosimetry To Evaluate Relative Biological Effectiveness of Boron Neutron Capture Therapy

Accurate prediction of the relative biological effectiveness (RBE) of boron neutron capture therapy (BNCT) is challenging. The therapy is different from other radiotherapy; the dynamic distribution of boron-containing compounds in tumor cells affects the therapeutic outcome considerably and hampers accurate measurement of the neutron-absorbed dose. Herein, we used boron-containing metal-organic framework nanoparticles (BMOFs) with high boron content to target U87-MG cells and maintain the concentration of the 10B isotope in cells. The content of boron in the cells could maintain 90% (60 ppm) within 20 min compared with that at the beginning; therefore, the accurate RBE of BNCT can be acquired. The effects of BNCT upon cells after neutron irradiation were observed, and the neutron-absorbed dose was obtained by Monte Carlo simulations. The RBE of BMOFs was 6.78, which was 4.1-fold higher than that of a small-molecule boron-containing agent (boric acid). The energy spectrum of various particles was analyzed by Monte Carlo simulations, and the RBE was verified theoretically. Our results suggested that the use of nanoparticle-based boron carriers in BNCT may have many advantages and that maintaining a stable boron distribution within cells may significantly improve the efficiency of BNCT.

Technical note: Determination of proton linear energy transfer from the integral depth dose

BACKGROUND

Proton linear energy transfer (LET) is associated with the relative biological effectiveness of radiation on tissues. Monte Carlo (MC) simulations have been known to be the preferred method to calculate LET. Detectors have also been built to measure LET, but they need to be calibrated with MC simulations.

PURPOSE

To propose and test a MC-free method for determining LET from the measured integral depth dose (LFI) of the protons of interest.

METHOD AND MATERIALS

LFI consists of three steps: (1) IDD measurements, (2) extraction of energy spectrum (ES) from the IDD, and (3) LET determination from the extracted ES and the stopping power of each energy. To validate the accuracy of the extraction of ES, we use Gaussian ES to synthesize IDD, extract ES from the synthesized IDD, and then compare the original (ground truth) and extracted ES. LETs calculated from the original and extracted ES are also compared. To obtain the LET of protons of interest, we measure IDDs by a large-area plane-parallel ionization chamber in water. Finally, TOPAS MC is employed to simulate IDDs, ES, and LETs. From the simulated IDD, the extracted ES and LET are compared with the simulations from TOPAS MC.

RESULTS

From the synthesized IDDs, the LETs agreed excellently when the peak energies ≥10 and 1.25 MeV with depth resolutions 0.1 and 0.01 mm, respectively. For energy <1.25 MeV, even higher depth resolution than 0.01 mm is required. From the MC simulated IDDs, our track-averaged LET excellently agreed with MC simulation, but not the LETd . Our LETd was smaller than MC simulated LETd in the shallow region but larger in the distal Bragg peak region.

CONCLUSION

LET can be accurately determined from the IDD. This method can be used in the clinic to commission or validate LETs from other measurement methods or a treatment planning system.

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

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

Dose Distribution Degradation of Carbon-ion Radiotherapy Caused by Tumor Cell-specific Relative Biological Effectiveness of Osteosarcoma: A Simulation Study Using In Vitro Experimental Results

BACKGROUND/AIM

Dose distributions of carbon-ion radiotherapy (C-ion RT) have been created with the relative biological effectiveness (RBE) of human salivary gland cells (HSG). However, no dose distributions have been created using various tumor cell-specific RBE values. Hence, we conducted in vitro experiments to determine the RBE of human osteosarcoma cells (U2OS) and used this RBE value (RBEU2OS) to calculate the dose distribution for C-ion RT.

MATERIALS AND METHODS

To obtain RBE values for various linear energy transfer (LET) levels, we exposed U2OS cells to different doses of X-rays and varying doses and LET levels of C-ion beams (13, 30, 50, and 70 keV/μm). Subsequently, we converted the RBE of HSG (RBEHSG) to RBEU2OS in the treatment planning system and reconstructed the dose distribution for a typical osteosarcoma case. We performed a dose-volume histogram (DVH) analysis, evaluating the percentage of the minimum dose that covered 98%, 50%, and 2% (D98%, D50%, and D2%, respectively), as well as the homogeneity index [HI; calculated as (D2%-D98%)/D50%].

RESULTS

The RBEU2OS values for C-ion beams with LET of 13, 30, 50, and 70 keV/μm were 1.77, 2.25, 2.72, and 4.50, respectively. When comparing DVH parameters with the planning target volume, we observed the following values: D98%, D50%, D2%, and HI for RBEHSG were 64.1, 70.1, 72.4 Gy (RBE), and 0.12, respectively. For RBEU2OS, these values were 86.2, 95.0, 107.9 Gy (RBE), and 0.23, respectively.

CONCLUSION

We utilized RBEU2OS to calculate the dose distribution of carbon ion radiotherapy, revealing potential degradation in dose distribution and particularly worsening of the HI.

DNA damage and repair dependencies of ionising radiation modalities

Radiotherapy is utilised in the treatment of ∼50% of all human cancers, which predominantly employs photon radiation. However, particle radiotherapy elicits significant benefits over conventional photons due to more precise dose deposition and increased linear energy transfer (LET) that generates an enhanced therapeutic response. Specifically, proton beam therapy (PBT) and carbon ion radiotherapy (CIRT) are characterised by a Bragg peak, which generates a low entrance radiation dose, with the majority of the energy deposition being defined within a small region which can be specifically targeted to the tumour, followed by a low exit dose. PBT is deemed relatively low-LET whereas CIRT is more densely ionising and therefore high LET. Despite the radiotherapy type, tumour cell killing relies heavily on the introduction of DNA damage that overwhelms the repair capacity of the tumour cells. It is known that DNA damage complexity increases with LET that leads to enhanced biological effectiveness, although the specific DNA repair pathways that are activated following the different radiation sources is unclear. This knowledge is required to determine whether specific proteins and enzymes within these pathways can be targeted to further increase the efficacy of the radiation. In this review, we provide an overview of the different radiation modalities and the DNA repair pathways that are responsive to these. We also provide up-to-date knowledge of studies examining the impact of LET and DNA damage complexity on DNA repair pathway choice, followed by evidence on how enzymes within these pathways could potentially be therapeutically exploited to further increase tumour radiosensitivity, and therefore radiotherapy efficacy.

Combined RBE and OER optimization in proton therapy with FLUKA based on EF5-PET

INTRODUCTION

Tumor hypoxia is associated with poor treatment outcome. Hypoxic regions are more radioresistant than well-oxygenated regions, as quantified by the oxygen enhancement ratio (OER). In optimization of proton therapy, including OER in addition to the relative biological effectiveness (RBE) could therefore be used to adapt to patient-specific radioresistance governed by intrinsic radiosensitivity and hypoxia.

METHODS

A combined RBE and OER weighted dose (ROWD) calculation method was implemented in a FLUKA Monte Carlo (MC) based treatment planning tool. The method is based on the linear quadratic model, with α and β parameters as a function of the OER, and therefore a function of the linear energy transfer (LET) and partial oxygen pressure (pO2 ). Proton therapy plans for two head and neck cancer (HNC) patients were optimized with pO2 estimated from [18 F]-EF5 positron emission tomography (PET) images. For the ROWD calculations, an RBE of 1.1 (RBE1.1,OER ) and two variable RBE models, Rørvik (ROR) and McNamara (MCN), were used, alongside a reference plan without incorporation of OER (RBE1.1 ).

RESULTS

For the HNC patients, treatment plans in line with the prescription dose and with acceptable target ROWD could be generated with the established tool. The physical dose was the main factor modulated in the ROWD. The impact of incorporating OER during optimization of HNC patients was demonstrated by the substantial difference found between ROWD and physical dose in the hypoxic tumor region. The largest physical dose differences between the ROWD optimized plans and the reference plan was 12.2 Gy.

CONCLUSION

The FLUKA MC based tool was able to optimize proton treatment plans taking the tumor pO2 distribution from hypoxia PET images into account. Independent of RBE-model, both elevated LET and physical dose were found in the hypoxic regions, which shows the potential to increase the tumor control compared to a conventional optimization approach.

Microdosimetric assessment about proton spread-out Bragg peak at different depths based on the normal human mesh-type cell population model

Objective.In clinical proton therapy, the spread-out Bragg peak (SOBP) is commonly used to fit the target shape. Dose depositions at microscopic sites vary, even with a consistent absorbed dose (D) in SOBP. In the present study, monolayer mesh-type cell population models were developed for microdosimetric assessment at different SOBP depths.Approach.Normal human bronchial epithelial (BEAS-2B) and hepatocytes (L-O2) mesh-type cell models were constructed based on fluorescence tomography images of normal human cells. Particle transport simulation in cell populations was performed coupled with Monte Carlo software PHITS. The relationship between microdosimetry and macrodosimetry of SOBP at different depths was described by analyzing the microdosimetric indicators such as specific energyz,specific energy distributionfz,D,and relative standard deviationσz/z¯within cells. Additionally, the microdosimetric distributions characteristics and their contributing factors were also discussed.Main results.The microscopic dose distribution is strongly influenced by cellular size, shape, and material. The mean specific energyz¯of nucleus and cytoplasm in the cell population is greater than the overall absorbed dose of the cell population model (Dp), with a maximumz¯/Dpof 1.1. The cellular dose distribution is different between the BEAS-2B mesh-type model and its concentric ellipsoid geometry-type model, which difference inz¯is about 10.3% for the nucleus and about 7.5% for the cytoplasm with the SOBP depth of 15 cm. WhenD= 2 Gy, the maximumzof L-O2 nucleus reaches 2.8 Gy andσz/z¯is 5.1% at the mid-depth SOBP (16-18 cm); while the maximumzof the BEAS-2B nucleus reaches 2.2 Gy with only 2.7% ofσz/z¯.Significance.The significant variation of microdosimetric distributions of SOBP different depths indicates the necessity to use mesh-type cell population models, which have the potential to be compared with biological results and build the bio-physical model.

Improved Algorithm for Estimation of Linear Energy Transfer in Carbon Ion Radiotherapy Plans

BACKGROUND/AIM

This study aimed to develop an improved algorithm for linear energy transfer (LET) estimation in carbon ion radiotherapy (CIRT) using relative biological effectiveness (RBE) and to establish a clinical pipeline for LET assessment.

MATERIALS AND METHODS

New approximation functions for LET versus RBE were developed for the overkill region. LET estimation performance was examined at two facilities (A and B) using archival- and Monte Carlo simulation-derived LET data, respectively, as a reference. A clinical pipeline for LET assessment was developed using Python and treatment planning systems (TPS).

RESULTS

In dataset A, LET estimation accuracy in the overkill region was improved by 80.0%. In dataset B, estimation accuracy was 2.3%±0.67% across 5 data points examined. LET distribution and LET-volume histograms were visualized for multiple CIRT plans.

CONCLUSION

The new algorithm showed a greater LET estimation performance at multiple facilities using the same TPS. A clinical pipeline for LET assessment was established.

Single proton LET characterization with the Timepix detector and artificial intelligence for advanced proton therapy treatment planning

OBJECTIVE

Protons have advantageous dose distributions and are increasingly used in cancer therapy. At the depth of the Bragg peak range, protons produce a mixed radiation field consisting of low- and high-linear energy transfer (LET) components, the latter of which is characterized by an increased ionization density on the microscopic scale associated with increased biological effectiveness. Prediction of the yield and LET of primary and secondary charged particles at a certain depth in the patient is performed by Monte Carlo simulations but is difficult to verify experimentally. &#xD;Approach: Here, the results of measurements performed with Timepix detector in the mixed radiation field produced by a therapeutic proton beam in water are presented and compared to Monte Carlo simulations. The unique capability of the detector to perform high-resolution single particle tracking and identification enhanced by artificial intelligence allowed to resolve the particle type and measure the deposited energy of each particle comprising the mixed radiation field. Based on the collected data, biologically important physics parameters, the LET of single protons and dose-averaged LET, were computed.&#xD;Main results: An accuracy over 95% was achieved for proton recognition with a developed neural network model. For recognized protons, the measured LET spectra generally agree with the results of Monte Carlo simulations. The mean difference between dose-averaged LET values obtained from measurements and simulations is 17%. We observed a broad spectrum of LET values ranging from a fraction of keV/um to about 10 keV/um for most of the measurements performed in the mixed radiation fields.&#xD;Significance: It has been demonstrated that the introduced measurement method provides experimental data for validation of LET_D or LET spectra in any treatment planning system. The simplicity and accessibility of the presented methodology make it easy to be translated into a clinical routine in any proton therapy facility.

A Mission to Mars: Prediction of GCR Doses and Comparison with Astronaut Dose Limits

Long-term human space missions such as a future journey to Mars could be characterized by several hazards, among which radiation is one the highest-priority problems for astronaut health. In this work, exploiting a pre-existing interface between the BIANCA biophysical model and the FLUKA Monte Carlo transport code, a study was performed to calculate astronaut absorbed doses and equivalent doses following GCR exposure under different shielding conditions. More specifically, the interface with BIANCA allowed us to calculate both the RBE for cell survival, which is related to non-cancer effects, and that for chromosome aberrations, related to the induction of stochastic effects, including cancer. The results were then compared with cancer and non-cancer astronaut dose limits. Concerning the stochastic effects, the equivalent doses calculated by multiplying the absorbed dose by the RBE for chromosome aberrations ("high-dose method") were similar to those calculated using the Q-values recommended by ICRP. For a 650-day mission at solar minimum (representative of a possible Mars mission scenario), the obtained values are always lower than the career limit recommended by ICRP (1 Sv), but higher than the limit of 600 mSv recently adopted by NASA. The comparison with the JAXA limits is more complex, since they are age and sex dependent. Concerning the deterministic limits, even for a 650-day mission at solar minimum, the values obtained by multiplying the absorbed dose by the RBE for cell survival are largely below the limits established by the various space agencies. Following this work, BIANCA, interfaced with an MC transport code such as FLUKA, can now predict RBE values for cell death and chromosome aberrations following GCR exposure. More generally, both at solar minimum and at solar maximum, shielding of 10 g/cm² Al seems to be a better choice than 20 g/cm² for astronaut protection against GCR.

Monte Carlo-Based Radiobiological Investigation of the Most Optimal Ion Beam Forming SOBP for Particle Therapy

Proton (p) and carbon (C) ion beams are in clinical use for cancer treatment, although other particles such as He, Be, and B ions have more recently gained attention. Identification of the most optimal ion beam for radiotherapy is a challenging task involving, among others, radiobiological characterization of a beam, which is depth-, energy-, and cell type- dependent. This study uses the FLUKA and MCDS Monte Carlo codes in order to estimate the relative biological effectiveness (RBE) for several ions of potential clinical interest such as p, ⁴He, ⁷Li, ¹⁰Be, ¹⁰B, and ¹²C forming a spread-out Bragg peak (SOBP). More specifically, an energy spectrum of the projectiles corresponding to a 5-cm SOBP at a depth of 8 cm was used. All secondary particles produced by the projectiles were considered and RBE was determined based on radiation-induced Double Strand Breaks (DSBs), as calculated by MCDS. In an attempt to identify the most optimal ion beam, using the latter data, biological optimization was performed and the obtained depth-dose distributions were inter-compared. The results showed that ¹²C ions are more effective inside the SOBP region, which comes at the expense of higher dose values at the tail (i.e., after the SOBP). In contrast, p beams exhibit a higher DSOPB/DEntrance ratio, if physical doses are considered. By performing a biological optimization in order to obtain a homogeneous biological dose (i.e., dose × RBE) in the SOBP, the corresponding advantages of p and ¹²C ions are moderated. ⁷Li ions conveniently combine a considerably lower dose tail and a DSOPB/DEntrance ratio similar to ¹²C. This work contributes towards identification of the most optimal ion beam for cancer therapy. The overall results of this work suggest that ⁷Li ions are of potential interest, although more studies are needed to demonstrate the relevant advantages. Future work will focus on studying more complex beam configurations.

Hypoxia adapted relative biological effectiveness models for proton therapy: a simulation study

In proton therapy, a constant relative biological effectiveness (RBE) factor of 1.1 is applied although the RBE has been shown to depend on factors including the Linear Energy Transfer (LET). The biological effectiveness of radiotherapy has also been shown to depend on the level of oxygenation, quantified by the oxygen enhancement ratio (OER). To estimate the biological effectiveness across different levels of oxygenation the RBE-OER-weighted dose (ROWD) can be used. To investigate the consistency between different approaches to estimate ROWD, we implemented and compared OER models in a Monte Carlo (MC) simulation tool. Five OER models were explored: Wenzl and Wilkens 2011 (WEN), Tinganelliet al2015 (TIN), Strigariet al2018 (STR), Dahleet al2020 (DAH) and Meinet al2021 (MEI). OER calculations were combined with a proton RBE model and the microdosimetric kinetic model for ROWD calculations. ROWD and OER were studied for a water phantom scenario and a head and neck cancer case using hypoxia PET data for the OER calculation. The OER and ROWD estimates from the WEN, MEI and DAH showed good agreement while STR and TIN gave higher OER values and lower ROWD. The WEN, STR and DAH showed some degree of OER-LET dependency while this was negligible for the MEI and TIN models. The ROWD for all implemented models is reduced in hypoxic regions with an OER of 1.0-2.1 in the target volume. While some variations between the models were observed, all models display a large difference in the estimated dose from hypoxic and normoxic regions. This shows the potential to increase the dose or LET in hypoxic regions or reduce the dose to normoxic regions which again could lead to normal tissue sparing. With reliable hypoxia imaging, RBE-OER weighting could become a useful tool for proton therapy plan optimization.

Assessing the DNA Damaging Effectiveness of Ionizing Radiation Using Plasmid DNA

Plasmid DNA is useful for investigating the DNA damaging effects of ionizing radiation. In this study, we have explored the feasibility of plasmid DNA-based detectors to assess the DNA damaging effectiveness of two radiotherapy X-ray beam qualities after undergoing return shipment of ~8000 km between two institutions. The detectors consisted of 18 μL of pBR322 DNA enclosed with an aluminum seal in nine cylindrical cavities drilled into polycarbonate blocks. We shipped them to Toronto, Canada for irradiation with either 100 kVp or 6 MV X-ray beams to doses of 10, 20, and 30 Gy in triplicate before being shipped back to San Diego, USA. The Toronto return shipment also included non-irradiated controls and we kept a separate set of controls in San Diego. In San Diego, we quantified DNA single strand breaks (SSBs), double strand breaks (DSBs), and applied Nth and Fpg enzymes to quantify oxidized base damage. The rate of DSBs/Gy/plasmid was 2.8±0.7 greater for the 100 kVp than the 6 MV irradiation. The 100 kVp irradiation also resulted in 5±2 times more DSBs/SSB than the 6 MV beam, demonstrating that the detector is sensitive enough to quantify relative DNA damage effectiveness, even after shipment over thousands of kilometers.

Treatment-planning approaches to intensity modulated proton therapy and the impact on dose-weighted linear energy transfer

PURPOSE

We quantified the effect of various forward-based treatment-planning strategies in proton therapy on dose-weighted linear energy transfer (LETd). By maintaining the dosimetric quality at a clinically acceptable level, we aimed to evaluate the differences in LETd among various treatment-planning approaches and their practicality in minimizing biologic uncertainties associated with LETd.

METHOD

Eight treatment-planning strategies that are achievable in commercial treatment-planning systems were applied on a cylindrical water phantom and four pediatric brain tumor cases. Each planning strategy was compared to either an opposed lateral plan (phantom study) or original clinical plan (patient study). Deviations in mean and maximum LETd from clinically acceptable dose distributions were compared.

RESULTS

In the phantom study, using a range shifter and altering the robust scenarios during optimization had the largest effect on the mean clinical target volume LETd, which was reduced from 4.5 to 3.9 keV/μm in both cases. Variations in the intersection angle between beams had the largest effect on LETd in a ring defined 3 to 5 mm outside the target. When beam intersection angles were reduced from opposed laterals (180°) to 120°, 90°, and 60°, corresponding maximum LETd increased from 7.9 to 8.9, 10.9, and 12.2 keV/μm, respectively. A clear trend in mean and maximum LETd variations in the clinical cases could not be established, though spatial distribution of LETd suggested a strong dependence on patient anatomy and treatment geometry.

CONCLUSION

Changes in LETd from treatment-plan setup follow intuitive trends in a controlled phantom experiment. Anatomical and other patient-specific considerations, however, can preclude generalizable strategies in clinical cases. For pediatric cranial radiation therapy, we recommend using opposed lateral treatment fields to treat midline targets.

Effect of boron compounds on the biological effectiveness of proton therapy

PURPOSE

We assessed whether adding sodium borocaptate (BSH) or 4-borono-l-phenylalanine (BPA) to cells irradiated with proton beams influenced the biological effectiveness of those beams against prostate cancer cells to investigate if the alpha particles generated through proton-boron nuclear reactions would be sufficient to enhance the biological effectiveness of the proton beams.

METHODS

We measured clonogenic survival in DU145 cells treated with 80.4-ppm BSH or 86.9-ppm BPA, or their respective vehicles, after irradiation with 6-MV X-rays, 1.2-keV/μm (low linear energy transfer [LET]) protons, or 9.9-keV/μm (high-LET) protons. We also measured γH2AX and 53BP1 foci in treated cells at 1 and 24 h after irradiation with the same conditions.

RESULTS

We found that BSH radiosensitized DU145 cells across all radiation types. However, no difference was found in relative radiosensitization, characterized by the sensitization enhancement ratio or the relative biological effectiveness, for vehicle- versus BSH-treated cells. No differences were found in numbers of γH2AX or 53BP1 foci or γH2AX/53BP1 colocalized foci for vehicle- versus BSH-treated cells across radiation types. BPA did not radiosensitize DU145 cells nor induced any significant differences when comparing vehicle- versus BPA-treated cells for clonogenic cell survival or γH2AX and 53BP1 foci or γH2AX/53BP1 colocalized foci.

CONCLUSIONS

Treatment with 11 B, at concentrations of 80.4 ppm from BSH or 86.9 ppm from BPA, had no effect on the biological effectiveness of proton beams in DU145 prostate cancer cells. Our results agree with published theoretical calculations indicating that the contribution of alpha particles from such reactions to the total absorbed dose and biological effectiveness is negligible. We also found that BSH radiosensitized DU145 cells to X-rays, low-LET protons, and high-LET protons but that the radiosensitization was not related to DNA damage.

An empirical model of proton RBE based on the linear correlation between x-ray and proton radiosensitivity

BACKGROUND

Proton relative biological effectiveness (RBE) is known to depend on physical factors of the proton beam, such as its linear energy transfer (LET), as well as on cell-line specific biological factors, such as their ability to repair DNA damage. However, in a clinical setting, proton RBE is still considered to have a fixed value of 1.1 despite the existence of several empirical models that can predict proton RBE based on how a cell's survival curve (linear-quadratic model [LQM]) parameters α and β vary with the LET of the proton beam. Part of the hesitation to incorporate variable RBE models in the clinic is due to the great noise in the biological datasets on which these models are trained, often making it unclear which model, if any, provides sufficiently accurate RBE predictions to warrant a departure from RBE = 1.1.

PURPOSE

Here, we introduce a novel model of proton RBE based on how a cell's intrinsic radiosensitivity varies with LET, rather than its LQM parameters.

METHODS AND MATERIALS

We performed clonogenic cell survival assays for eight cell lines exposed to 6 MV x-rays and 1.2, 2.6, or 9.9 keV/µm protons, and combined our measurements with published survival data (n = 397 total cell line/LET combinations). We characterized how radiosensitivity metrics of the form DSF% , (the dose required to achieve survival fraction [SF], e.g., D10% ) varied with proton LET, and calculated the Bayesian information criteria associated with different LET-dependent functions to determine which functions best described the underlying trends. This allowed us to construct a six-parameter model that predicts cells' proton survival curves based on the LET dependence of their radiosensitivity, rather than the LET dependence of the LQM parameters themselves. We compared the accuracy of our model to previously established empirical proton RBE models, and implemented our model within a clinical treatment plan evaluation workflow to demonstrate its feasibility in a clinical setting.

RESULTS

Our analyses of the trends in the data show that DSF% is linearly correlated between x-rays and protons, regardless of the choice of the survival level (e.g., D10% , D37% , or D50% are similarly correlated), and that the slope and intercept of these correlations vary with proton LET. The model we constructed based on these trends predicts proton RBE within 15%-30% at the 68.3% confidence level and offers a more accurate general description of the experimental data than previously published empirical models. In the context of a clinical treatment plan, our model generally predicted higher RBE-weighted doses than the other empirical models, with RBE-weighted doses in the distal portion of the field being up to 50.7% higher than the planned RBE-weighted doses (RBE = 1.1) to the tumor.

CONCLUSIONS

We established a new empirical proton RBE model that is more accurate than previous empirical models, and that predicts much higher RBE values in the distal edge of clinical proton beams.

Implications of Recent Epidemiological Studies for Compensation of Veterans Exposed to Plutonium

ABSTRACT

The objective of this paper is to compare post-2007 epidemiological results for plutonium workers to risk predicted by the software program NIOSH-IREP (IREP for short), which is used to determine the lowest dose for a US veteran to obtain cancer compensation. IREP output and methodology were used to predict excess relative risk per Gy (ERR Gy -1 ) for lung cancer at the 99 th credibility percentile, which is used for compensation decisions. Also estimated were relative biological effectiveness factors (RBE) predicted for workers using IREP methodology. IREP predictions were compared to results for Mayak and Sellafield plutonium workers, separately and pooled. Indications that IREP might underpredict 99 th -percentile lung cancer plutonium risk came from (1) comparison of worker RBEs and (2) from comparison of Sellafield results separately. When Sellafield and Mayak data were pooled, ERR Gy -1 comparisons at the 99 th percentile roughly matched epidemiological data with regression dose range restricted to < 0.05 Gy, the most relevant region to veterans, but overpredicted for the full dose range. When four plausible distributions for lung cancer risk, including both new and old data, were combined using illustrative weighting factors, compensation cutoff dose for lung cancer matched current IREP values unless regression results below 0.05 were chosen for Sellafield, producing a two-fold reduction. A 1997 claim of a dose threshold in lung cancer dose response was not confirmed in later literature. The benefit of the doubt is given to claimants when the science is unclear. The challenge for NIOSH-IREP custodians is dealing with the Sellafield results, which might best match US claimants.

A case-control study of linear energy transfer and relative biological effectiveness related to symptomatic brainstem toxicity following pediatric proton therapy

BACKGROUND AND PURPOSE

A fixed relative biological effectiveness (RBE) of 1.1 (RBE_1.1) is used clinically in proton therapy even though the RBE varies with properties such as dose level and linear energy transfer (LET). We therefore investigated if symptomatic brainstem toxicity in pediatric brain tumor patients treated with proton therapy could be associated with a variable LET and RBE.

MATERIALS AND METHODS

36 patients treated with passive scattering proton therapy were selected for a case-control study from a cohort of 954 pediatric brain tumor patients. Nine children with symptomatic brainstem toxicity were each matched to three controls based on age, diagnosis, adjuvant therapy, and brainstem RBE_1.1 dose characteristics. Differences across cases and controls related to the dose-averaged LET (LET_d) and variable RBE-weighted dose from two RBE models were analyzed in the high-dose region.

RESULTS

LET_d metrics were marginally higher for cases vs. controls for the majority of dose levels and brainstem substructures. Considering areas with doses above 54 Gy(RBE_1.1), we found a moderate trend of 13% higher median LET_d in the brainstem for cases compared to controls (P = .08), while the difference in the median variable RBE-weighted dose for the same structure was only 2% (P = .6).

CONCLUSION

Trends towards higher LET_d for cases compared to controls were noticeable across structures and LET_d metrics for this patient cohort. While case-control differences were minor, an association with the observed symptomatic brainstem toxicity cannot be ruled out.

Modeling secondary cancer risk ratios for proton versus carbon ion beam therapy: A comparative study based on the local effect model

BACKGROUND

Ion beam therapy allows for substantial sparing of normal tissues. Besides deterministic normal-tissue complications, stochastic long-term effects like secondary cancer (SC) induction are of importance when comparing different treatment modalities.

PURPOSE

To develop a modeling approach for comparison of SC risk in proton and carbon ion therapy.

METHODS AND MATERIALS

The local effect model (LEM) is used to predict the relative biological effectiveness (RBE) of SC induction after particle therapy. A key feature of the new approach is the double use of the LEM, reflecting the competition between the two processes of mutation induction (leading to cancer development) and cell inactivation (leading to suppression of cancer development). Based on previous investigations, treatment plans were in this work analyzed for an idealized geometry in order to assess the underlying systematic dependencies of cancer induction. In a further step, relative SC risks were predicted for proton and carbon ion treatment plans prepared for 10 prostate cancer patients.

RESULTS

We investigated the impact of factors such as treatment plan geometry, fractionation scheme, and tissue radiosensitivity to photon irradiation on the ion beam SC risk. Our model studies do not result in a clear preference for either protons or carbon ions, but rather indicate a complex interplay of different aspects. Reduced lateral scattering leads to a lower SC risk for carbon ions compared to protons at the lateral field margins in the entrance channel, while an increased risk was found closely behind the tumor due to projectile fragmentation. The fractionation scheme had little impact on the expected risk ratio. With respect to sensitivity parameters, those characterizing RBE for cell killing of potentially cancerous cells as well as of the primary tumor had the most significant impact. The observed general systematic dependencies are in agreement with results from previous model studies. The prostate patient study reveals reduced SC risks predictions for skin and bones for carbon ions as compared to protons, but higher mean risks for bladder and rectum.

CONCLUSION

The methods established in this work provide a basis for further investigating treatment optimizing strategies for ion beam therapy with regard to SC risk comparisons.

A double-strand-break model for the relative biological effectiveness of electrons based on ionization clustering

BACKGROUND

The effectiveness of ionizing radiation regarding DNA damage induction depends on its spatial energy deposition pattern. For electrons an increased effectiveness is observed at low kinetic energies due to the enhanced density of energy deposition events at electron track ends.

PURPOSE

A model is presented, which enables the calculation of the double-strand-break (DSB) yield and the relative biological effectiveness (RBE) for DSB induction of electrons.

METHODS

The model applies the mean free path between two ionizations and the assumption that two ionizations within a certain threshold distance are necessary to potentially lead to a DSB. Next to an expression for the electron RBE according to its common definition, a local RBE is determined, which describes the electrons' local effectiveness at a defined point on their track.

RESULTS

This local RBE allows a better understanding of microscopic processes resulting from radiation and can be used, for instance, to describe the mean effectiveness of the mixed electron radiation field as a function of the radial distance to the center of an ion track.

CONCLUSIONS

The presented model reflects the experimentally observed increased effectiveness of low-energetic electrons. It will be used in a future work to improve RBE predictions for ions performed with the local effect model.

Empirical Relative Biological Effectiveness (RBE) for Mandible Osteoradionecrosis (ORN) in Head and Neck Cancer Patients Treated With Pencil-Beam-Scanning Proton Therapy (PBSPT): A Retrospective, Case-Matched Cohort Study

Purpose

To retrospectively investigate empirical relative biological effectiveness (RBE) for mandible osteoradionecrosis (ORN) in head and neck (H&N) cancer patients treated with pencil-beam-scanning proton therapy (PBSPT).

Methods

We included 1,266 H&N cancer patients, of which, 931 patients were treated with volumetric-modulated arc therapy (VMAT) and 335 were treated with PBSPT. Among them, 26 VMAT and 9 PBSPT patients experienced mandible ORN (ORN group), while all others were included in the control group. To minimize the impact of the possible imbalance in clinical factors between VMAT and PBSPT patients in the dosimetric comparison between these two modalities and the resulting RBE quantification, we formed a 1:1 case-matched patient cohort (335 VMAT patients and 335 PBSPT patients including both the ORN and control groups) using the greedy nearest neighbor matching of propensity scores. Mandible dosimetric metrics were extracted from the case-matched patient cohort and statistically tested to evaluate the association with mandibular ORN to derive dose volume constraints (DVCs) for VMAT and PBSPT, respectively. We sought the equivalent constraint doses for VMAT so that the critical volumes of VMAT were equal to those of PBSPT at different physical doses. Empirical RBEs of PBSPT for ORN were obtained by calculating the ratio between the derived equivalent constraint doses and physical doses of PBSPT. Bootstrapping was further used to get the confidence intervals.

Results

Clinical variables of age, gender, tumor stage, prescription dose, chemotherapy, hypertension or diabetes, dental extraction, smoking history, or current smoker were not statistically related to the incidence of ORN in the overall patient cohort. Smoking history was found to be significantly associated with the ORN incidence in PBSPT patients only. V40Gy[RBE], V50Gy[RBE], and V60Gy[RBE] were statistically different (p<0.05) between the ORN and control group for VMAT and PBSPT. Empirical RBEs of 1.58(95%CI: 1.34-1.64), 1.34(95%CI: 1.23-1.40), and 1.24(95%: 1.15-1.26) were obtained for proton dose at 40 Gy[RBE=1.1], 50 Gy[RBE=1.1] and 60 Gy[RBE=1.1], respectively.

Conclusions

Our study suggested that RBEs were larger than 1.1 at moderate doses (between 40 and 60 Gy[RBE=1.1]) with high LET for mandible ORN. RBEs are underestimated in current clinical practice in PBSPT. The derived DVCs can be used for PBSPT plan evaluation and optimization to minimize the incidence rate of mandible ORN.

Evaluation of the Response of HNSCC Cell Lines to γ-Rays and 12C Ions: Can Radioresistant Tumors Be Identified and Selected for 12C Ion Radiotherapy?

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide. Thirty percent of patients will experience locoregional recurrence for which median survival is less than 1 year. Factors contributing to treatment failure include inherent resistance to X-rays and chemotherapy, hypoxia, epithelial to mesenchymal transition, and immune suppression. The unique properties of ¹²C radiotherapy including enhanced cell killing, a decreased oxygen enhancement ratio, generation of complex DNA damage, and the potential to overcome immune suppression make its application well suited to the treatment of HNSCC. We examined the ¹²C radioresponse of five HNSCC cell lines, whose surviving fraction at 3.5 Gy ranged from average to resistant when compared with a larger panel of 38 cell lines to determine if ¹²C irradiation can overcome X-ray radioresistance and to identify biomarkers predictive of ¹²C radioresponse. Cells were irradiated with ¹²C using a SOBP with an average LET of 80 keV/μm (CNAO: Pavia, Italy). RBE values varied depending upon endpoint used. A 37 gene signature was able to place cells in their respective radiosensitivity cohort with an accuracy of 86%. Radioresistant cells were characterized by an enrichment of genes associated with radioresistance and survival mechanisms including but not limited to G2/M Checkpoint MTORC1, HIF1α, and PI3K/AKT/MTOR signaling. These data were used in conjunction with an in silico-based modeling approach to evaluate tumor control probability after ¹²C irradiation that compared clinically used treatment schedules with fixed RBE values vs. the RBEs determined for each cell line. Based on the above analysis, we present the framework of a strategy to utilize biological markers to predict which HNSCC patients would benefit the most from ¹²C radiotherapy.

Impact of RBE variations on risk estimates of temporal lobe necrosis in patients treated with intensity-modulated proton therapy for head and neck cancer

BACKGROUND

Temporal lobe necrosis (TLN) is a potential late effect after radiotherapy for skull base head and neck cancer (HNC). Several photon-derived dose constraints and normal tissue complication probability (NTCP) models have been proposed, however variation in relative biological effectiveness (RBE) may challenge the applicability of these dose constraints and models in proton therapy. The purpose of this study was therefore to investigate the influence of RBE variations on risk estimates of TLN after Intensity-Modulated Proton Therapy for HNC.

MATERIAL AND METHODS

Seventy-five temporal lobes from 45 previously treated patients were included in the analysis. Sixteen temporal lobes had radiation associated Magnetic Resonance image changes (TLIC) suspected to be early signs of TLN. Fixed (RWD_Fix) and variable RBE-weighed doses (RWD_Var) were calculated using RBE = 1.1 and two RBE models, respectively. RWD_Fix and RWD_Var for temporal lobes were compared using Friedman's test. Based on RWD_Fix, six NTCP models were fitted and internally validated through bootstrapping. Estimated probabilities from RWD_Fix and RWD_Var were compared using paired Wilcoxon test. Seven dose constraints were evaluated separately for RWD_Fix and RWD_Var by calculating the observed proportion of TLIC in temporal lobes meeting the specific dose constraints.

RESULTS

RWD_Var were significantly higher than RWD_Fix (p < 0.01). NTCP model performance was good (AUC:0.79-0.84). The median difference in estimated probability between RWD_Fix and RWD_Var ranged between 5.3% and 20.0% points (p < 0.01), with V_60GyRBE and D_Max at the smallest and largest differences, respectively. The proportion of TLIC was higher for RWD_Fix (4.0%-13.1%) versus RWD_Var (1.3%-5.3%). For V_65GyRBE ≤ 0.03 cc the proportion of TLIC was less than 5% for both RWD_Fix and RWD_Var.

CONCLUSION

NTCP estimates were significantly influenced by RBE variations. D_max as model predictor resulted in the largest deviations in risk estimates between RWD_Fix and RWD_Var. V_65GyRBE ≤ 0.03 cc was the most consistent dose constraint for RWD_Fix and RWD_Var.

[Biological Effects of Neutron Radiation: An Overview]

Exposure of human body to neutrons occurs in radiotherapy using high-energy radiations. This review summarizes knowledges related to biological effects of neutrons, including those obtained in recent projects in Japan and Europe. A study of Japanese atomic bomb survivors with recently revised dosimetry indicated very high relative biological effectiveness (RBE) of 25-80 (as point estimates) regarding cancer risk. Animal studies indicate RBE of 2-100 or even higher regarding cancer induction, which seem to have a peak around ～1 MeV. Evidence suggests that these values depend on the age and sex. Reported RBE regarding the effects on the lens of the eye is in a similar range and sometimes very high. Regarding other tissue reactions, reported RBE values range from 2-10. Experiments at the cellular level have reported RBE of 1-5 regarding cell killing, 2-20 regarding induction of mutations (with a peak at ～1 MeV), and ～1 regarding induction of DNA double strand breaks. A simulation study predicted that the RBE of induction of complex DNA breaks peaks at ～1 MeV with a value of ～17. The complex breaks produced are likely to be far less in amount than simple DNA breaks, leading to a subtle increase in the yield of total DNA breaks; however, these complex damages may be very efficient in inducing mutations and cancer. Thus, the combination of the yield of complex DNA damage and its efficacy in inducing cancer is considered to underlie the high RBE of neutrons regarding cancer risk.

Microdosimetric Investigation and a Novel Model of Radiosensitization in the Presence of Metallic Nanoparticles

Auger cascades generated in high atomic number nanoparticles (NPs) following ionization were considered a potential mechanism for NP radiosensitization. In this work, we investigated the microdosimetric consequences of the Auger cascades using the theory of dual radiation action (TDRA), and we propose the novel Bomb model as a general framework for describing NP-related radiosensitization. When triggered by an ionization event, the Bomb model considers the NPs that are close to a radiation sensitive cellular target, generates dense secondary electrons and kills the cells according to a probability distribution, acting like a “bomb.” TDRA plus a distance model were used as the theoretical basis for calculating the change in α of the linear-quadratic survival model and the relative biological effectiveness (RBE). We calculated these quantities for SQ20B and Hela human cancer cells under 250 kVp X-ray irradiation with the presence of gadolinium-based NPs (AGuIX^TM), and 220 kVp X-ray irradiation with the presence of 50 nm gold NPs (AuNPs), respectively, and compared with existing experimental data. Geant4-based Monte Carlo (MC) simulations were used to (1) generate the electron spectrum and the phase space data of photons entering the NPs and (2) calculate the proximity functions and other related parameters for the TDRA and the Bomb model. The Auger cascade electrons had a greater proximity function than photoelectric and Compton electrons in water by up to 30%, but the resulting increases in α were smaller than those derived from experimental data. The calculated RBEs cannot explain the experimental findings. The relative increase in α predicted by TDRA was lower than the experimental result by a factor of at least 45 for SQ20B cells with AGuIX under 250 kVp X-ray irradiation, and at least four for Hela cells with AuNPs under 220 kVp X-ray irradiation. The application of the Bomb model to Hela cells with AuNPs under 220 kVp X-ray irradiation indicated that a single ionization event for NPs caused by higher energy photons has a higher probability of killing a cell. NPs that are closer to the cell nucleus are more effective for radiosensitization. Microdosimetric calculations of the RBE for cell death of the Auger electron cascade cannot explain the experimentally observed radiosensitization by AGuIX or AuNP, while the proposed Bomb model is a potential candidate for describing NP-related radiosensitization at low NP concentrations.

64Cu-ATSM Predicts Efficacy of Carbon Ion Radiotherapy Associated with Cellular Antioxidant Capacity

Simple Summary

Carbon ion radiotherapy is an emerging cancer treatment modality that has a greater therapeutic window than conventional photon radiotherapy. To maximize the efficacy of this extremely scarce medical resource, it is important to identify predictive biomarkers of higher carbon ion relative biological effectiveness (RBE) over photons. Here we show that the carbon ion RBE in human cancer cells correlates with the cellular uptake of ⁶⁴Cu(II)-diacetyl-bis(N4-methylthiosemicarbazone) (⁶⁴Cu-ATSM), a potential radioligand that reflects an over-reduced intracellular environment. High RBE/⁶⁴Cu-ATSM cells show greater steady-state levels of antioxidant proteins and increased capacity to scavenge reactive oxygen species in response to X-rays than low RBE/⁶⁴Cu-ATSM counterparts. These data suggest that the cellular antioxidant activity is a possible determinant of carbon ion RBE predictable by ⁶⁴Cu-ATSM uptake.

Abstract

Carbon ion radiotherapy is an emerging cancer treatment modality that has a greater therapeutic window than conventional photon radiotherapy. To maximize the efficacy of this extremely scarce medical resource, it is important to identify predictive biomarkers of higher carbon ion relative biological effectiveness (RBE) over photons. We addressed this issue by focusing on cellular antioxidant capacity and investigated ⁶⁴Cu(II)-diacetyl-bis(N4-methylthiosemicarbazone) (⁶⁴Cu-ATSM), a potential radioligand that reflects an over-reduced intracellular environment. We found that the carbon ion RBE correlated with ⁶⁴Cu-ATSM uptake both in vitro and in vivo. High RBE/⁶⁴Cu-ATSM cells showed greater steady-state levels of antioxidant proteins and increased capacity to scavenge reactive oxygen species in response to X-rays than low RBE/⁶⁴Cu-ATSM counterparts; this upregulation of antioxidant systems was associated with downregulation of TCA cycle intermediates. Furthermore, inhibition of nuclear factor erythroid 2-related factor 2 (Nrf2) sensitized high RBE/⁶⁴Cu-ATSM cells to X-rays, thereby reducing RBE values to levels comparable to those in low RBE/⁶⁴Cu-ATSM cells. These data suggest that the cellular activity of Nrf2-driven antioxidant systems is a possible determinant of carbon ion RBE predictable by ⁶⁴Cu-ATSM uptake. These new findings highlight the potential clinical utility of ⁶⁴Cu-ATSM imaging to identify high RBE tumors that will benefit from carbon ion radiotherapy.

Variation of 4 MV X-ray dose rate in fractionated irradiation strongly impacts biological endothelial cell response in vitro

PURPOSE

Even though X-ray beams are widely used in medical diagnosis or radiotherapy, the comparisons of their dose rates are scarce. We have recently demonstrated in vitro (clonogenic assay, cell viability, cell cycle, senescence) and in vivo (weight follow-up of animals and bordering epithelium staining of lesion), that for a single dose of irradiation, the relative biological effectiveness (RBE) deviates from 1 (up to twofold greater severe damage at the highest dose rate depending on the assay) when increasing the dose rate of high energy X-ray beams.

MATERIAL AND METHODS

To further investigate the impact of the dose rate on RBE, in this study, we performed in vitro fractionated irradiations by using the same two dose rates (0.63 and 2.5 Gy.min^-1) of high-energy X-rays (both at 4 MV) on normal endothelial cells (HUVECs). We investigated the viability/mortality, characterized radiation-induced senescence by using flow cytometry and measured gene analysis deregulations on custom arrays.

RESULTS

The overall results enlighten that, in fractionated irradiations when varying the dose rate of high-energy X-rays, the RBE of photons deviates from 1 (up to 2.86 for viability/mortality experiments performed 21 days postirradiation).

CONCLUSION

These results strengthen the interest of multiparametric analysis approaches in providing an accurate evaluation of the outcomes of irradiated cells in support of clonogenic assays, especially when such assays are not feasible.

Healthy Tissue Damage Following Cancer Ion Therapy: A Radiobiological Database Predicting Lymphocyte Chromosome Aberrations Based on the BIANCA Biophysical Model

Chromosome aberrations are widely considered among the best biomarkers of radiation health risk due to their relationship with late cancer incidence. In particular, aberrations in peripheral blood lymphocytes (PBL) can be regarded as indicators of hematologic toxicity, which is a major limiting factor of radiotherapy total dose. In this framework, a radiobiological database describing the induction of PBL dicentrics as a function of ion type and energy was developed by means of the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model, which has been previously applied to predict the effectiveness of therapeutic-like ion beams at killing tumour cells. This database was then read by the FLUKA Monte Carlo transport code, thus allowing us to calculate the Relative Biological Effectiveness (RBE) for dicentric induction along therapeutic C-ion beams. A comparison with previous results showed that, while in the higher-dose regions (e.g., the Spread-Out Bragg Peak, SOBP), the RBE for dicentrics was lower than that for cell survival. In the lower-dose regions (e.g., the fragmentation tail), the opposite trend was observed. This work suggests that, at least for some irradiation scenarios, calculating the biological effectiveness of a hadrontherapy beam solely based on the RBE for cell survival may lead to an underestimation of the risk of (late) damage to healthy tissues. More generally, following this work, BIANCA has gained the capability of providing RBE predictions not only for cell killing, but also for healthy tissue damage.

Biological effectiveness of He-3 and He-4 ion beams for cancer hadrontherapy: a study based on the BIANCA biophysical model

While cancer therapy with protons and C-ions is continuously spreading, in the near future patients will be also treated with He-ions which, in comparison to photons, combine the higher precision of protons with the higher relative biological effectiveness (RBE) of C-ions. Similarly to C-ions, also for He-ions the RBE variation along the beam must be known as precisely as possible, especially for active beam delivery systems. In this framework the BIANCA biophysical model, which has already been applied to calculate the RBE along proton and C-ion beams, was extended to⁴He-ions and, following interface with the FLUKA code, was benchmarked against cell survival data on CHO normal cells and Renca tumour cells irradiated at different positions along therapeutic-like⁴He-ion beams at the Heidelberg Ion-beam Therapy centre, where the first He-ion patient will be treated soon. Very good agreement between simulations and data was obtained, showing that BIANCA can now be used to predict RBE following irradiation with all ion types that are currently used, or will be used soon, for hadrontherapy. Thanks to the development of a reference simulation database describing V79 cell survival for ion and photon irradiation, these predictions can be cell-type specific because analogous databases can be produced, in principle, for any cell line. Furthermore, survival data on CHO cells irradiated by a He-3 beam were reproduced to compare the biophysical properties of He-4 and He-3 beams, which is currently an open question. This comparison showed that, at the same depth, He-4 beams tend to have a higher RBE with respect to He-3 beams, and that this difference is also modulated by the considered physical dose, as well as the cell radiosensitivity. However, at least for the considered cases, no significant difference was found for the ratio between the RBE-weighted dose in the SOBP and that in the entrance plateau.

Uncertainty in tissue equivalent proportional counter assessments of microdosimetry and RBE estimates in carbon radiotherapy

Microdosimetry is an important tool for assessing energy deposition distributions from ionizing radiation at cellular and cellular nucleus scales. It has served as an input parameter for multiple common mathematical models, including evaluation of relative biological effectiveness (RBE) of carbon ion therapy. The most common detector used for microdosimetry is the tissue-equivalent proportional counter (TEPC). Although it is widely applied, TEPC has various inherent uncertainties. Therefore, this work quantified the magnitude of TEPC measurement uncertainties and their impact on RBE estimates for therapeutic carbon beams. Microdosimetric spectra and frequency-, dose-, and saturation-corrected dose-mean lineal energy (****) were calculated using the Monte Carlo toolkit Geant4 for five monoenergetic and three spread-out Bragg peak carbon beams in water at every millimeter along the central beam axis. We simulated the following influences on these spectra from eight sources of uncertainty: wall effects, pulse pile-up, electronics, gas pressure, W-value, gain instability, low energy cut-off, and counting statistics. Statistic uncertainty was quantified as the standard deviation of perturbed values for each source. Bias was quantified as the difference between default lineal energy values and the mean of perturbed values for each systematic source. Uncertainties were propagated to RBE using the modified microdosimetric kinetic model (MKM). Variance introduced by statistic sources iny¯Fandy¯Daveraged 3.8% and 3.4%, respectively, and 1.5% iny*across beam depths and energies. Bias averaged 6.2% and 7.3% iny¯Fandy¯D,and 4.8% iny*.These uncertainties corresponded to 1.2 ± 0.9% on average in RBE_MKM. The largest contributors to variance and bias were pulse pile-up and wall effects. This study established an error budget for microdosimetric carbon measurements by quantifying uncertainty inherent to TEPC measurements. It is necessary to understand how robust the measurement of RBE model input parameters are against this uncertainty in order to verify clinical model implementation.

A Critical Review of LET-Based Intensity-Modulated Proton Therapy Plan Evaluation and Optimization for Head and Neck Cancer Management

In this review article, we review the 3 important aspects of linear-energy-transfer (LET) in intensity-modulated proton therapy (IMPT) for head and neck (H&N) cancer management. Accurate LET calculation methods are essential for LET-guided plan evaluation and optimization, which can be calculated either by analytical methods or by Monte Carlo (MC) simulations. Recently, some new 3D analytical approaches to calculate LET accurately and efficiently have been proposed. On the other hand, several fast MC codes have also been developed to speed up the MC simulation by simplifying nonessential physics models and/or using the graphics processor unit (GPU)–acceleration approach. Some concepts related to LET are also briefly summarized including (1) dose-weighted versus fluence-weighted LET; (2) restricted versus unrestricted LET; and (3) microdosimetry versus macrodosimetry. LET-guided plan evaluation has been clinically done in some proton centers. Recently, more and more studies using patient outcomes as the biological endpoint have shown a positive correlation between high LET and adverse events sites, indicating the importance of LET-guided plan evaluation in proton clinics. Various LET-guided plan optimization methods have been proposed to generate proton plans to achieve biologically optimized IMPT plans. Different optimization frameworks were used, including 2-step optimization, 1-step optimization, and worst-case robust optimization. They either indirectly or directly optimize the LET distribution in patients while trying to maintain the same dose distribution and plan robustness. It is important to consider the impact of uncertainties in LET-guided optimization (ie, LET-guided robust optimization) in IMPT, since IMPT is sensitive to uncertainties including both the dose and LET distributions. We believe that the advancement of the LET-guided plan evaluation and optimization will help us exploit the unique biological characteristics of proton beams to improve the therapeutic ratio of IMPT to treat H&N and other cancers.

Impact of Hypoxia on Relative Biological Effectiveness and Oxygen Enhancement Ratio for a 62-MeV Therapeutic Proton Beam

This study uses the yields of double-strand breaks (DSBs) to determine the relative biological effectiveness (RBE) of proton beams, using cell survival as a biological endpoint. DSB induction is determined when cells locate at different depths (6 positions) along the track of 62 MeV proton beams. The DNA damage yields are estimated using Monte Carlo Damage Simulation (MCDS) software. The repair outcomes are estimated using Monte Carlo excision repair (MCER) simulations. The RBE for cell survival at different oxygen concentrations is calculated using the repair-misrepair-fixation (RMF) model. Using 60Co γ-rays (linear energy transfer (LET) = 2.4 keV/μm) as the reference radiation, the RBE for DSB induction and enzymatic DSB under aerobic condition (21% O2) are in the range 1.0-1.5 and 1.0-1.6 along the track depth, respectively. In accord with RBE obtained from experimental data, RMF model-derived RBE values for cell survival are in the range of 1.0-3.0. The oxygen enhancement ratio (OER) for cell survival (10%) decreases from 3.0 to 2.5 as LET increases from 1.1 to 22.6 keV/μm. The RBE values for severe hypoxia (0.1% O2) are in the range of 1.1-4.4 as LET increases, indicating greater contributions of direct effects for protons. Compared with photon therapy, the overall effect of 62 MeV proton beams results in greater cell death and is further intensified under hypoxic conditions.

Monte Carlo-based calculation of nano-scale dose enhancement factor and relative biological effectiveness in using different nanoparticles as a radiosensitizer

INTRODUCTION

Nowadays, some nanoparticles (NPs) are known and used as radiosensitizers in radiotherapy and radiobiology, due to their desired biological, physical, and chemical effects on cells. This study aimed to evaluate and compare the dose enhancement factor (DEF) and the biological effectiveness of some common NPs through EGSnrc and MCDS Monte Carlo (MC) simulation codes.

MATERIALS AND METHODS

To evaluate considered NPs' DEF, a single NP with 50 nm diameter was simulated at the center of concentric spheres. NP irradiations were done with 30, 60, and 100 keV photon energies. The secondary electron spectra were scored at the surface of considered NPs, and the dose values were scored at surrounding water-filled spherical shells which were distributed up to 4000 nm from the NP surface. The electron spectra were used in the MCDS code to obtain different initial DNA damages for the calculation of enhanced relative biological effectiveness (eRBE).

RESULTS

By decreasing the photon energy, an increment of DEF was seen for all studied NPs. The maximum DEF at 30, 60, and 100 keV photon energies were respectively related to silver (Ag), gadolinium (Gd), and bismuth (Bi) NPs. The maximum double-strand break (DSB) related (eRBE_DSB) values for the 30 keV photon belonged to Ag, while BiNPs showed the maximum values at other photon energies. The minimum eRBE_DSB values were also related to iron (Fe) NPs at the entire range of studied photon energies.

CONCLUSIONS

The compared nanoscale physical and biological results of our study can be helpful in the selection of optimum NP as a radiosensitizer in future radiobiological studies. Bi, gold (Au), Ag, and platinum (Pt) NPs had great potential, respectively, as radiosensitizers relative to the other studied NPs.

Cell lines of the same anatomic site and histologic type show large variability in intrinsic radiosensitivity and relative biological effectiveness to protons and carbon ions

PURPOSE

To show that intrinsic radiosensitivity varies greatly for protons and carbon (C) ions in addition to photons, and that DNA repair capacity remains important in governing this variability.

METHODS

We measured or obtained from the literature clonogenic survival data for a number of human cancer cell lines exposed to photons, protons (9.9 keV/μm), and C-ions (13.3-77.1 keV/μm). We characterized their intrinsic radiosensitivity by the dose for 10% or 50% survival (D_10% or D_50% ), and quantified the variability at each radiation quality by the coefficient of variation (COV) in D_10% and D_50% . We also treated cells with DNA repair inhibitors prior to irradiation to assess how DNA repair capacity affects their variability.

RESULTS

We found no statistically significant differences in the COVs of D_10% or D_50% between any of the radiation qualities investigated. The same was true regardless of whether the cells were treated with DNA repair inhibitors, or whether they were stratified into histologic subsets. Even within histologic subsets, we found remarkable differences in radiosensitivity for high LET C-ions that were often greater than the variations in RBE, with brain cancer cells varying in D_10% (D_50% ) up to 100% (131%) for 77.1 keV/μm C-ions, and non-small cell lung cancer and pancreatic cancer cell lines varying up to 55% (76%) and 51% (78%), respectively, for 60.5 keV/μm C-ions. The cell lines with modulated DNA repair capacity had greater variability in intrinsic radiosensitivity across all radiation qualities.

CONCLUSIONS

Even for cell lines of the same histologic type, there are remarkable variations in intrinsic radiosensitivity, and these variations do not differ significantly between photon, proton or C-ion radiation. The importance of DNA repair capacity in governing the variability in intrinsic radiosensitivity is not significantly diminished for higher LET radiation.

Impact of Multiple Beams on Plan Quality, Linear Energy Transfer Distribution, and Plan Robustness of Intensity Modulated Proton Therapy for Lung Cancer

The increase of proton beam number might provide higher degrees of freedom in the optimization of intensity-modulated proton therapy planning. In this study, we aimed to quantitatively explore the potential benefits of the increased beam number, including dose volume histogram (DVH), linear energy transfer volume histogram, and DVH bandwidth metrics. Twelve patients with lung cancer are retrospectively selected. Four plans were created based on internal target volume (ITV) robust optimization for each patient using the RayStation treatment planning system. Four plans were generated using different numbers (three, five, seven, and nine) of evenly separated coplanar beams. The three-beam plan was considered as the reference plan. Biologically equivalent doses were calculated using both constant relative biological effectiveness (RBE) and variable RBE models, respectively. To evaluate plan quality, DVH metrics in the target [ITV: D_2%, CI, HI] and organs-at-risk [Lung: V_5Gy[RBE], V_20Gy[RBE], V_30Gy[RBE]; Heart D_2%; Spinal cord D_2%] were calculated using both RBE models. To evaluate LET distributions, LET volume histogram metrics [ITV LET_mean and LET_2%; Lung LET_mean and LET_2%; Heart LET_2%; Spinal cord LET_2%] were quantified. To evaluate plan robustness, the metrics using DVH bandwidth [ITV: D_2%, D_99%; Lung: V_5Gy[RBE], V_20Gy[RBE], V_30Gy[RBE]; Heart D_2%; Spinal cord D_2%] were also reported. For plan quality, the increase of proton beam number resulted in fewer target hot spots, improved target dose conformity, improved target dose homogeneity, lower median-dose lung volume, and fewer hot spots in spinal cord. As to LET distributions, target mean LET increased significantly as the beam number increased to seven or more. Lung LET hot spots were significantly reduced with the increase of proton beams. With respect to plan robustness, the robustness of target dose coverage, target hot spots, and low-dose lung volume were improved, while the robustness of heart hot spots became worse as the beam number increased to nine. The robustness of cord hot spots became worse using five and seven beams compared to that using three beams. As the proton beam number increased, plan quality and LET distributions were comparable or significantly improved. The robustness of target dose coverage, target dose hot spots, and low-dose lung volume were significantly improved.

Variance-based sensitivity analysis for uncertainties in proton therapy: A framework to assess the effect of simultaneous uncertainties in range, positioning, and RBE model predictions on RBE-weighted dose distributions

PURPOSE

Treatment plans in proton therapy are more sensitive to uncertainties than in conventional photon therapy. In addition to setup uncertainties, proton therapy is affected by uncertainties in proton range and relative biological effectiveness (RBE). While to date a constant RBE of 1.1 is commonly assumed, the actual RBE is known to increase toward the distal end of the spread-out Bragg peak. Several models for variable RBE predictions exist. We present a framework to evaluate the combined impact and interactions of setup, range, and RBE uncertainties in a comprehensive, variance-based sensitivity analysis (SA).

MATERIAL AND METHODS

The variance-based SA requires a large number (10⁴ -10⁵ ) of RBE-weighted dose (RWD) calculations. Based on a particle therapy extension of the research treatment planning system CERR we implemented a fast, graphics processing unit (GPU) accelerated pencil beam modeling of patient and range shifts. For RBE predictions, two biological models were included: The mechanistic repair-misrepair-fixation (RMF) model and the phenomenological Wedenberg model. All input parameters (patient position, proton range, RBE model parameters) are sampled simultaneously within their assumed probability distributions. Statistical formalisms rank the input parameters according to their influence on the overall uncertainty of RBE-weighted dose-volume histogram (RW-DVH) quantiles and the RWD in every voxel, resulting in relative, normalized sensitivity indices (S = 0: noninfluential input, S = 1: only influential input). Results are visualized as RW-DVHs with error bars and sensitivity maps.

RESULTS AND CONCLUSIONS

The approach is demonstrated for two representative brain tumor cases and a prostate case. The full SA including ∼ 3 × 10 4 RWD calculations took 39, 11, and 55 min, respectively. Range uncertainty was an important contribution to overall uncertainty at the distal end of the target, while the relatively smaller uncertainty inside the target was governed by biological uncertainties. Consequently, the uncertainty of the RW-DVH quantile D₉₈ for the target was governed by range uncertainty while the uncertainty of the mean target dose was dominated by the biological parameters. The SA framework is a powerful and flexible tool to evaluate uncertainty in RWD distributions and DVH quantiles, taking into account physical and RBE uncertainties and their interactions. The additional information might help to prioritize research efforts to reduce physical and RBE uncertainties and could also have implications for future approaches to biologically robust planning and optimization.

Mapping the Relative Biological Effectiveness of Proton, Helium and Carbon Ions with High-Throughput Techniques

Large amounts of high quality biophysical data are needed to improve current biological effects models but such data are lacking and difficult to obtain. The present study aimed to more efficiently measure the spatial distribution of relative biological effectiveness (RBE) of charged particle beams using a novel high-accuracy and high-throughput experimental platform. Clonogenic survival was selected as the biological endpoint for two lung cancer cell lines, H460 and H1437, irradiated with protons, carbon, and helium ions. Ion-specific multi-step microplate holders were fabricated such that each column of a 96-well microplate is spatially situated at a different location along a particle beam path. Dose, dose-averaged linear energy transfer (LET_d), and dose-mean lineal energy (y_d) were calculated using an experimentally validated Geant4-based Monte Carlo system. Cells were irradiated at the Heidelberg Ion Beam Therapy Center (HIT). The experimental results showed that the clonogenic survival curves of all tested ions were y_d-dependent. Both helium and carbon ions achieved maximum RBEs within specific y_d ranges before biological efficacy declined, indicating an overkill effect. For protons, no overkill was observed, but RBE increased distal to the Bragg peak. Measured RBE profiles strongly depend on the physical characteristics such as y_d and are ion specific.

Implementation of a double scattering nozzle for Monte Carlo recalculation of proton plans with variable relative biological effectiveness

A constant relative biological effectiveness (RBE) of 1.1 is currently used in clinical proton therapy. However, theRBEvaries with factors such as dose level, linear energy transfer (LET) and tissue type. MultipleRBEmodels have been developed to account for this biological variation. To enable recalculation of patients treated with double scattering (DS) proton therapy, includingLETand variableRBE, we implemented and commissioned a Monte Carlo (MC) model of a DS treatment nozzle. The main components from the IBA nozzle were implemented in the FLUKA MC code. We calibrated and verified the following entities to experimental measurements: range of pristine Bragg peaks (PBPs) and spread-out Bragg peaks (SOBPs), energy spread, lateral profiles, compensator range degradation, and absolute dose. We recalculated two patients with different field setups, comparing FLUKA vs. treatment planning system (TPS) dose, also obtainingLETand variableRBEdoses. We achieved good agreement between FLUKA and measurements. The range differences between FLUKA and measurements were for the PBPs within ±0.9 mm (83% ⩽ 0.5 mm), and for SOBPs ±1.6 mm (82% ⩽ 0.5 mm). The differences in modulation widths were below 5 mm (79% ⩽ 2 mm). The differences in the distal dose fall off (D80%-D20%) were below 0.5 mm for all PBPs and the lateral penumbras diverged from measurements by less than 1 mm. The mean dose difference (RBE= 1.1) in the target between the TPS and FLUKA were below 0.4% in a three-field plan and below 1.4% in a four-field plan. A dose increase of 9.9% and 7.2% occurred when using variableRBEfor the two patients, respectively. We presented a method to recalculate DS proton plans in the FLUKA MC code. The implementation was used to obtainLETand variableRBEdose and can be used for investigating variableRBEfor previously treated patients.

Thermal Neutron Relative Biological Effectiveness Factors for Boron Neutron Capture Therapy from In Vitro Irradiations

The experimental determination of the relative biological effectiveness of thermal neutron factors is fundamental in Boron Neutron Capture Therapy. The present values have been obtained while using mixed beams that consist of both neutrons and photons of various energies. A common weighting factor has been used for both thermal and fast neutron doses, although such an approach has been questioned. At the nuclear reactor of the Institut Laue-Langevin a pure low-energy neutron beam has been used to determine thermal neutron relative biological effectiveness factors. Different cancer cell lines, which correspond to glioblastoma, melanoma, and head and neck squamous cell carcinoma, and non-tumor cell lines (lung fibroblast and embryonic kidney), have been irradiated while using an experimental arrangement designed to minimize neutron-induced secondary gamma radiation. Additionally, the cells were irradiated with photons at a medical linear accelerator, providing reference data for comparison with that from neutron irradiation. The survival and proliferation were studied after irradiation, yielding the Relative Biological Effectiveness that corresponds to the damage of thermal neutrons for the different tissue types.

Relative Biological Effectiveness of Carbon Ions for Head-and-Neck Squamous Cell Carcinomas According to Human Papillomavirus Status

Carbon-ion radiotherapy (CIRT) has strong antitumor effects and excellent dose conformity. In head-and-neck squamous cell carcinoma (HNSCC), human papillomavirus (HPV) status is a prognostic factor for photon radiotherapy outcomes. However, the effect of HPV status on the sensitivity of HNSCCs to carbon ions remains unclear. Here, we showed that the relative biological effectiveness (RBE) of carbon ions over X-rays was higher in HPV-negative cells than in HSGc-C5 cells, which are used for CIRT dose establishment, whereas the RBE in HPV-positive cells was modest. These data indicate that CIRT is more advantageous in HPV-negative than in HPV-positive HNSCCs.

Investigating the impact of alpha/beta and LETd on relative biological effectiveness in scanned proton beams: An in vitro study based on human cell lines

PURPOSE

A relative biological effectiveness (RBE) of 1.1 is commonly used in clinical proton therapy, irrespective of tissue type and depth. This in vitro study was conducted to quantify the RBE of scanned protons as a function of the dose-averaged linear energy transfer (LET_d ) and the sensitivity factor (α/ß)_X . Additionally, three phenomenological models (McNamara, Rørvik, and Jones) and one mechanistic model (repair-misrepair-fixation, RMF) were applied to the experimentally derived data.

METHODS

Four human cell lines (FaDu, HaCat, Du145, SKMel) with differential (α/ß)_X ratios were irradiated in a custom-designed irradiation setup with doses between 0 and 6 Gy at proximal, central, and distal positions of a 80 mm spread-out Bragg peak (SOBP) centered at 80 mm (setup A: proton energies 66.5-135.6 MeV) and 155 mm (setup B: proton energies 127.2-185.9 MeV) depth, respectively. LET_d values at the respective cell positions were derived from Monte Carlo simulations performed with the treatment planning system (TPS, RayStation). Dosimetric measurements were conducted to verify dose homogeneity and dose delivery accuracy. RBE values were derived for doses that resulted in 90 % (RBE₉₀ ) and 10 % (RBE₁₀ ) of cell survival, and survival after a 0.5 Gy dose (RBE_0.5Gy ), 2 Gy dose (RBE_2Gy ), and 6 Gy dose (RBE_6Gy ).

RESULTS

LET_d values at sample positions were 1.9, 2.1, 2.5, 2.8, 4.1, and 4.5 keV/µm. For the cell lines with high (α/ß)_X ratios (FaDu, HaCat), the LET_d did not impact on the RBE. For low (α/ß)_X cell lines (Du145, SKMel), LQ-derived survival curves indicated a clear correlation of LET_d and RBE. RBE₉₀ values up to 2.9 and RBE₁₀ values between 1.4 and 1.8 were obtained. Model-derived RBE predictions slightly overestimated the RBE for the high (α/ß)_X cell lines, although all models except the Jones model provided RBE values within the experimental uncertainty. For low (α/ß)_X cell lines, no agreement was found between experiments and model predictions, that is, all models underestimated the measured RBE.

CONCLUSIONS

The sensitivity parameter (α/ß)_X was observed to be a major influencing factor for the RBE of protons and its sensitivity toward LET_d changes. RBE prediction models are applicable for high (α/ß)_X cell lines but do not estimate RBE values with sufficient accuracy in low (α/ß)_X cell lines.

Proton and photon radiosensitization effects of niraparib, a PARP-1/-2 inhibitor, on human head and neck cancer cells

BACKGROUND

Combining photon or proton radiotherapy with targeted therapy shows promise for head and neck cancer (HNSCC). The poly (adenosine diphosphate [ADP]-ribose) polymerase-1/2 inhibitor niraparib targets DNA damage repair (DDR). We evaluated the effects of niraparib in combination with photons or protons, and its effects on the relative biological effectiveness (RBE) of protons, in human HNSCC cell lines.

METHODS

Radiosensitivity was assessed and RBE was calculated with clonogenic survival assays; unrepaired DNA double-strand breaks were evaluated using immunocytochemical analysis of 53BP1 foci.

RESULTS

Niraparib reduced colony formation in two of the four cell lines tested (P < .05), enhanced radiosensitivity in all four cell lines, delayed DDR (P < .05), and increased proton vs photon RBE.

CONCLUSION

Niraparib enhanced the sensitivity of four HNSCC cell lines to both photons and protons and increased the RBE of protons, possibly by inhibiting DDR. Niraparib may enhance the effectiveness of both photon and proton radiotherapy for patients with HNSCC.

High LET Radiation Overcomes In Vitro Resistance to X-Rays of Chondrosarcoma Cell Lines

Chondrosarcomas are malignant tumors of the cartilage that are chemoresistant and radioresistant to X-rays. This restricts the treatment options essential to surgery. In this study, we investigated the sensitivity of chondrosarcoma to X-rays and C-ions in vitro. The sensitivity of 4 chondrosarcoma cell lines (SW1353, CH2879, OUMS27, and L835) was determined by clonogenic survival assays and cell cycle progression. In addition, biomarkers of DNA damage responses were analyzed in the SW1353 cell line. Chondrosarcoma cells showed a heterogeneous sensitivity toward irradiation. Chondrosarcoma cell lines were more sensitive to C-ions exposure compared to X-rays. Using D10 values, the relative biological effectiveness of C-ions was higher (relative biological effectiveness = 5.5) with cells resistant to X-rays (CH2879) and lower (relative biological effectiveness = 3.7) with sensitive cells (L835). C-ions induced more G2 phase blockage and micronuclei in SW1353 cells as compared to X-rays with the same doses. Persistent unrepaired DNA damage was also higher following C-ions irradiation. These results indicate that chondrosarcoma cell lines displayed a heterogeneous response to conventional radiation treatment; however, treatment with C-ions irradiation was more efficient in killing chondrosarcoma cells, compared to X-rays.

Establishment of a New Three-Dimensional Dose Evaluation Method Considering Variable Relative Biological Effectiveness and Dose Fractionation in Proton Therapy Combined with High-Dose-Rate Brachytherapy

Purpose:

The purpose of this study is to evaluate the influence of variable relative biological effectiveness (RBE) of proton beam and dose fractionation has on dose distribution and to establish a new three-dimensional dose evaluation method for proton therapy combined with high-dose-rate (HDR) brachytherapy.

Materials and Methods:

To evaluate the influence of variable RBE and dose fractionation on dose distribution in proton beam therapy, the depth-dose distribution of proton therapy was compared with clinical dose, RBE-weighted dose, and equivalent dose in 2 Gy fractions using a linear-quadratic-linear model (EQD2_LQL). The clinical dose was calculated by multiplying the physical dose by RBE of 1.1. The RBE-weighted dose is a biological dose that takes into account RBE variation calculated by microdosimetric kinetic model implemented in Monte Carlo code. The EQD2_LQL is a biological dose that makes the RBE-weighted dose equivalent to 2 Gy using a linear-quadratic-linear (LQL) model. Finally, we evaluated the three-dimensional dose by taking into account RBE variation and LQL model for proton therapy combined with HDR brachytherapy.

Results:

The RBE-weighted dose increased at the distal of the spread-out Bragg peak (SOBP). With the difference in the dose fractionation taken into account, the EQD2_LQL at the distal of the SOBP increased more than the RBE-weighted dose. In proton therapy combined with HDR brachytherapy, a divergence of 103% or more was observed between the conventional dose estimation method and the dose estimation method we propose.

Conclusions:

Our dose evaluation method can evaluate the EQD2_LQL considering RBE changes in the dose distribution.

Effects of indirect actions and oxygen on relative biological effectiveness: estimate of DSB inductions and conversions induced by therapeutic proton beams

Purpose: This study evaluated the DNA double strand breaks (DSBs) induced by indirect actions and its misrepairs to estimate the relative biological effectiveness (RBE) of proton beams.Materials and methods: From experimental data, DSB induction was evaluated in cells irradiated by 62 MeV proton beams in the presence of dimethylsulphoxide (DMSO) and under hypoxic conditions. The DNA damage yields for calculating the RBE were estimated using Monte Carlo Damage Simulation (MCDS) software. The repair outcomes (correct repairs, mutations and DSB conversions) were estimated using Monte Carlo Excision Repair (MCER) simulations.Results: The values for RBE of 62 MeV protons (LET = 1.051 keV/μm) for DSB induction and enzymatic DSB under aerobic condition (21% O₂) was 1.02 and 0.94, respectively, as comparing to ⁶⁰Co γ-rays (LET = 2.4 keV/μm). DMSO mitigated the inference of indirect action and reduced DSB induction to a greater extent when damaged by protons rather than γ-rays, resulting in a decreased RBE of 0.86. DMSO also efficiently prevented enzymatic DSB yields triggered by proton irradiation and reduced the RBE to 0.83. However, hypoxia (2% O₂) produced a similar level of DSB induction with respect to the protons and γ-rays, with a comparable RBE of 1.02.Conclusions: The RBE values of proton beams estimated from DSB induction and enzymatic DSB decreased by 16% and 12%, respectively, in the presence of DMSO. Our findings indicate that the overall effects of DSB induction and enzymatic DSB could intensify the tumor killing, while alleviate normal tissue damage when indirect actions are effectively interrupted.