A comparison of mechanism-inspired models for particle relative biological effectiveness (RBE)

Biological dose optimization incorporating intra-tumoural cellular radiosensitivity heterogeneity in ion-beam therapy treatment planning

Objective.Treatment plans of ion-beam therapy have been made under an assumption that all cancer cells within a tumour equally respond to a given radiation dose. However, an intra-tumoural cellular radiosensitivity heterogeneity clearly exists, and it may lead to an overestimation of therapeutic effects of the radiation. The purpose of this study is to develop a biological model that can incorporate the radiosensitivity heterogeneity into biological optimization for ion-beam therapy treatment planning.Approach.The radiosensitivity heterogeneity was modeled as the variability of a cell-line specific parameter in the microdosimetric kinetic model following the gamma distribution. To validate the developed intra-tumoural-radiosensitivity-heterogeneity-incorporated microdosimetric kinetic (HMK) model, a treatment plan with H-ion beams was made for a chordoma case, assuming a radiosensitivity heterogeneous region within the tumour. To investigate the effects of the radiosensitivity heterogeneity on the biological effectiveness of H-, He-, C-, O-, and Ne-ion beams, the relative biological effectiveness (RBE)-weighted dose distributions were planned for a cuboid target with the stated ion beams without considering the heterogeneity. The planned dose distributions were then recalculated by taking the heterogeneity into account.Main results. The cell survival fraction and corresponding RBE-weighted dose were formulated based on the HMK model. The first derivative of the RBE-weighted dose distribution was also derived, which is needed for fast biological optimization. For the patient plan, the biological optimization increased the dose to the radiosensitivity heterogeneous region to compensate for the heterogeneity-induced reduction in biological effectiveness of the H-ion beams. The reduction in biological effectiveness due to the heterogeneity was pronounced for low linear energy transfer (LET) beams but moderate for high-LET beams. The RBE-weighted dose in the cuboid target decreased by 7.6% for the H-ion beam, while it decreased by just 1.4% for the Ne-ion beam.Significance.Optimal treatment plans that consider intra-tumoural cellular radiosensitivity heterogeneity can be devised using the HMK model.

An inter-comparison between radiobiological characteristics of a commercial low-energy IORT system by Geant4-DNA and MCDS Monte Carlo codes

INTRODUCTION

The need for accurate relative biological effectiveness (RBE) estimation for low energy therapeutic X-rays (corresponding to 50 kV nominal energy of a commercial low-energy IORT system (INTRABEAM)) is a crucial issue due to increased radiobiological effects, respect to high energy photons. Modeling of radiation-induced DNA damage through Monte Carlo (MC) simulation approaches can give useful information. Hence, this study aimed to evaluate and compare RBE of low energy therapeutic X-rays using Geant4-DNA toolkit and Monte Carlo damage simulation (MCDS) code.

MATERIALS AND METHODS

RBE calculations were performed considering the emitted secondary electron spectra through interactions of low energy X-rays inside the medium. In Geant4-DNA, the DNA strand breaks were obtained by employing a B-DNA model in physical stage with 10.79 eV energy-threshold and the probability of hydroxyl radical's chemical reactions of about 0.13%. Furthermore, RBE estimations by MCDS code were performed under fully aerobic conditions.

RESULTS

Acquired results by two considered MC codes showed that the same trend is found for RBEDSB and RBESSB variations. Totally, a reasonable agreement between the calculated RBE values (both RBESSB and RBEDSB) existed between the two considered MC codes. The mean differences of 9.2% and 1.8% were obtained between the estimated RBESSB and RBEDSB values by two codes, respectively.

CONCLUSION

Based on the obtained results, it can be concluded that a tolerable accordance is found between the calculated RBEDSB values through MCDS and Geant4-DNA, a fact which appropriates both codes for RBE evaluations of low energy therapeutic X-rays, especially in the case of RBEDSB where lethal damages are regarded.

Effects of Differing Underlying Assumptions in In Silico Models on Predictions of DNA Damage and Repair

The induction and repair of DNA double-strand breaks (DSBs) are critical factors in the treatment of cancer by radiotherapy. To investigate the relationship between incident radiation and cell death through DSB induction many in silico models have been developed. These models produce and use custom formats of data, specific to the investigative aims of the researchers, and often focus on particular pairings of damage and repair models. In this work we use a standard format for reporting DNA damage to evaluate combinations of different, independently developed, models. We demonstrate the capacity of such inter-comparison to determine the sensitivity of models to both known and implicit assumptions. Specifically, we report on the impact of differences in assumptions regarding patterns of DNA damage induction on predicted initial DSB yield, and the subsequent effects this has on derived DNA repair models. The observed differences highlight the importance of considering initial DNA damage on the scale of nanometres rather than micrometres. We show that the differences in DNA damage models result in subsequent repair models assuming significantly different rates of random DSB end diffusion to compensate. This in turn leads to disagreement on the mechanisms responsible for different biological endpoints, particularly when different damage and repair models are combined, demonstrating the importance of inter-model comparisons to explore underlying model assumptions.

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

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

Evaluation of the Yield of DNA Double-Strand Breaks for Carbon Ions Using Monte Carlo Simulation and DNA Fragment Distribution

PURPOSE

The aim of this work was to provide a method to evaluate the yield of DNA double-strand breaks (DSBs) for carbon ions, overcoming the bias in existing methods due to the nonrandom distribution of DSBs.

METHODS AND MATERIALS

A previously established biophysical program based on the radiation track structure and a multilevel chromosome model was used to simulate DNA damage induced by x-rays and carbon ions. The fraction of activity retained (FAR) as a function of absorbed dose or particle fluence was obtained by counting the fraction of DNA fragments larger than 6 Mbp. Simulated FAR curves for the 250 kV x-rays and carbon ions at various energies were compared with measurements using constant-field gel electrophoresis. The doses or fluences at the FAR of 0.7 based on linear interpolation were used to estimate the simulation error for the production of DSBs.

RESULTS

The relative difference of doses at the FAR of 0.7 between simulation and experiment was -8.5% for the 250 kV x-rays. The relative differences of fluences at the FAR of 0.7 between simulations and experiments were -17.5%, -42.2%, -18.2%, -3.1%, 10.8%, and -14.5% for the 34, 65, 130, 217, 2232, and 3132 MeV carbon ions, respectively. In comparison, the measurement uncertainty was about 20%. Carbon ions produced remarkably more DSBs and DSB clusters per unit dose than x-rays. The yield of DSBs for carbon ions, ranging from 10 to 16 Gbp-1Gy-1, increased with linear energy transfer (LET) but plateaued in the high-LET end. The yield of DSB clusters first increased and then decreased with LET. This pattern was similar to the relative biological effectiveness for cell survival for heavy ions.

CONCLUSIONS

The estimated yields of DSBs for carbon ions increased from 10 Gbp-1Gy-1 in the low-LET end to 16 Gbp-1Gy-1 in the high-LET end with 20% uncertainty.

High-LET radiation induces large amounts of rapidly-repaired sublethal damage

There is agreement that high-LET radiation has a high Relative Biological Effectiveness (RBE) when delivered as a single treatment, but how it interacts with radiations of different qualities, such as X-rays, is less clear. We sought to clarify these effects by quantifying and modelling responses to X-ray and alpha particle combinations. Cells were exposed to X-rays, alpha particles, or combinations, with different doses and temporal separations. DNA damage was assessed by 53BP1 immunofluorescence, and radiosensitivity assessed using the clonogenic assay. Mechanistic models were then applied to understand trends in repair and survival. 53BP1 foci yields were significantly reduced in alpha particle exposures compared to X-rays, but these foci were slow to repair. Although alpha particles alone showed no inter-track interactions, substantial interactions were seen between X-rays and alpha particles. Mechanistic modelling suggested that sublethal damage (SLD) repair was independent of radiation quality, but that alpha particles generated substantially more sublethal damage than a similar dose of X-rays, [Formula: see text]. This high RBE may lead to unexpected synergies for combinations of different radiation qualities which must be taken into account in treatment design, and the rapid repair of this damage may impact on mechanistic modelling of radiation responses to high LETs.

Creation, evolution, and future challenges of ion beam therapy from a medical physicist's viewpoint (Part 2). Chapter 2. Biophysical model, treatment planning system and image guided radiotherapy

When an ion beam penetrates deeply into the body, its kinetic energy decreases, and its biological effect increases due to the change of the beam quality. To give a uniform biological effect to the target, it is necessary to reduce the absorbed dose with the depth. A bio-physical model estimating the relationship between ion beam quality and biological effect is necessary to determine the relative biological effectiveness (RBE) of the ion beam that changes with depth. For this reason, Lawrence Berkeley Laboratory, National Institute of Radiological Sciences (NIRS) and GSI have each developed their own model at the starting of the ion beam therapy. Also, NIRS developed a new model at the starting of the scanning irradiation. Although the Local Effect Model (LEM) at the GSI and the modified Microdosimetric Kinetic Model (MKM) at the NIRS, the both are currently used, can similarly predict radiation quality-induced changes in surviving fraction of cultured cell, the clinical RBE-weighted doses for the same absorbed dose are different. This is because the LEM uses X-rays as a reference for clinical RBE, whereas the modified MKM uses carbon ion beam as a reference and multiplies it by a clinical factor of 2.41. Therefore, both are converted through the absorbed dose. In PART 2, I will describe the development of such a bio-physical model, as well as the birth and evolution of a treatment planning system and image guided radiotherapy.

Modelling tissue specific RBE for different radiation qualities based on a multiscale characterization of energy deposition

PURPOSE

We present the nanoCluE model, which uses nano- and microdosimetric quantities to model RBE for protons and carbon ions. Under the hypothesis that nano- and microdosimetric quantities correlates with the generation of complex DNA double strand breakes, we wish to investigate whether an improved accuracy in predicting LQ parameters may be achieved, compared to some of the published RBE models.

METHODS

The model is based on experimental LQ data for protons and carbon ions. We generated a database of track structure data for a number of proton and carbon ion kinetic energies with the Geant4-DNA Monte Carlo code. These data were used to obtain both a nanodosimetric quantity and a set of microdosimetric quantities. The latter were tested with different parameterizations versus experimental LQ-data to select the variable and parametrization that yielded the best fit.

RESULTS

For protons, the nanoCluE model yielded, for the ratio of the linear LQ term versus the test data, a root mean square error (RMSE) of 1.57 compared to 1.31 and 1.30 for two earlier other published proton models. For carbon ions the RMSE was 2.26 compared to 3.24 and 5.24 for earlier published carbon ion models.

CONCLUSION

These results demonstrate the feasibility of the nanoCluE RBE model for carbon ions and protons. The increased accuracy for carbon ions as compared to two other considered models warrants further investigation.

A phenomenological model of proton FLASH oxygen depletion effects depending on tissue vasculature and oxygen supply

Introduction

Radiation-induced oxygen depletion in tissue is assumed as a contributor to the FLASH sparing effects. In this study, we simulated the heterogeneous oxygen depletion in the tissue surrounding the vessels and calculated the proton FLASH effective-dose-modifying factor (FEDMF), which could be used for biology-based treatment planning.

Methods

The dose and dose-weighted linear energy transfer (LET) of a small animal proton irradiator was simulated with Monte Carlo simulation. We deployed a parabolic partial differential equation to account for the generalized radiation oxygen depletion, tissue oxygen diffusion, and metabolic processes to investigate oxygen distribution in 1D, 2D, and 3D solution space. Dose and dose rates, particle LET, vasculature spacing, and blood oxygen supplies were considered. Using a similar framework for the hypoxic reduction factor (HRF) developed previously, the FEDMF was derived as the ratio of the cumulative normoxic-equivalent dose (CNED) between CONV and UHDR deliveries.

Results

Dynamic equilibrium between oxygen diffusion and tissue metabolism can result in tissue hypoxia. The hypoxic region displayed enhanced radio-resistance and resulted in lower CNED under UHDR deliveries. In 1D solution, comparing 15 Gy proton dose delivered at CONV 0.5 and UHDR 125 Gy/s, 61.5% of the tissue exhibited ≥20% FEDMF at 175 μm vasculature spacing and 18.9 μM boundary condition. This percentage reduced to 34.5% and 0% for 8 and 2 Gy deliveries, respectively. Similar trends were observed in the 3D solution space. The FLASH versus CONV differential effect remained at larger vasculature spacings. A higher FLASH dose rate showed an increased region with ≥20% FEDMF. A higher LET near the proton Bragg peak region did not appear to alter the FLASH effect.

Conclusion

We developed 1D, 2D, and 3D oxygen depletion simulation process to obtain the dynamic HRF and derive the proton FEDMF related to the dose delivery parameters and the local tissue vasculature information. The phenomenological model can be used to simulate or predict FLASH effects based on tissue vasculature and oxygen concentration data obtained from other experiments.

Linear Energy Transfer and Relative Biological Effectiveness Investigation of Various Structures for a Cohort of Proton Patients With Brain Tumors

Purpose

The current knowledge on biological effects associated with proton therapy is limited. Therefore, we investigated the distributions of dose, dose-averaged linear energy transfer (LET_d), and the product between dose and LET_d (DLET_d) for a patient cohort treated with proton therapy. Different treatment planning system features and visualization tools were explored.

Methods and Materials

For a cohort of 24 patients with brain tumors, the LET_d, DLET_d, and dose was calculated for a fixed relative biological effectiveness value and 2 variable models: plan-based and phenomenological. Dose threshold levels of 0, 5, and 20 Gy were imposed for LET_d visualization. The relationship between physical dose and LET_d and the frequency of LET_d hotspots were investigated.

Results

The phenomenological relative biological effectiveness model presented consistently higher dose values. For lower dose thresholds, the LET_d distribution was steered toward higher values related to low treatment doses. Differences up to 26.0% were found according to the threshold. Maximum LET_d values were identified in the brain, periventricular space, and ventricles. An inverse relationship between LET_d and dose was observed. Frequency information to the domain of dose and LET_d allowed for the identification of clusters, which steer the mean LET_d values, and the identification of higher, but sparse, LET_d values.

Conclusions

Identifying, quantifying, and recording LET distributions in a standardized fashion is necessary, because concern exists over a link between toxicity and LET hotspots. Visualizing DLET_d or dose × LET_d during treatment planning could allow for clinicians to make informed decisions.

Small-scale (sub-organ and cellular level) alpha-particle dosimetry methods using an iQID digital autoradiography imaging system

Targeted radiopharmaceutical therapy with alpha-particle emitters (αRPT) is advantageous in cancer treatment because the short range and high local energy deposition of alpha particles enable precise radiation delivery and efficient tumor cell killing. However, these properties create sub-organ dose deposition effects that are not easily characterized by direct gamma-ray imaging (PET or SPECT). We present a computational procedure to determine the spatial distribution of absorbed dose from alpha-emitting radionuclides in tissues using digital autoradiography activity images from an ionizing-radiation quantum imaging detector (iQID). Data from ²¹¹At-radioimmunotherapy studies for allogeneic hematopoietic cell transplantation in a canine model were used to develop these methods. Nine healthy canines were treated with 16.9-30.9 MBq ²¹¹At/mg monoclonal antibodies (mAb). Lymph node biopsies from early (2-5 h) and late (19-20 h) time points (16 total) were obtained, with 10-20 consecutive 12-µm cryosections extracted from each and imaged with an iQID device. iQID spatial activity images were registered within a 3D volume for dose-point-kernel convolution, producing dose-rate maps. The accumulated absorbed doses for high- and low-rate regions were 9 ± 4 Gy and 1.2 ± 0.8 Gy from separate dose-rate curves, respectively. We further assess uptake uniformity, co-registration with histological pathology, and requisite slice numbers to improve microscale characterization of absorbed dose inhomogeneities in αRPT.

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

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

The Mayo Clinic Florida microdosimetric kinetic model of clonogenic survival: formalism and first benchmark against in vitro and in silico data

Objective. To develop a new model (Mayo Clinic Florida microdosimetric kinetic model, MCF MKM) capable of accurately describing the in vitro clonogenic survival at low and high linear energy transfer (LET) using single-event microdosimetric spectra in a single target. Methodology. The MCF MKM is based on the ‘post-processing average’ implementation of the non-Poisson microdosimetric kinetic model and includes a novel expression to compute the particle-specific quadratic-dependence of the cell survival with respect to dose (β of the linear-quadratic model). A new methodology to a priori calculate the mean radius of the MCF MKM subnuclear domains is also introduced. Lineal energy spectra were simulated with the Particle and Heavy Ion Transport code System (PHITS) for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe, and 132Xe ions and used in combination with the MCF MKM to calculate the ion-specific LET-dependence of the relative biological effectiveness (RBE) for Chinese hamster lung fibroblasts (V79 cell line) and human salivary gland tumor cells (HSG cell line). The results were compared with in vitro data from the Particle Irradiation Data Ensemble (PIDE) and in silico results of different models. The possibility of performing experiment-specific predictions to explain the scatter in the in vitro RBE data was also investigated. Finally, a sensitivity analysis on the model parameters is also included. Main results. The RBE values predicted with the MCF MKM were found to be in good agreement with the in vitro data for all tested conditions. Though all MCF MKM model parameters were determined a priori, the accuracy of the MCF MKM was found to be comparable or superior to that of other models. The model parameters determined a priori were in good agreement with the ones obtained by fitting all available in vitro data. Significance. The MCF MKM will be considered for implementation in cancer radiotherapy treatment planning with accelerated ions.

Comparison of 126 MeV antiproton and proton—a FLUKA-based microdosimetric approach

Objective. This study aims at comparing dosimetric parameters of 126 MeV antiprotons and protons using microdosimetric approach. Approach. Microdosimetric distributions of 126 MeV proton and antiproton beams at 1 μm site size are calculated using the Monte Carlo-based FLUKA code. The distributions are calculated at various depths along the central axis in water phantom as well as at different off-axis locations. The study also includes calculations of secondary radiations produced by antiprotons and protons. Mean quality factor, Q ¯ is calculated using the ICRP 60 and ICRU 40 recommendations. The Relative Biological Effectiveness (RBE) of HSG tumour cell at 10% survival level is calculated based on Microdosimetric Kinetic Model. Main results. Q ¯ I C R P , Q ¯ ICRU and RBE for antiprotons are higher by a factor of about 3.60, 3.41 and 1.24, respectively, at Bragg-peak and higher by a factor of about 1.41, 1.76 and 1.05, respectively, at plateau region of depth-dose profile when compared to protons. At 15 cm depth along the central axis, Q ¯ ICRP , Q ¯ ICRU and RBE for protons are higher by a factor of about 1.42, 1.66 and 1.26, respectively, when compared to antiprotons. At the off-axis distance (Ld ) of 6 cm (at 11.5 cm depth in water), Q ¯ ICRP and Q ¯ ICRU of protons are higher than that of antiproton whereas the trend is opposite at off-axis distance of 4 cm. At Ld = 4 cm (at 11.5 cm depth in water), RBE of antiprotons is higher by about 4% than protons whereas at Ld = 6 cm, RBE of protons is higher by about 13% than antiprotons. Significance. The study shows that antiproton radiotherapy is advantageous as compared to protons considering enhancements in the absorbed dose and RBE-weighed dose values at the Bragg-peak.

Roadmap: helium ion therapy

Helium ion beam therapy for the treatment of cancer was one of several developed and studied particle treatments in the 1950s, leading to clinical trials beginning in 1975 at the Lawrence Berkeley National Laboratory. The trial shutdown was followed by decades of research and clinical silence on the topic while proton and carbon ion therapy made debuts at research facilities and academic hospitals worldwide. The lack of progression in understanding the principle facets of helium ion beam therapy in terms of physics, biological and clinical findings persists today, mainly attributable to its highly limited availability. Despite this major setback, there is an increasing focus on evaluating and establishing clinical and research programs using helium ion beams, with both therapy and imaging initiatives to supplement the clinical palette of radiotherapy in the treatment of aggressive disease and sensitive clinical cases. Moreover, due its intermediate physical and radio-biological properties between proton and carbon ion beams, helium ions may provide a streamlined economic steppingstone towards an era of widespread use of different particle species in light and heavy ion therapy. With respect to the clinical proton beams, helium ions exhibit superior physical properties such as reduced lateral scattering and range straggling with higher relative biological effectiveness (RBE) and dose-weighted linear energy transfer (LET_d) ranging from ∼4 keVμm^-1to ∼40 keVμm^-1. In the frame of heavy ion therapy using carbon, oxygen or neon ions, where LET_dincreases beyond 100 keVμm^-1, helium ions exhibit similar physical attributes such as a sharp lateral penumbra, however, with reduced radio-biological uncertainties and without potentially spoiling dose distributions due to excess fragmentation of heavier ion beams, particularly for higher penetration depths. This roadmap presents an overview of the current state-of-the-art and future directions of helium ion therapy: understanding physics and improving modeling, understanding biology and improving modeling, imaging techniques using helium ions and refining and establishing clinical approaches and aims from learned experience with protons. These topics are organized and presented into three main sections, outlining current and future tasks in establishing clinical and research programs using helium ion beams-A. Physics B. Biological and C. Clinical Perspectives.

Reflections on beam configuration optimization for intensity-modulated proton therapy

Presumably, intensity-modulated proton radiotherapy (IMPT) is the most powerful form of proton radiotherapy. In the current state of the art, IMPT beam configurations (i.e. the number of beams and their directions) are, in general, chosen subjectively based on prior experience and practicality. Beam configuration optimization (BCO) for IMPT could, in theory, significantly enhance IMPT’s therapeutic potential. However, BCO is complex and highly computer resource-intensive. Some algorithms for BCO have been developed for intensity-modulated photon therapy (IMRT). They are rarely used clinically mainly because the large number of beams typically employed in IMRT renders BCO essentially unnecessary. Moreover, in the newer form of IMRT, volumetric modulated arc therapy, there are no individual static beams. BCO is of greater importance for IMPT because it typically employs a very small number of beams (2-4) and, when the number of beams is small, BCO is critical for improving plan quality. However, the unique properties and requirements of protons, particularly in IMPT, make BCO challenging. Protons are more sensitive than photons to anatomic changes, exhibit variable relative biological effectiveness along their paths, and, as recently discovered, may spare the immune system. Such factors must be considered in IMPT BCO, though doing so would make BCO more resource intensive and make it more challenging to extend BCO algorithms developed for IMRT to IMPT. A limited amount of research in IMPT BCO has been conducted; however, considerable additional work is needed for its further development to make it truly effective and computationally practical. This article aims to provide a review of existing BCO algorithms, most of which were developed for IMRT, and addresses important requirements specific to BCO for IMPT optimization that necessitate the modification of existing approaches or the development of new effective and efficient ones.

Biological effectiveness and relative biological effectiveness of ion beams for in-vitro cell irradiation

Biological effectiveness and relative biological effectiveness are critical for proton and ion beam radiotherapy. However, the relationship between the two quantities and physical character of ion beams is not well established. By analyzing 1188 sets of in‐vitro cell irradiation experiments using ion beams ranging from protons to ²³⁸U, compiled by the Particle Irradiation Data Ensemble (PIDE) project, the biological effectiveness of the ion beams, with cell survival fractionation (SF) as the endpoint, was found to be dependent on the fluence and linear energy transfer (LET) of the ion beam. Consequently, the relative biological effectiveness of the ion beam to photon beam was also established as a function of LET. A common form of relationship among SF, fluence, and LET was found to be valid for all ion beam experiments. The close form relationship could be used for proton and ion beam radiotherapy applications.

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

Objective. To investigate similarities and differences in the formalism, processing, and the results of relative biological effectiveness (RBE) calculations with a biological weighting function (BWF), the microdosimetric kinetic model (MKM) and subsequent modifications (non-Poisson MKM, modified MKM). This includes: (a) the extension of the V79-RBE10% BWF to model the RBE for other clonogenic survival levels; (b) a novel implementation of MKMs as weighting functions; (c) a benchmark against Chinese Hamster lung fibroblast (V79) in vitro data; (d) a study on the effect of pre- or post- processing the average biophysical quantities used for the RBE calculations; (e) a possible modification of the modified MKM parameters to improve the model accuracy at high linear energy transfer (LET). Methodology. Lineal energy spectra were simulated for two spherical targets (diameter = 0.464 or 1.0 μm) using PHITS for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe and 132Xe ions. The results of the in silico calculations were compared with published in vitro data. Main results. All models appear to underestimate the RBE α of hydrogen ions. All MKMs generally overestimate the RBE50%, RBE10% and RBE1% for ions with an LET greater than ∼200 keV μm−1. This overestimation is greater for small surviving fractions and is likely due to the assumption of a radiation-independent quadratic term of clonogenic survival (ß). The overall RBE trends seem to be best described by the novel ‘post-processing average’ implementation of the non-Poisson MKM. In case of calculations with the non-Poisson MKM, pre- or post- processing the average biophysical quantities affects the computed RBE values significantly. Significance. This study presents a systematic analysis of the formalism and results of widely used microdosimetric models of clonogenic survival for ions relevant for cancer particle therapy and space radiation protection. Points for improvements were highlighted and will contribute to the development of upgraded biophysical models.

The Effect of Hypoxia on Relative Biological Effectiveness and Oxygen Enhancement Ratio for Cells Irradiated with Grenz Rays

Grenz-ray therapy (GT) is commonly used for dermatological radiotherapy and has a higher linear energy transfer, relative biological effectiveness (RBE) and oxygen enhancement ratio (OER). GT is a treatment option for lentigo maligna and lentigo maligna melanoma. This study aims to calculate the RBE for DNA double-strand break (DSB) induction and cell survival under hypoxic conditions for GT. The yield of DSBs induced by GT is calculated at the aerobic and hypoxic conditions, using a Monte Carlo damage simulation (MCDS) software. The RBE value for cell survival is calculated using the repair–misrepair–fixation (RMF) model. The RBE values for cell survival for cells irradiated by 15 kV, 10 kV and 10 kVp and titanium K-shell X-rays (4.55 kV) relative to 60Co γ-rays are 1.0–1.6 at the aerobic conditions and moderate hypoxia (2% O2), respectively, but increase to 1.2, 1.4 and 1.9 and 2.1 in conditions of severe hypoxia (0.1% O2). The OER values for DSB induction relative to 60Co γ-rays are about constant and ~2.4 for GT, but the OER for cell survival is 2.8–2.0 as photon energy decreases from 15 kV to 4.55 kV. The results indicate that GT results in more DSB induction and allows effective tumor control for superficial and hypoxic tumors.

Proton Therapy for Prostate Cancer: Challenges and Opportunities

Simple Summary

Reported clinical outcomes of proton therapy (PT) for localized prostate cancer are similar to photon-based external beam radiotherapy. Apparently, the dosimetric advantages of PT have yet to be translated to clinical benefits. The suboptimal clinical outcomes of PT might be attributable to inadequate dose prescription, as indicated by the ASCENDE-RT trial. Moreover, uncertainties involved in the treatment planning and delivery processes, as well as technological limitations in PT treatment systems, may lead to discrepancies between planned doses and actual doses delivered to patients. In this article, we reviewed the current status of PT for prostate cancer and discussed different clinical implementations that could potentially improve the clinical outcome of PT for prostate cancer. Various technological advancements under which uncertainties in dose calculations can be minimized, including MRI-guided PT, dual-energy photon-counting CT and high-resolution Monte Carlo-based treatment planning systems, are highlighted.

Abstract

The dosimetric advantages of proton therapy (PT) treatment plans are demonstrably superior to photon-based external beam radiotherapy (EBRT) for localized prostate cancer, but the reported clinical outcomes are similar. This may be due to inadequate dose prescription, especially in high-risk disease, as indicated by the ASCENDE-RT trial. Alternatively, the lack of clinical benefits with PT may be attributable to improper dose delivery, mainly due to geometric and dosimetric uncertainties during treatment planning, as well as delivery procedures that compromise the dose conformity of treatments. Advanced high-precision PT technologies, and treatment planning and beam delivery techniques are being developed to address these uncertainties. For instance, external magnetic resonance imaging (MRI)-guided patient setup rooms are being developed to improve the accuracy of patient positioning for treatment. In-room MRI-guided patient positioning systems are also being investigated to improve the geometric accuracy of PT. Soon, high-dose rate beam delivery systems will shorten beam delivery time to within one breath hold, minimizing the effects of organ motion and patient movements. Dual-energy photon-counting computed tomography and high-resolution Monte Carlo-based treatment planning systems are available to minimize uncertainties in dose planning calculations. Advanced in-room treatment verification tools such as prompt gamma detector systems will be used to verify the depth of PT. Clinical implementation of these new technologies is expected to improve the accuracy and dose conformity of PT in the treatment of localized prostate cancers, and lead to better clinical outcomes. Improvement in dose conformity may also facilitate dose escalation, improving local control and implementation of hypofractionation treatment schemes to improve patient throughput and make PT more cost effective.

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.

Applications of nanodosimetry in particle therapy planning and beyond

This topical review summarizes underlying concepts of nanodosimetry. It describes the development and current status of nanodosimetric detector technology. It also gives an overview of Monte Carlo track structure simulations that can provide nanodosimetric parameters for treatment planning of proton and ion therapy. Classical and modern radiobiological assays that can be used to demonstrate the relationship between the frequency and complexity of DNA lesion clusters and nanodosimetric parameters are reviewed. At the end of the review, existing approaches of treatment planning based on relative biological effectiveness (RBE) models or dose-averaged linear energy transfer are contrasted with an RBE-independent approach based on nandosimetric parameters. Beyond treatment planning, nanodosimetry is also expected to have applications and give new insights into radiation protection dosimetry.

Cell Survival Computation via the Generalized Stochastic Microdosimetric Model (GSM2); Part I: The Theoretical Framework

The current article presents the first application of the Generalized Stochastic Microdosimetric Model (GSM2) for computing explicitly a cell survival curve. GSM2 is a general probabilistic model that predicts the kinetic evolution of DNA damages taking full advantage of a microdosimetric description of a radiation energy deposition. We show that, despite the high generality and flexibility of GSM2, an explicit form for the survival fraction curve predicted by the GSM2 is achievable. We illustrate how several correction terms typically added a posteriori in existing radiobiological models to improve the prediction accuracy, are naturally included into GSM2. Among the most relevant features of the survival curve derived from GSM2 and presented in this article, is the linear-quadratic behavior at low doses and a purely linear trend for high doses. The study also identifies and discusses the connections between GSM2 and existing cell survival models, such as the Microdosimetric Kinetic Model (MKM) and the Multi-hit model. Several approximations to predict cell survival in different irradiation regimes are also introduced to include intercellular non-Poissonian behaviors.

Performance Evaluation for Repair of HSGc-C5 Carcinoma Cell Using Geant4-DNA

Track-structure Monte Carlo simulations are useful tools to evaluate initial DNA damage induced by irradiation. In the previous study, we have developed a Gean4-DNA-based application to estimate the cell surviving fraction of V79 cells after irradiation, bridging the gap between the initial DNA damage and the DNA rejoining kinetics by means of the two-lesion kinetics (TLK) model. However, since the DNA repair performance depends on cell line, the same model parameters cannot be used for different cell lines. Thus, we extended the Geant4-DNA application with a TLK model for the evaluation of DNA damage repair performance in HSGc-C5 carcinoma cells which are typically used for evaluating proton/carbon radiation treatment effects. For this evaluation, we also performed experimental measurements for cell surviving fractions and DNA rejoining kinetics of the HSGc-C5 cells irradiated by 70 MeV protons at the cyclotron facility at the National Institutes for Quantum and Radiological Science and Technology (QST). Concerning fast- and slow-DNA rejoining, the TLK model parameters were adequately optimized with the simulated initial DNA damage. The optimized DNA rejoining speeds were reasonably agreed with the experimental DNA rejoining speeds. Using the optimized TLK model, the Geant4-DNA simulation is now able to predict cell survival and DNA-rejoining kinetics for HSGc-C5 cells.

Carbon ion radiotherapy boosts anti-tumour immune responses by inhibiting myeloid-derived suppressor cells in melanoma-bearing mice

Numerous studies have shown that carbon ion radiotherapy (CIRT) induces anti-cancer immune responses in melanoma patients, yet the mechanism remains elusive. The abundance of myeloid-derived suppressor cells (MDSC) in the tumour microenvironment is associated with therapeutic efficacy and disease outcome. This study analysed the changes in the immune contexture in response to the carbon ion treatment. The murine melanoma B16, MelanA, and S91 tumour models were established in syngeneic immunocompetent mice. Then, the tumours were irradiated with carbon ion beams, and flow cytometry was utilised to observe the immune contexture changes in the bone marrow, peripheral blood, spleen, and tumours. The immune infiltrates in the tumour tissues were further assessed using haematoxylin/eosin staining and immunohistochemistry. The immunoblot detected the expression of proteins associated with the JAK/STAT signalling pathway. The secretion of immune-related cytokines was examined using ELISA. Compared to conventional radiotherapy, particle beams have distinct advantages in cancer therapy. Here, the use of carbon ion beams (5 GyE) for melanoma-bearing mice was found to reduce the population of MDSC in the bone marrow, peripheral blood, and spleen of the animals via a JAK2/STAT3-dependent mechanism. The percentage of CD3⁺, CD4⁺, CD8⁺ T cells, macrophages, and natural killer cells increased after radiation, resulting in reduced tumour growth and prolonged overall survival in the three different mouse models of melanoma. This study, therefore, substantiated that CIRT boosts anti-tumour immune responses via the inhibition of MDSC.

Combined DNA Damage Repair Interference and Ion Beam Therapy: Development, Benchmark, and Clinical Implications of a Mechanistic Biological Model

PURPOSE

Our purpose was to develop a mechanistic model that describes and predicts radiation response after combined DNA damage repair interference (DDRi) and particle radiation therapy.

METHODS AND MATERIALS

The heterogeneous dose distributions of protons and ⁴He ions were implemented into the "UNIfied and VERSatile bio-response Engine" (UNIVERSE). Predictions for monoenergetic and mixed fields over clinically relevant dose and linear energy transfer range were compared with experimental in vitro survival data measured in this work as well as data available in the literature, including different cell lines and DDR interferences. Ultimately, UNIVERSE predictions were investigated in a patient plan.

RESULTS

UNIVERSE accurately predicts survival of cell lines with and without DDRi in clinical settings of ion beam therapy based only on 3 parameters derived from photon data. With increasing dose or linear energy transfer, the radiosensitizing effect of DDRi decreases, resulting in diminished relative biological effect of ion beam radiation for cells subjected to DDRi in comparison to cells that are not. Similar trends were observed in patient plan recalculations; however, this analysis also suggests that DDRi + particle radiation therapy may better preserve the therapeutic window in comparison to DDRi + photon radiation therapy.

CONCLUSIONS

The presented framework represents the first mechanistic model of combined DDRi and particle radiation therapy comprehensively benchmarked in clinically relevant scenarios and a step toward more personalized treatment. It reveals potential differences between DDRi + photon radiation therapy versus DDRi + particle radiation therapy, which have not been described so far. UNIVERSE could aid in appraising the clinical viability of combined administration of radiosensitizing drugs and charged particle therapy, as well as the identification of patients with known DDR deficiencies in the tumor who might benefit from therapy with light ions, freeing limited space at heavy ion therapy centers.

Track Structure Components: Characterizing Energy Deposited in Spherical Cells from Direct and Peripheral HZE Ion Hits

To understand the biological effects of radiation, it is important to determine how ionizing radiation deposits energy in micrometric targets. The energy deposited in a target located in an irradiated tissue is a function of several factors such as the radiation type and the irradiated volume size. We simulated the energy deposited by energetic ions in spherical targets of 1, 2, 4, and 8 µm radii encompassed in irradiated parallelepiped volumes of various sizes using the stochastic radiation track structure code Relativistic Ion Tracks (RITRACKS). Because cells are usually part of a tissue when they are irradiated, electrons originating from radiation tracks in neighboring volumes also contribute to energy deposition in the target. To account for this contribution, we used periodic boundary conditions in the simulations. We found that the single-ion spectra of energy deposition in targets comprises two components: the direct ion hits to the targets, which is identical in all irradiation conditions, and the contribution of hits from electrons from neighboring volumes, which depends on the irradiated volume. We also calculated an analytical expression of the indirect hit contributions using the local effect model, which showed results similar to those obtained with RITRACKS.

Comparisons of 3-Dimensional Conformal and Intensity-Modulated Neutron Therapy for Head and Neck Cancers

PURPOSE

Neutron therapy is a high linear energy transfer modality that is useful for the treatment of radioresistant head and neck (H&N) cancers. It has been limited to 3-dimensioanal conformal-based fast-neutron therapy (3DCNT), but recent technical advances have enabled the clinical implementation of intensity-modulated neutron therapy (IMNT). This study evaluated the comparative dosimetry of IMNT and 3DCNT plans for the treatment of H&N cancers.

MATERIALS AND METHODS

Seven H&N IMNT plans were retrospectively created for patients previously treated with 3DCNT at the University of Washington (Seattle). A custom RayStation model with neutron-specific scattering kernels was used for inverse planning. Organ-at-risk (OAR) objectives from the original 3DCNT plan were initially used and were then systematically reduced to investigate the feasibility of improving a therapeutic ratio, defined as the ratio of the mean tumor to OAR dose. The IMNT and 3DCNT plan quality was evaluated using the therapeutic ratio, isodose contours, and dose volume histograms.

RESULTS

When compared with the 3DCNT plans, IMNT reduces the OAR dose for the equivalent tumor coverage. Moreover, IMNT is most advantageous for OARs in close spatial proximity to the target. For the 7 patients with H&N cancers examined, the therapeutic ratio for IMNT increased by an average of 56% when compared with the 3DCNT. The maximum OAR dose was reduced by an average of 20.5% and 20.7% for the spinal cord and temporal lobe, respectively. The mean dose to the larynx decreased by an average of 80%.

CONCLUSION

The IMNT significantly decreases the OAR doses compared with 3DCNT and provides comparable tumor coverage. Improvements in the therapeutic ratio with IMNT are especially significant for dose-limiting OARs near tumor targets. Moreover, IMNT provides superior sparing of healthy tissues and creates significant new opportunities to improve the care of patients with H&N cancers treated with neutron therapy.

Radioactive Beams for Image-Guided Particle Therapy: The BARB Experiment at GSI

Several techniques are under development for image-guidance in particle therapy. Positron (β⁺) emission tomography (PET) is in use since many years, because accelerated ions generate positron-emitting isotopes by nuclear fragmentation in the human body. In heavy ion therapy, a major part of the PET signals is produced by β⁺-emitters generated via projectile fragmentation. A much higher intensity for the PET signal can be obtained using β⁺-radioactive beams directly for treatment. This idea has always been hampered by the low intensity of the secondary beams, produced by fragmentation of the primary, stable beams. With the intensity upgrade of the SIS-18 synchrotron and the isotopic separation with the fragment separator FRS in the FAIR-phase-0 in Darmstadt, it is now possible to reach radioactive ion beams with sufficient intensity to treat a tumor in small animals. This was the motivation of the BARB (Biomedical Applications of Radioactive ion Beams) experiment that is ongoing at GSI in Darmstadt. This paper will present the plans and instruments developed by the BARB collaboration for testing the use of radioactive beams in cancer therapy.

Dosimetric Assessment of a High Precision System for Mouse Proton Irradiation to Assess Spinal Cord Toxicity

The uncertainty associated with the relative biological effectiveness (RBE) in proton therapy, particularly near the Bragg peak (BP), has led to the shift towards biological-based treatment planning. Proton RBE uncertainty has recently been reported as a possible cause for brainstem necrosis in pediatric patients treated with proton therapy. Despite this, in vivo studies have been limited due to the complexity of accurate delivery and absolute dosimetry. The purpose of this investigation was to create a precise and efficient method of treating the mouse spinal cord with various portions of the proton Bragg curve and to quantify associated uncertainties for the characterization of proton RBE. Mice were restrained in 3D printed acrylic boxes, shaped to their external contour, with a silicone insert extending down to mold around the mouse. Brass collimators were designed for parallel opposed beams to treat the spinal cord while shielding the brain and upper extremities of the animal. Up to six animals may be accommodated for simultaneous treatment within the restraint system. Two plans were generated targeting the cervical spinal cord, with either the entrance (ENT) or the BP portion of the beam. Dosimetric uncertainty was measured using EBT3 radiochromic film with a dose-averaged linear energy transfer (LETd) correction. Positional uncertainty was assessed by collecting a library of live mouse scans (n = 6 mice, two independent scans per mouse) and comparing the following dosimetric statistics from the mouse cervical spinal cord: Volume receiving 90% of the prescription dose (V90); mean dose to the spinal cord; and LETd. Film analysis results showed the dosimetric uncertainty to be ±1.2% and ±5.4% for the ENT and BP plans, respectively. Preliminary results from the mouse library showed the V90 to be 96.3 ± 4.8% for the BP plan. Positional uncertainty of the ENT plan was not measured due to the inherent robustness of that treatment plan. The proposed high-throughput mouse proton irradiation setup resulted in accurate dose delivery to mouse spinal cords positioned along the ENT and BP. Future directions include adapting the setup to account for weight fluctuations in mice undergoing fractionated irradiation.

Development of a DNA damage model that accommodates different cellular oxygen concentrations and radiation qualities

PURPOSE

Research regarding cellular responses at different oxygen concentrations (OCs) is of immense interest within the field of radiobiology. Therefore, this study aimed to develop a mechanistic model to analyze cellular responses at different OCs.

METHODS

A DNA damage model (the different cell oxygen level DNA damage [DICOLDD] model) that examines the oxygen effect was developed based on the oxygen fixation hypothesis, which states that dissolved oxygen can modify the reaction kinetics of DNA-derived radicals generated by ionizing radiation. The generation of DNA-derived radicals was simulated using the Monte Carlo method. The decay of DNA-derived radicals due to the competing processes of chemical repair, oxygen fixation, and intrinsic damaging was described using differential equations. The DICOLDD model was fitted to the previous experimental data obtained under different irradiation configurations and validated by calculating the yields of DNA double-strand breaks (DSBs) after exposure to ¹³⁷ Cs as well as cell survival fractions (SFs) using a mechanistic model of cellular survival. Moreover, we used the DICOLDD model to calculate DNA DSB damage yields after irradiation with 0.5-50 MeV protons.

RESULTS

Generally, DSB yields calculated after exposure to ¹³⁷ Cs at different OCs correspond to statistical uncertainties of previous experimental results. Calculated SFs of CHO and V79 cells exposed to photons, protons, and alpha particles at different OCs generally concur with those obtained in previous studies. Our results demonstrated that the variation in DSB yields was less than 10% when the cellular OC decreased from 21% to 5%. Additionally, DSB yields changed drastically when OC dropped below 1%.

CONCLUSIONS

We developed a DNA damage model to evaluate the oxygen effect and provide evidence that a reaction-kinetic model of DNA-derived radicals induced by ionizing radiation suffices to explain the observed oxygen effects. Therefore, the DICOLDD model is a powerful tool for the analysis of cellular responses at different OCs after exposure to different types of radiation.

Focused Ion Microbeam Irradiation Induces Clustering of DNA Double-Strand Breaks in Heterochromatin Visualized by Nanoscale-Resolution Electron Microscopy

Background: Charged-particle radiotherapy is an emerging treatment modality for radioresistant tumors. The enhanced effectiveness of high-energy particles (such as heavy ions) has been related to the spatial clustering of DNA lesions due to highly localized energy deposition. Here, DNA damage patterns induced by single and multiple carbon ions were analyzed in the nuclear chromatin environment by different high-resolution microscopy approaches. Material and Methods: Using the heavy-ion microbeam SNAKE, fibroblast monolayers were irradiated with defined numbers of carbon ions (1/10/100 ions per pulse, ipp) focused to micrometer-sized stripes or spots. Radiation-induced lesions were visualized as DNA damage foci (γH2AX, 53BP1) by conventional fluorescence and stimulated emission depletion (STED) microscopy. At micro- and nanoscale level, DNA double-strand breaks (DSBs) were visualized within their chromatin context by labeling the Ku heterodimer. Single and clustered pKu70-labeled DSBs were quantified in euchromatic and heterochromatic regions at 0.1 h, 5 h and 24 h post-IR by transmission electron microscopy (TEM). Results: Increasing numbers of carbon ions per beam spot enhanced spatial clustering of DNA lesions and increased damage complexity with two or more DSBs in close proximity. This effect was detectable in euchromatin, but was much more pronounced in heterochromatin. Analyzing the dynamics of damage processing, our findings indicate that euchromatic DSBs were processed efficiently and repaired in a timely manner. In heterochromatin, by contrast, the number of clustered DSBs continuously increased further over the first hours following IR exposure, indicating the challenging task for the cell to process highly clustered DSBs appropriately. Conclusion: Increasing numbers of carbon ions applied to sub-nuclear chromatin regions enhanced the spatial clustering of DSBs and increased damage complexity, this being more pronounced in heterochromatic regions. Inefficient processing of clustered DSBs may explain the enhanced therapeutic efficacy of particle-based radiotherapy in cancer treatment.

Biological Effective Dose for Treatment of a Heterogeneous Population of Cells with a Spread-Out Bragg Peak of Particle Radiation

Calculation of the biological effective dose (BED) of a fractionated course of hadron particle radiation (e.g., protons or carbon ions) administered via a spread-out Bragg peak (SOBP) to a population of cells with heterogeneous radiosensitivity is described. The calculated BED has the important property that, if equal to that of a course of photon radiation, the particle course will result in the same fraction of cells of the exposed population that survive and can be expected to have the same clinical effect. The calculated BED provides a way to relate the effect of a planned treatment course with particle radiation to clinical experience of the effects of treatment with low-LET photon radiation.

Update of the particle irradiation data ensemble (PIDE) for cell survival

The particle irradiation data ensemble (PIDE) is the largest database of cell survival data measured after exposure to ion beams and photon reference radiation. We report here on the updated version of the PIDE database and demonstrate how to investigate generic properties of radiation dose response using these sets of raw data. The database now contains information of over 1100 pairs of photon and ion dose response curves. It provides the originally published raw data of cell survival in addition to given linear quadratic (LQ) model parameters. If available, the raw data were used to derive LQ model parameters in the same way for all experiments. To demonstrate the extent of the database and the variability among experiments we focus on the dose response curves after ion and photon radiation separately in a first step. Furthermore, we discuss the capability and the limitations of the database for analyzing properties of low and high linear energy transfer (LET) radiation response based on multiple experiments. PIDE is freely available to the research community under www.gsi.de/bio-pide.

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.

The Effects of Dimethylsulfoxide and Oxygen on DNA Damage Induction and Repair Outcomes for Cells Irradiated by 62 MeV Proton and 3.31 MeV Helium Ions

Reactive oxygen species (ROS) play an essential role in radiation-induced indirect actions. In terms of DNA damage, double strand breaks (DSBs) have the greatest effects on the repair of DNA damage, cell survival and transformation. This study evaluated the biological effects of the presence of ROS and oxygen on DSB induction and mutation frequency. The relative biological effectiveness (RBE) and oxygen enhancement ratio (OER) of 62 MeV therapeutic proton beams and 3.31 MeV helium ions were calculated using Monte Carlo damage simulation (MCDS) software. Monte Carlo excision repair (MCER) simulations were used to calculate the repair outcomes (mutation frequency). The RBE values of proton beams decreased to 0.75 in the presence of 0.4 M dimethylsulfoxide (DMSO) and then increases to 0.9 in the presence of 2 M DMSO while the RBE values of 3.31 MeV helium ions increased from 2.9 to 5.7 (0–2 M). The mutation frequency of proton beams also decreased from 0.008–0.065 to 0.004–0.034 per cell per Gy by the addition of 2 M DMSO, indicating that ROS affects both DSB induction and repair outcomes. These results show that the combined use of DMSO in normal tissues and an increased dose in tumor regions increases treatment efficiency.

Microdosimetric investigation of the radiation quality of low-medium energy electrons using Geant4-DNA

The increasing clinical use of low-energy photon and electron sources (below few tens of keV) has raised concerns on the adequacy of the existing approximation of an energy-independent radiobiological effectiveness. In this work, the variation of the quality factor (Q) and relative biological effectiveness (RBE) of electrons over the low-medium energy range (0.1 keV-1 MeV) is examined using several microdosimetry-based Monte Carlo methodologies with input data obtained from Geant4-DNA track-structure simulations. The sensitivity of the results to the different methodologies, Geant4-DNA physics models, and target sizes is examined. Calculations of Q and RBE are based on the ICRU Report 40 recommendations, the Kellerer-Hahn approximation, the site version of the theory of dual radiation action (TDRA), the microdosimetric kinetic model (MKM) of cell survival, and the calculated yield of DNA double strand breaks (DSB). The stochastic energy deposition spectra needed as input in the above approaches have been calculated for nanometer spherical volumes using the different electron physics models of Geant4-DNA. Results are normalized at 100 keV electrons which is here considered the reference radiation. It is shown that in the energy range ~50 keV-1 MeV, the calculated Q and RBE are approximately unity (to within 1-2%) irrespective of the methodology, Geant4-DNA physics model, and target size. At lower energies, Q and RBE become energy-dependent reaching a maximum value of ~1.5-2.5 between ~200 and 700 eV. The detailed variation of Q and RBE at low energies depends mostly upon the adopted methodology and target size, and less so upon the Geant4-DNA physics model. Overall, the DSB yield predicts the highest RBE values (with RBE_max≈2.5) whereas the MKM the lowest RBE values (with RBE_max≈1.5). The ICRU Report 40, Kellerer-Hahn, and TDRA methods are in excellent agreement (to within 1-2%) over the whole energy range predicting a Q_max≈2. In conclusion, the approximation Q=RBE=1 was found to be valid only above ~50 keV whereas at lower energies both Q and RBE become strongly energy-dependent. It is envisioned that the present work will contribute towards establishing robust methodologies to determine theoretically the energy-dependence of radiation quality of individual electrons which may then be used in subsequent calculations involving practical electron and photon radiation sources.

Proton RBE models: commonalities and differences

Uncertainties in the relative biological effectiveness (RBE) of protons remains a major barrier to the biological optimisation of proton therapy. While a constant value of 1.1 is widely used in treatment planning, extensive preclinical in vitro and in vivo data suggests that proton RBE is variable, depending on proton energy, target tissue, and endpoint. A number of phenomenological models have been developed to try and explain this variation, but agreement between these models is often poor. This has been attributed to both the models' underlying assumptions and the data to which they are fit. In this brief note, we investigate the underlying trends in these models by comparing their predictions as a function of relevant biological and physical parameters, to determine where models are in conceptual agreement or disagreement. By doing this, it can be seen that the primary differences between models arise from how they handle biological parameters (i.e. [Formula: see text] and [Formula: see text] from the linear-quadratic model for photon exposures). By contrast, when specifically explored for linear energy transfer-dependence, all models show extremely good correlation. These observations suggest that there is a pressing need for more systematic exploration of biological variation in RBE across different cells in well-controlled conditions to help distinguish between these different models and identify the true behaviour.

A Mathematical Radiobiological Model (MRM) to Predict Complex DNA Damage and Cell Survival for Ionizing Particle Radiations of Varying Quality

Predicting radiobiological effects is important in different areas of basic or clinical applications using ionizing radiation (IR); for example, towards optimizing radiation protection or radiation therapy protocols. In this case, we utilized as a basis the ‘MultiScale Approach (MSA)’ model and developed an integrated mathematical radiobiological model (MRM) with several modifications and improvements. Based on this new adaptation of the MSA model, we have predicted cell-specific levels of initial complex DNA damage and cell survival for irradiation with ¹¹Β, ¹²C, ¹⁴Ν, ¹⁶Ο, ²⁰Νe, ⁴⁰Αr, ²⁸Si and ⁵⁶Fe ions by using only three input parameters (particle’s LET and two cell-specific parameters: the cross sectional area of each cell nucleus and its genome size). The model-predicted survival curves are in good agreement with the experimental ones. The particle Relative Biological Effectiveness (RBE) and Oxygen Enhancement Ratio (OER) are also calculated in a very satisfactory way. The proposed integrated MRM model (within current limitations) can be a useful tool for the assessment of radiation biological damage for ions used in hadron-beam radiation therapy or radiation protection purposes.

Development of patient-specific 3D models from histopathological samples for applications in radiation therapy

The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p < 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated.

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.

Carbon Ion Radiobiology

Simple Summary

Radiotherapy with carbon ions has been used for over 20 years in Asia and Europe and is now planned in the USA. The physics advantages of carbon ions compared to X-rays are similar to those of protons, but their radiobiological features are quite distinct and may lead to a breakthrough in the treatment of some cancers characterized by high mortality.

Abstract

Radiotherapy using accelerated charged particles is rapidly growing worldwide. About 85% of the cancer patients receiving particle therapy are irradiated with protons, which have physical advantages compared to X-rays but a similar biological response. In addition to the ballistic advantages, heavy ions present specific radiobiological features that can make them attractive for treating radioresistant, hypoxic tumors. An ideal heavy ion should have lower toxicity in the entrance channel (normal tissue) and be exquisitely effective in the target region (tumor). Carbon ions have been chosen because they represent the best combination in this direction. Normal tissue toxicities and second cancer risk are similar to those observed in conventional radiotherapy. In the target region, they have increased relative biological effectiveness and a reduced oxygen enhancement ratio compared to X-rays. Some radiobiological properties of densely ionizing carbon ions are so distinct from X-rays and protons that they can be considered as a different “drug” in oncology, and may elicit favorable responses such as an increased immune response and reduced angiogenesis and metastatic potential. The radiobiological properties of carbon ions should guide patient selection and treatment protocols to achieve optimal clinical results.

Mechanistic Modeling of the Relative Biological Effectiveness of Boron Neutron Capture Therapy

Accurate dosimetry and determination of the biological effectiveness of boron neutron capture therapy (BNCT) is challenging because of the mix of different types and energies of radiation at the cellular and subcellular levels. In this paper, we present a computational, multiscale system of models to better assess the relative biological effectiveness (RBE) and compound biological effectiveness (CBE) of several neutron sources as applied to BNCT using boronophenylalanine (BPA) and a potential monoclonal antibody (mAb) that targets HER-2-positive cells with Trastuzumab. The multiscale model is tested against published in vitro and in vivo measurements of cell survival with and without boron. The combined dosimetric and radiobiological model includes an analytical formulation that accounts for the type of neutron source, the tissue- or cancer-specific dose–response characteristics, and the microdistribution of boron. Tests of the model against results from published experiments with and without boron show good agreement between modeled and experimentally determined cell survival for neutrons alone and in combination with boron. The system of models developed in this work is potentially useful as an aid for the optimization and individualization of BNCT for HER-2-positive cancers, as well as other cancers, that can be targeted with mAb or a conventional BPA compound.

Assessment of RBE-Weighted Dose Models for Carbon Ion Therapy Toward Modernization of Clinical Practice at HIT: In Vitro, in Vivo, and in Patients

PURPOSE

Present-day treatment planning in carbon ion therapy is conducted with assumptions for a limited number of tissue types and models for effective dose. Here, we comprehensively assess relative biological effectiveness (RBE) in carbon ion therapy and associated models toward the modernization of current clinical practice in effective dose calculation.

METHODS

Using 2 human (A549, H460) and 2 mouse (B16, Renca) tumor cell lines, clonogenic cell survival assay was performed for examination of changes in RBE along the full range of clinical-like spread-out Bragg peak (SOBP) fields. Prediction power of the local effect model (LEM1 and LEM4) and the modified microdosimetric kinetic model (mMKM) was assessed. Experimentation and analysis were carried out in the frame of a multidimensional end point study for clinically relevant ranges of physical dose (D), dose-averaged linear energy transfer (LET_d), and base-line photon radio-sensitivity (α/β)_x. Additionally, predictions were compared against previously reported RBE measurements in vivo and surveyed in patient cases.

RESULTS

RBE model prediction performance varied among the investigated perspectives, with mMKM prediction exhibiting superior agreement with measurements both in vitro and in vivo across the 3 investigated end points. LEM1 and LEM4 performed their best in the highest LET conditions but yielded overestimations and underestimations in low/midrange LET conditions, respectively, as demonstrated by comparison with measurements. Additionally, the analysis of patient treatment plans revealed substantial variability across the investigated models (±20%-30% uncertainty), largely dependent on the selected model and absolute values for input tissue parameters α_x and β_x.

CONCLUSION

RBE dependencies in vitro, in vivo, and in silico were investigated with respect to various clinically relevant end points in the context of tumor-specific tissue radio-sensitivity assignment and accurate RBE modeling. Discovered model trends and performances advocate upgrading current treatment planning schemes in carbon ion therapy and call for verification via clinical outcome analysis with large patient cohorts.

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.

Microdosimetric calculations of the direct DNA damage induced by low energy electrons using the Geant4-DNA Monte Carlo code

To calculate the yield of direct DNA damage induced by low energy electrons using Monte Carlo generated microdosimetric spectra at the nanometer scale and examine the influence of various simulation inputs. The potential of classical microdosimetry to offer a viable and simpler alternative to more elaborate mechanistic approaches for practical applications is discussed. Track-structure simulations with the Geant4-DNA low-energy extension of the Geant4 Monte Carlo toolkit were used for calculating lineal energy spectra in spherical volumes with dimensions relevant to double-strand-break (DSB) induction. The microdosimetric spectra were then used to calculate the yield of simple and clustered DSB based on literature values of the threshold energy of DNA damage. The influence of the different implementations of the dielectric function of liquid water available in Geant4-DNA (Option 2 and Option 4 constructors), as well as the effect of particle tracking cutoff energy and target size are examined. Frequency- and dose-mean lineal energies in liquid-water spheres of 2, 2.3, 2.6, and 3.4 nm diameter, as well as, number of simple and clustered DSB/Gy/cell are presented for electrons over the 100 eV to 100 keV energy range. Results are presented for both the 'default' (Option 2) and 'Ioannina' (Option 4) physics models of Geant4-DNA applying several commonly used tracking cutoff energies (10, 20, 50, 100 eV). Overall, the choice of the physics model and target diameter has a moderate effect (up to ~10%-30%) on the DSB yield whereas the effect of the tracking cutoff energy may be significant (>100%). Importantly, the yield of both simple and clustered DSB was found to vary significantly (by a factor of 2 or more) with electron energy over the examined range. The yields of electron-induced simple and clustered DSB exhibit a strong energy dependence over the 100 eV-100 keV range with implications to radiation quality issues. It is shown that a classical microdosimetry approach for the calculation of DNA damage based on lineal energy spectra in nanometer-size targets predicts comparable results to computationally intensive mechanistic approaches which use detailed atomistic DNA geometries, thus, offering a relatively simple and robust alternative for some practical applications.

Comparative photon and proton dosimetry for patients with mediastinal lymphoma in the era of Monte Carlo treatment planning and variable relative biological effectiveness

Background

Existing pencil beam analytical (PBA) algorithms for proton therapy treatment planning are not ideal for sites with heterogeneous tissue density and do not account for the spatial variations in proton relative biological effectiveness (vRBE). Using a commercially available Monte Carlo (MC) treatment planning system, we compared various dosimetric endpoints between proton PBA, proton MC, and photon treatment plans among patients with mediastinal lymphoma.

Methods

Eight mediastinal lymphoma patients with both free breathing (FB) and deep inspiration breath hold (DIBH) CT simulation scans were analyzed. The original PBA plans were re-calculated with MC. New proton plans that used MC for both optimization and dose calculation with equivalent CTV/ITV coverage were also created. A vRBE model, which uses a published model for DNA double strand break (DSB) induction, was applied on MC plans to study the potential impact of vRBE on cardiac doses. Comparative photon plans were generated on the DIBH scan.

Results

Re-calculation of FB PBA plans with MC demonstrated significant under coverage of the ITV V99 and V95. Target coverage was recovered by re-optimizing the PT plan with MC with minimal change to OAR doses. Compared to photons with DIBH, MC-optimized FB and DIBH proton plans had significantly lower dose to the mean lung, lung V5, breast tissue, and spinal cord for similar target coverage. Even with application of vRBE in the proton plans, the putative increase in RBE at the end of range did not decrease the dosimetric advantages of proton therapy in cardiac substructures.

Conclusions

MC should be used for PT treatment planning of mediastinal lymphoma to ensure adequate coverage of target volumes. Our preliminary data suggests that MC-optimized PT plans have better sparing of the lung and breast tissue compared to photons. Also, the potential for end of range RBE effects are unlikely to be large enough to offset the dosimetric advantages of proton therapy in cardiac substructures for mediastinal targets, although these dosimetric findings require validation with late toxicity data.