Towards Achieving the Full Clinical Potential of Proton Therapy by Inclusion of LET and RBE Models

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.

The dirty and clean dose concept: Towards creating proton therapy treatment plans with a photon-like dose response

BACKGROUND

Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1.

PURPOSE

This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon-like dose response for OAR and, thus, less uncertainties when applying photon-based tolerance doses.

METHODS

The concept divides the 1.1-weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon-like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1-weighted dose, variable RBE-weighted dose using the Wedenberg RBE model and dose-average LETd distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives.

RESULTS

In the water phantom studies, LET thresholds between 1.5 and 2.5 keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1-weighted dose in the OARs was slightly increased (patient 1: 0.45 Gy(RBE), patient 2: 0.08 Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1-weighted dose in healthy brain tissue was observed (patient 1: 0.81 Gy(RBE), patient 2: 0.53 Gy(RBE)). The variation of NTCP values due to variation of α/β from 2 to 3 Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp).

CONCLUSIONS

The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon-like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon-based tolerance doses for OAR.

Monte Carlo simulations of cell survival in proton SOBP

Objective. The objective of this study is to develop a multi-scale modeling approach that accurately predicts radiation-induced DNA damage and survival fraction in specific cell lines.Approach. A Monte Carlo based simulation framework was employed to make the predictions. The FLUKA Monte Carlo code was utilized to estimate absorbed doses and fluence energy spectra, which were then used in the Monte Carlo Damage Simulation code to compute DNA damage yields in Chinese hamster V79 cell lines. The outputs were converted into cell survival fractions using a previously published theoretical model. To reduce the uncertainties of the predictions, new values for the parameters of the theoretical model were computed, expanding the database of experimental points considered in the previous estimation. Simulated results were validated against experimental data, confirming the applicability of the framework for proton beams up to 230 MeV. Additionally, the impact of secondary particles on cell survival was estimated.Main results. The simulated survival fraction versus depth in a glycerol phantom is reported for eighteen different configurations. Two proton spread out Bragg peaks at several doses were simulated and compared with experimental data. In all cases, the simulations follow the experimental trends, demonstrating the accuracy of the predictions up to 230 MeV.Significance. This study holds significant importance as it contributes to the advancement of models for predicting biological responses to radiation, ultimately contributing to more effective cancer treatment in proton therapy.

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.

The risk of radiation-induced neurocognitive impairment and the impact of sparing the hippocampus during pediatric proton cranial irradiation

BACKGROUND AND PURPOSE

Hippocampus is a central component for neurocognitive function and memory. We investigated the predicted risk of neurocognitive impairment of craniospinal irradiation (CSI) and the deliverability and effects of hippocampal sparing. The risk estimates were derived from published NTCP models. Specifically, we leveraged the estimated benefit of reduced neurocognitive impairment with the risk of reduced tumor control.

MATERIAL AND METHODS

For this dose planning study, a total of 504 hippocampal sparing intensity modulated proton therapy (HS-IMPT) plans were generated for 24 pediatric patients whom had previously received CSI. Plans were evaluated with respect to target coverage and homogeneity index to target volumes, maximum and mean dose to OARs. Paired t-tests were used to compare hippocampal mean doses and normal tissue complication probability estimates.

RESULTS

The median mean dose to the hippocampus could be reduced from 31.3 Gy_RBE to 7.3 Gy_RBE (p < .001), though 20% of these plans were not considered clinically acceptable as they failed one or more acceptance criterion. Reducing the median mean hippocampus dose to 10.6 Gy_RBE was possible with all plans considered as clinically acceptable treatment plans. By sparing the hippocampus to the lowest dose level, the risk estimation of neurocognitive impairment could be reduced from 89.6%, 62.1% and 51.1% to 41.0% (p < .001), 20.1% (p < .001) and 29.9% (p < .001) for task efficiency, organization and memory, respectively. Estimated tumor control probability was not adversely affected by HS-IMPT, ranging from 78.5 to 80.5% for all plans.

CONCLUSIONS

We present estimates of potential clinical benefit in terms of neurocognitive impairment and demonstrate the possibility of considerably reducing neurocognitive adverse effects, minimally compromising target coverage locally using HS-IMPT.

Proton radiotherapy in the treatment of IDH-mutant diffuse gliomas: an early experience from shanghai proton and heavy ion center

PURPOSE

According to the presence or absence of isocitrate dehydrogenase (IDH) mutation, the 2021 WHO classification system bisected diffuse gliomas into IDH-mutant tumors and IDH-wildtype tumors. This study was aimed to evaluate the outcomes of proton radiotherapy treating IDH-mutant diffuse gliomas.

PATIENTS AND METHODS

Between May 2015 and May 2022, a total of 52 consecutive patients with IDH-mutant diffuse gliomas were treated at Shanghai Proton and Heavy Ion Center. Tumor histologies were 33 cases of astrocytoma and 19 cases of oligodendroglioma. Tumor classified by WHO grade 2, 3 and 4 were 22, 25, and 5 cases, respectively. All 22 patients with WHO grade 2 tumors and one patient with brain stem WHO grade 4 tumor were irradiated with 54GyE. The other 29 patients with WHO grade 3 and 4 tumors were irradiated with 60GyE. Temozolomide was recommended to all patients, and was eventually conducted in 50 patients.

RESULTS

The median follow-up time was 21.7 months. The 12/24-month progression-free survival (PFS) and overall survival (OS) rates for the entire cohort were 97.6%/78.4% and 100%/91.0% group. Examined by both univariate and multivariate analysis, WHO grade of tumor were of the most significant impact for both PFS and OS. No severe acute toxicity (grade 3 or above) was found. In terms of late toxicity, grade 3 radio-necrosis was developed in one case of oligodendroglioma, WHO grade 3.

CONCLUSION

Proton radiotherapy produced a favorable outcome with acceptable adverse-effects in patients with IDH-mutant diffuse gliomas.

The dose accumulation and the impact of deformable image registration on dose reporting parameters in a moving patient undergoing proton radiotherapy

INTRODUCTION

Potential changes in patient anatomy during proton radiotherapy may lead to a deviation of the delivered dose. A dose estimate can be computed through a deformable image registration (DIR) driven dose accumulation. The present study evaluates the accumulated dose uncertainties in a patient subject to an inadvertent breathing associated motion.

MATERIALS AND METHODS

A virtual lung tumour was inserted into a pair of single participant landmark annotated computed tomography images depicting opposite breathing phases, with the deep inspiration breath-hold the planning reference and the exhale the off-reference geometry. A novel Monte Carlo N-Particle, Version 6 (MCNP6) dose engine was developed, validated and used in treatment plan optimization. Three DIR methods were compared and used to transfer the exhale simulated dose to the reference geometry. Dose conformity and homogeneity measures from International Committee on Radioactivity Units and Measurements (ICRU) reports 78 and 83 were evaluated on simulated dose distributions registered with different DIR algorithms.

RESULTS

The MCNP6 dose engine handled patient-like geometries in reasonable dose calculation times. All registration methods were able to align image associated landmarks to distances, comparable to voxel sizes. A moderate deterioration of ICRU measures was encountered in comparing doses in on and off-reference anatomy. There were statistically significant DIR driven differences in ICRU measures, particularly a 10% difference in the relative D_98% for planning tumour volume and in the 3 mm/3% gamma passing rate.

CONCLUSIONS

T he dose accumulation over two anatomies resulted in a DIR driven uncertainty, important in reporting the associated ICRU measures for quality assurance.

Further development of spinal cord retreatment dose estimation: including radiotherapy with protons and light ions

PURPOSE

A graphical user interface (GUI) was developed to aid in the assessment of changes in the radiation tolerance of spinal cord/similar central nervous system tissues with time between two individual treatment courses.

METHODS

The GUI allows any combination of photons, protons (or ions) to be used as the initial, or retreatment, radiotherapy courses. Allowances for clinical circumstances, of reduced tolerance, can also be made. The radiobiological model was published previously and has been incorporated with additional checks and safety features, to be as safe to use as possible. The proton option includes use of a fixed RBE of 1.1 (set as the default), or a variable RBE, the latter depending on the proton linear energy transfer (LET) for organs at risk. This second LET-based approach can also be used for ions, by changing the LET parameters.

RESULTS

GUI screenshots are used to show the input and output parameters for different clinical situations used in worked examples. The results from the GUI are in agreement with manual calculations, but the results are now rapidly available without tedious and error-prone manual computations. The software outputs provide a maximum dose limit boundary, which should not be exceeded. Clinicians may also choose to further lower the number of treatment fractions, whilst using the same dose per fraction (or conversely a lower dose per fraction but with the same number of fractions) in order to achieve the intended clinical benefit as safely as possible.

CONCLUSIONS

The new GUI will allow scientific-based estimations of time related radiation tolerance changes in the spinal cord and similar central nervous tissues (optic chiasm, brainstem), which can be used to guide the choice of retreatment dose fractionation schedules, with either photons, protons or ions.

Handling of beam spectra in training and application of proton RBE models

Published data from cell survival experiments are frequently used as training data for models of proton relative biological effectiveness (RBE). The publications rarely provide full information about the primary particle spectrum of the used beam, or its content of heavy secondary particles. The purpose of this paper is to assess to what extent heavy secondary particles may have been present in published cell survival experiments, and to investigate the impact of non-primary protons for RBE calculations in treatment planning. We used the Monte Carlo code Geant4 to calculate the occurrence of non-primary protons and heavier secondary particles for clinical protons beams in water for four incident energies in the [100, 250] MeV interval. We used the resulting spectra together with a conservative RBE parameterization and an RBE model to map both the rise of RBE at the beam entry surface due to heavy secondary particle buildup, and the difference in estimated RBE if non-primary protons are included or not in the beam quality metric. If included, non-primary protons cause a difference of 2% of the RBE in the plateau region of an spread out Bragg peak and 1% in the Bragg peak. Including non-primary protons specifically for RBE calculations will consequently have a negligible impact and can be ignored. A buildup distance in water of one millimeter was sufficient to reach an equilibrium state of RBE for the four incident energies selected. For the investigated experimental data, 83 out of the 86 data points were found to have been determined with at least that amount of buildup material. Hence, RBE model training data should be interpreted to include the contribution of heavy secondaries.

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.

Physical and Biological Characteristics of Particle Therapy for Oncologists

Particle therapy is a promising and evolving modality of radiotherapy that can be used to treat tumors that are radioresistant to conventional photon beam radiotherapy. It has unique biological and physical advantages compared with conventional radiotherapy. The characteristic feature of particle therapy is the "Bragg peak," a steep and localized peak of dose, that enables precise delivery of the radiation dose to the tumor while effectively sparing normal organs. Especially, the charged particles (e.g., proton, helium, carbon) cause a high rate of energy loss along the track, thereby leading to high biological effectiveness, which makes particle therapy attractive. Using this property, the particle beam induces more severe DNA double-strand breaks than the photon beam, which is less influenced by the oxygen level. This review describes the general biological and physical aspects of particle therapy for oncologists, including non-radiation oncologists and beginners in the field.

Fast neutron energy based modelling of biological effectiveness with implications for proton and ion beams

A practical neutron energy dependent RBE model has been developed, based on the relationship between a mono-energetic neutron energy and its likely recoil proton energy. Essentially, the linear energy transfer (LET) values of the most appropriate recoil proton energies are then used to modify the linear quadratic model radiosensitivities (α and β) from their reference LET radiation values to provide the RBE estimates. Experimental neutron studies published by Hall (including some mono-energetic beams ranging from 0.2 to 15 MeV), Broerse, Berry, and data from the Clatterbridge and Detroit clinical neutron beams, which all contain some data from a spectrum of neutron energies, are used to derive single effective neutron energies (NE_eff) for each spectral beam. These energies yield a recoil proton spectrum, but with an effective mean proton energy (being around 50% of NE_eff). The fractional increase in LET is given by the recoil proton LET divided by the proton (LET_U) value which provides the highest RBE. This ratio is then used to determine the change in the linear-quadratic model α and β parameters, from those of the reference radiation, to estimate the RBE. The predicted proton recoil RBE is then reasonably close to the experimental neutron RBE values found when taking into account the variation inherent in biological experiments. The work has some important consequences. The data of Hall et al (1975 Radiat. Res. 64 245-55) shows that the highest RBE values are found with neutron energies around 0.3-0.4 MeV, but this energy cannot possibly generate recoil proton energies which are higher, as necessary for a 0.68 MeV proton with a 30.5 keV μm^-1 LET_U (the LET value which provides the maximum obtainable RBE for a specified ion). For 0.4 MeV neutrons with proton recoil energies of around 0.2 MeV, the latter have a LET of around 62.88 keV μm^-1. This could have an impact on proton beam RBE modelling. However, this is compensated by finding that the maximum radiosensitivity for mono-energetic neutrons was around 1.7 times larger than previously suggested from experimental ion beam studies, probably due to the necessary spreading out of Bragg peaks for ion beam experimental purposes, sampling errors and particle range considerations. This semi-empirical model can be used with minimal computer support and could have applications in ionic beams and in radioprotection.

Variation in relative biological effectiveness for cognitive structures in proton therapy of pediatric brain tumors

BACKGROUND

Clinically, a constant value of 1.1 is used for the relative biological effectiveness (RBE) of protons, whereas in vitro the RBE has been shown to vary depending on physical dose, tissue type, and linear energy transfer (LET). As the LET increases at the distal end of the proton beam, concerns exist for an elevated RBE in normal tissues. The aim of this study was therefore to investigate the heterogeneity of RBE to brain structures associated with cognition (BSCs) in pediatric suprasellar tumors.

MATERIAL AND METHODS

Intensity-modulated proton therapy (IMPT) plans for 10 pediatric craniopharyngioma patients were re-calculated using 11 phenomenological and two plan-based variable RBE models. Based on LET, tissue dependence and number of data points used to fit the models, the three RBE models considered the most relevant for the studied endpoint were selected. Thirty BSCs were investigated in terms of RBE and dose/volume parameters.

RESULTS

For a representative patient, the median (range) dose-weighted mean RBE (RBE_d) across all BSCs from the plan-based models was among the lowest (1.09 (1.02-1.52) vs. the phenomenological models at 1.21 (0.78-2.24)). Omitting tissue dependency resulted in RBE_d at 1.21 (1.04-2.24). Across all patients, the narrower RBE model selection gave median RBE_d values from 1.22 to 1.30.

CONCLUSION

For all BSCs, there was a systematic model-dependent variation in RBE_d, mirroring the uncertainty in biological effects of protons. According to a refined selection of in vitro models, the RBE variation across BSCs was in effect underestimated when using a fixed RBE of 1.1.

RBE for proton radiation therapy - a Nordic view in the international perspective

BACKGROUND

This paper presents an insight into the critical discussions and the current strategies of the Nordic countries for handling the variable proton relative biological effectiveness (RBE) as presented at The Nordic Collaborative Workshop for Particle Therapy that took place at the Skandion Clinic on 14th and 15th of November 2019.

MATERIAL AND METHODS

In the current clinical practice at the two proton centres in operation at the date, Skandion Clinic, and the Danish Centre for Particle Therapy, a constant proton RBE of 1.1 is applied. The potentially increased effectiveness at the end of the particle range is however considered at the stage of treatment planning at both places based on empirical observations and knowledge. More elaborated strategies to evaluate the plans and mitigate the problem are intensely investigated internationally as well at the two centres. They involve the calculation of the dose-averaged linear energy transfer (LET_d) values and the assessment of their distributions corroborated with the distribution of the dose and the location of the critical clinical structures.

RESULTS

Methods and tools for LET_d calculations are under different stages of development as well as models to account for the variation of the RBE with LET_d, dose per fraction, and type of tissue. The way they are currently used for evaluation and optimisation of the plans and their robustness are summarised. A critical but not exhaustive discussion of their potential future implementation in the clinical practice is also presented.

CONCLUSIONS

The need for collaboration between the clinical proton centres in establishing common platforms and perspectives for treatment planning evaluation and optimisation is highlighted as well as the need of close interaction with the research academic groups that could offer a complementary perspective and actively help developing methods and tools for clinical implementation of the more complex metrics for considering the variable effectiveness of the proton beams.

Clinical Radiobiology of Fast Neutron Therapy: What Was Learnt?

Neutron therapy was developed from neutron radiobiology experiments, and had identified a higher cell kill per unit dose and an accompanying reduction in oxygen dependency. But experts such as Hal Gray were sceptical about clinical applications, for good reasons. Gray knew that the increase in relative biological effectiveness (RBE) with dose fall-off could produce marked clinical limitations. After many years of research, this treatment did not produce the expected gains in tumour control relative to normal tissue toxicity, as predicted by Gray. More detailed reasons for this are discussed in this paper. Neutrons do not have Bragg peaks and so did not selectively spare many tissues from radiation exposure; the constant neutron RBE tumour prescription values did not represent the probable higher RBE values in late-reacting tissues with low α/β values; the inevitable increase in RBE as dose falls along a beam would also contribute to greater toxicity than in a similar megavoltage photon beam. Some tissues such as the central nervous system white matter had the highest RBEs partly because of the higher percentage hydrogen content in lipid-containing molecules. All the above factors contributed to disappointing clinical results found in a series of randomised controlled studies at many treatment centres, although at the time they were performed, neutron therapy was in a catch-up phase with photon-based treatments. Their findings are summarised along with their technical aspects and fractionation choices. Better understanding of fast neutron experiments and therapy has been gained through relatively simple mathematical models—using the biological effective dose concept and incorporating the RBEmax and RBEmin parameters (the limits of RBE at low and high dose, respectively—as shown in the Appendix). The RBE itself can then vary between these limits according to the dose per fraction used. These approaches provide useful insights into the problems that can occur in proton and ion beam therapy and how they may be optimised. This is because neutron ionisations in living tissues are mainly caused by recoil protons of energy proportional to the neutron energy: these are close to the proton energies that occur close to the Bragg peak region. To some extent, neutron RBE studies contain the highest RBE ranges found within proton and ion beams near Bragg peaks. In retrospect, neutrons were a useful radiobiological tool that has continued to inform the scientific and clinical community about the essential radiobiological principles of all forms of high linear energy transfer therapy. Neutron radiobiology and its implications should be taught on training courses and studied closely by clinicians, physicists, and biologists engaged in particle beam therapies.

RBE variation in prostate carcinoma cells in active scanning proton beams: In-vitro measurements in comparison with phenomenological models

PURPOSE

In-vitro radiobiological studies are essential for modelling the relative biological effectiveness (RBE) in proton therapy. The purpose of this study was to experimentally determine the RBE values in proton beams along the beam path for human prostate carcinoma cells (Du-145). RBE-dose and RBE-LET_d (dose-averaged linear energy transfer) dependencies were investigated and three phenomenological RBE models, i.e. McNamara, Rørvik and Wilkens were benchmarked for this cell line.

METHODS

Cells were placed at multiple positions along the beam path, employing an in-house developed solid phantom. The experimental setup reflected the clinical prostate treatment scenario in terms of field size, depth, and required proton energies (127.2-180.1 MeV) and the physical doses from 0.5 to 6 Gy were delivered. The reference irradiation was performed with 200 kV X-ray beams. Respective (α/β) values were determined using the linear quadratic model and LET_d was derived from the treatment planning system at the exact location of cells.

RESULTS AND CONCLUSION

Independent of the cell survival level, all experimental RBE values were consistently higher in the target than the generic clinical RBE value of 1.1; with the lowest RBE value of 1.28 obtained at the beginning of the SOBP. A systematic RBE decrease with increasing dose was observed for the investigated dose range. The RBE values from all three applied models were considerably smaller than the experimental values. A clear increase of experimental RBE values with LET_d parameter suggests that proton LET must be taken into consideration for this low (α/β) tissue.

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.

Inter-patient variations in relative biological effectiveness for cranio-spinal irradiation with protons

Cranio-spinal irradiation (CSI) using protons has dosimetric advantages compared to photons and is expected to reduce risk of adverse effects. The proton relative biological effectiveness (RBE) varies with linear energy transfer (LET), tissue type and dose, but a variable RBE has not replaced the constant RBE of 1.1 in clinical treatment planning. We examined inter-patient variations in RBE for ten proton CSI patients. Variable RBE models were used to obtain RBE and RBE-weighted doses. RBE was quantified in terms of dose weighted organ-mean RBE ([Formula: see text] = mean RBE-weighted dose/mean physical dose) and effective RBE of the near maximum dose (D2%), i.e. RBED2% = [Formula: see text], where subscripts RBE and phys indicate that the D2% is calculated based on an RBE model and the physical dose, respectively. Compared to the median [Formula: see text] of the patient population, differences up to 15% were observed for the individual [Formula: see text] values found for the thyroid, while more modest variations were seen for the heart (6%), lungs (2%) and brainstem (<1%). Large inter-patient variation in RBE could be correlated to large spread in LET and dose for these organs at risk (OARs). For OARs with small inter-patient variations, the results show that applying a population based RBE in treatment planning may be a step forward compared to using RBE of 1.1. OARs with large inter-patient RBE variations should ideally be selected for patient-specific biological or RBE robustness analysis if the physical doses are close to known dose thresholds.

Physical characteristics at the turnover-points of relative biological effect (RBE) with linear energy transfer (LET)

This paper considers the kinematic physical characteristics of ionic beams for maximum relative bio-effectiveness (RBE). RBE studies, based on heterogenous cell survival studies at different laboratories and linear energy transfer (LET) conditions for proton, helium, carbon, neon and argon ions, have been further analysed to determine the LET_U values where RBE is maximal and the LET-RBE relationship has a turnover point. The SRIM stopping power software and other classical equations are used to determine the particle velocities, kinetic energies and their effective ionic charges at LET_U. The estimated mean LET_U values increase with atomic number (Z). Each LET_U has a unique relativistic velocity, β  =  v/c, the velocity v expressed as a fraction of the speed of light, (c), and which is non-linearly proportional to Z. For ions helium and heavier ions, these velocities indicate that the effective charge Z ^* is around 0.99 of the full Z value at each LET_U, with remarkably stable velocities of 3-4 nm · fs^-1 per nucleon, or around 6-8 nm · fs^-1 per unit Z. For Z  =  1, (protons and deuterium) some values fall outside these ranges but the result depends on the mix of proton and deuterium used in experiments. An alternative index of βA/Z ² (A is the atomic mass number), suggests an average velocity of around 15 nm · fs^-1 for each particle at LET_U. These distances, traversed in the time of the radiochemical process initiation, are all within the dimensions of the nucleosome. Curve fitting of the data set provides a predictive equation for LET_U for any ion, as LET_U  =  30.4  +  [Formula: see text] (1  -  Exp[-0.61  √  (Z  -  1)]) when normalised to protons. These data can be extended to heavier ions such as silicon and iron and give values that are consistent with experimental data. Each ion probably has a unique LET_U value. Kinematic studies show maximum bio-effectiveness occurs at particle velocities where electron stripping remains at around 99% and where the velocity per nucleon is around 3-4 nm · fs^-1. This study enhances the limited prior knowledge about the physical conditions of particle beams that provide maximum bio-effectiveness, with applications in particle radiotherapy, radiation protection and space travel.

Modelling variable proton relative biological effectiveness for treatment planning

Dose in proton radiotherapy is generally prescribed by scaling the physical proton dose by a constant value of 1.1. Relative biological effectiveness (RBE) is defined as the ratio of doses required by two radiation modalities to cause the same level of biological effect. The adoption of an RBE of 1.1. assumes that the biological efficacy of protons is similar to photons, allowing decades of clinical dose prescriptions from photon treatments and protocols to be utilized in proton therapy. There is, however, emerging experimental evidence that indicates that proton RBE varies based on technical, tissue and patient factors. The notion that a single scaling factor may be used to equate the effects of photons and protons across all biological endpoints and doses is too simplistic and raises concern for treatment planning decisions. Here, we review the models that have been developed to better predict RBE variations in tissue based on experimental data as well as using a mechanistic approach.

Using the Proton Energy Spectrum and Microdosimetry to Model Proton Relative Biological Effectiveness

PURPOSE

We introduce a methodology to calculate the microdosimetric quantity dose-mean lineal energy for input into the microdosimetric kinetic model (MKM) to model the relative biological effectiveness (RBE) of proton irradiation experiments.

METHODS AND MATERIALS

The data from 7 individual proton RBE experiments were included in this study. In each experiment, the RBE at several points along the Bragg curve was measured. Monte Carlo simulations to calculate the lineal energy probability density function of 172 different proton energies were carried out with use of Geant4 DNA. We calculated the fluence-weighted lineal energy probability density function (f_w(y)), based on the proton energy spectra calculated through Monte Carlo at each experimental depth, calculated the dose-mean lineal energy y_D¯ for input into the MKM, and then computed the RBE. The radius of the domain (r_d) was varied to reach the best agreement between the MKM-predicted RBE and experimental RBE. A generic RBE model as a function of dose-averaged linear energy transfer (LET_D) with 1 fitting parameter was presented and fit to the experimental RBE data as well to facilitate a comparison to the MKM.

RESULTS

Both the MKM and LET_D-based models modeled the RBE from experiments well. Values for r_d were similar to those of other cell lines under proton irradiation that were modeled with the MKM. Analysis of the performance of each model revealed that neither model was clearly superior to the other.

CONCLUSIONS

Our 3 key accomplishments include the following: (1) We developed a method that uses the proton energy spectra and lineal energy distributions of those protons to calculate dose-mean lineal energy. (2) We demonstrated that our application of the MKM provides theoretical validation of proton irradiation experiments that show that RBE is significantly greater than 1.1. (3) We showed that there is no clear evidence that the MKM is better than LET_D-based RBE models.

Fixed- versus Variable-RBE Computations for Intensity Modulated Proton Therapy

Purpose

To evaluate how using models of proton therapy that incorporate variable relative biological effectiveness (RBE) versus the current practice of using a fixed RBE of 1.1 affects dosimetric indices on treatment plans for large cohorts of patients treated with intensity modulated proton therapy (IMPT).

Methods and Materials

Treatment plans for 4 groups of patients who received IMPT for brain, head-and-neck, thoracic, or prostate cancer were selected. Dose distributions were recalculated in 4 ways: 1 with a fast-dose Monte Carlo calculator with fixed RBE and 3 with RBE calculated to 3 different models—McNamara, Wedenberg, and repair-misrepair-fixation. Differences among dosimetric indices (D02, D50, D98, and mean dose) for target volumes and organs at risk (OARs) on each plan were compared between the fixed-RBE and variable-RBE calculations.

Results

In analyses of all target volumes, for which the main concern is underprediction or RBE less than 1.1, none of the models predicted an RBE less than 1.05 for any of the cohorts. For OARs, the 2 models based on linear energy transfer, McNamara and Wedenberg, systematically predicted RBE >1.1 for most structures. For the mean dose of 25% of the plans for 2 OARs, they predict RBE equal to or larger than 1.4, 1.3, 1.3, and 1.2 for brain, head-and-neck, thorax, and prostate, respectively. Systematically lower increases in RBE are predicted by repair-misrepair-fixation, with a few cases (eg, femur) in which the RBE is less than 1.1 for all plans.

Conclusions

The variable-RBE models predict increased doses to various OARs, suggesting that strategies to reduce high-dose linear energy transfer in critical structures should be developed to minimize possible toxicity associated with IMPT.

Exploration and application of phenomenological RBE models for proton therapy

The relative biological effectiveness (RBE) of protons varies with multiple physical and biological factors. Phenomenological RBE models have been developed to include such factors in the estimation of a variable RBE, in contrast to the clinically applied constant RBE of 1.1. In this study, eleven published phenomenological RBE models and two plan-based models were explored and applied to simulated patient cases. All models were analysed with respect to the distribution and range of linear energy transfer (LET) and reference radiation fractionation sensitivity ((α/β) _x ) of their respective experimental databases. Proton therapy plans for a spread-out Bragg peak in water and three patient cases (prostate adenocarcinoma, pituitary adenoma and thoracic sarcoma) were optimised using an RBE of 1.1 in the Eclipse^™ treatment planning system prior to recalculation and modelling in the FLUKA Monte Carlo code. Model estimated dose-volume parameters for the planning target volumes (PTVs) and organs at risk (OAR) were compared. The experimental in vitro databases for the various models differed greatly in the range of (α/β) _x values and dose-averaged LET (LET_d). There were significant variations between the model estimations, which arose from fundamental differences in the database definitions and model assumptions. The greatest variations appeared in organs with low (α/β) _x and high LET_d, e.g. biological doses given to late responding OARs located distal to the target in the treatment field. In general, the variation in maximum dose (D_2%) was larger than the variation in mean dose and other dose metrics, with D_2% of the left optic nerve ((α/β) _x   =  2.1 Gy) in the pituitary adenoma case showing the greatest discrepancies between models: 28-52 Gy(RBE), while D_2% for RBE_1.1 was 30 Gy(RBE). For all patient cases, the estimated mean RBE to the PTV was in the range 1.09-1.29 ((α/β) _x   =  1.5/3.1/10.6 Gy). There were considerable variations between the estimations of RBE and RBE-weighted doses from the different models. These variations were a consequence of fundamental differences in experimental databases, model assumptions and regression techniques. The results from the implementation of RBE models in dose planning studies should be evaluated in light of these deviations.

MONTE CARLO SIMULATIONS OF SPATIAL LET DISTRIBUTIONS IN CLINICAL PROTON BEAMS

The linear energy transfer (LET) is commonly used as a parameter which describes the quality of the radiation applied in radiation therapy with fast ions. In particular in proton therapy, most models which predict the radiobiological properties of the applied beam, are fitted to the dose-averaged LET, LETd. The related parameter called the fluence- or track-averaged LET, LETt, is less frequently used. Both LETt and in particular LETd depends profoundly on the encountered secondary particle spectrum. For proton beams including all secondary particles, LETd may reach more than 3 keV/um in the entry channel of the proton field. However, typically the charged particle spectrum is only averaged over the primary and secondary protons, which is in the order of 0.5 keV/um for the same region. This is equal to assuming that the secondary particle spectrum from heavier ions is irrelevant for the resulting radiobiology, which is an assertion in the need of closer investigation. Models which rely on LETd should also be clear on what type of LETd is used, which is not always the case. Within this work, we have extended the Monte Carlo particle transport code SHIELD-HIT12A to provide dose- and track-average LET-maps for ion radiation therapy treatment plans.

The Radiobiology of Proton Therapy: Challenges and Opportunities Around Relative Biological Effectiveness

With the current UK expansion of proton therapy there is a great opportunity for clinical oncologists to develop a translational interest in the associated scientific base and clinical results. In particular, the underpinning controversy regarding the conversion of photon dose to proton dose by the relative biological effectiveness (RBE) must be understood, including its important implications. At the present time, the proton prescribed dose includes an RBE of 1.1 regardless of tissue, tumour and dose fractionation. A body of data has emerged against this pragmatic approach, including a critique of the existing evidence base, due to choice of dose, use of only acute-reacting in vivo assays, analysis methods and the reference radiations used to determine the RBE. Modelling systems, based on the best available scientific evidence, and which include the clinically useful biological effective dose (BED) concept, have also been developed to estimate proton RBEs for different dose and linear energy transfer (LET) values. The latter reflect ionisation density, which progressively increases along each proton track. Late-reacting tissues, such as the brain, where α/β = 2 Gy, show a higher RBE than 1.1 at a low dose per fraction (1.2-1.8 Gy) at LET values used to cover conventional target volumes and can be much higher. RBE changes with tissue depth seem to vary depending on the method of beam delivery used. To reduce unexpected toxicity, which does occasionally follow proton therapy, a more rational approach to RBE allocation, using a variable RBE that depends on dose per fraction and the tissue and tumour radiobiological characteristics such as α/β, is proposed.

Hypofractionated high-energy proton-beam irradiation is an alternative treatment for WHO grade I meningiomas

Background

Radiation treatment is commonly employed in the treatment of meningiomas. The aim of this study was to evaluate the effectiveness and safety of hypofractionated high-energy proton therapy as adjuvant or primary treatment for WHO grade I meningiomas.

Method

A total of 170 patients who received irradiation with protons for grade I meningiomas between 1994 and 2007 were included in the study. The majority of the tumours were located at the skull base (n = 155). Eighty-four patients were treated post subtotal resection, 42 at tumour relapse and 44 with upfront radiotherapy after diagnosis based on the typical radiological image. Irradiation was given in a hypofractionated fashion (3–8 fractions, usually 5 or 6 Gy) with a mean dose of 21.9 Gy (range, 14–46 Gy). All patients were planned for follow-up with clinical controls and magnetic resonance imaging scans at 6 months and 1, 2, 3, 5, 7 and 10 years after treatment. The median follow-up time was 84 months. Age, gender, tumour location, Simpson resection grade and target volume were assessed as possible prognostic factors for post-irradiation tumour progression and radiation related complications.

Results

The actuarial 5- and 10-year progression-free survival rates were 93% and 85% respectively. Overall mortality rate was 13.5%, while disease-specific mortality was 1.7% (3/170 patients). Older patients and patients with tumours located in the middle cranial fossa had a lower risk for tumour progression. Radiation-related complications were seen in 16 patients (9.4%), with pituitary insufficiency being the most common. Tumour location in the anterior cranial fossa was the only factor that significantly increased the risk of complications.

Conclusions

Hypofractionated proton-beam radiation therapy may be used particularly in the treatment of larger World Health Organisation grade I meningiomas not amenable to total surgical resection. Treatment is associated with high rates of long-term tumour growth control and acceptable risk for complications.

Special radiobiological features of second cancer risk after particle radiotherapy

In absolute terms: second cancer risks from radiotherapy of first cancers in adults are small compared to the benefits from radiotherapy but this is not so for radiotherapy of childhood cancers. Moreover, the radiation dose dependence of cancer induction differs between organs and tissues. The organ-specific dose dependence of second cancer risks may indicate the existence of different radiobiological mechanisms. As an inevitable consequence of the age dependence of organ sensitivity to second cancer induction, the organ/tissue weighting factors which have been proposed by ICRP for calculating effective dose (the dose unit Sv) and for risk estimation in the general population should not be used in medical radiation exposures. In adult cancer radiotherapy, the most common unwanted effect is local tumour recurrence whereas both, severe late normal tissue damage and radiation-induced second cancers are rare, around 1% of locally controlled cancer patients. In childhood cancers, local failures are rare (<10% in some cancers) yet second cancers are more common than uncontrolled primaries. The main reason for considering particle radiotherapy for childhood cancers is the possibility to exploit their physical characteristics to reduce the radiation exposure to organs and tissues close to and distant from the primary cancer which is to be targeted. However, the relative biological effectiveness of the radiation doses within the proton beam is not a constant and the relative biological effectiveness of the neutrons is not known as far as the mechanisms of late normal tissue damage and second cancer risk are concerned. In view of the highly charged discussions of the potential risks of treatment-induced seecond cancers from the neutron contamination of exposure doses in out-of-PTV critical organs a comprehensive European project called ANDANTE was performed which integrated the disciplines of radiation physics, molecular biology, systems biology modelling and epidemiology in order to investigate the RBE of induction of cancer from exposure to neutrons compared to photons. Since out-of-field "effective" neutron doses from proton therapy are smaller than the photon stray doses whichever reasonable RBE is chosen for comparison, and since the absolute risk of radiation-induced second cancer rates are in the order of 1% in the cohorts of adult patients who have been treated in the past with methods which caused relatively high out-of-field doses to large body volumes, it is highly unlikely that such patients treated in future with highly conformal particle therapy are at a higher radiation-induced second cancer risk than those patients treated with photons and described before. Still, the potential risks of second cancers from scattered proton radiotherapy for childhood cancers may cause concern. Yet, the overall risk of undesired consequences of radiation exposure of children which are more complex and manifold than in adult patients (including developmental, neurocognitive, hormonal and growth impairment effects) are likely to be very much reduced by the better focussing of the radiation dose in the target offered by particle radioherapy. This benefit may far outweigh the still hypothetical second cancer risk from particle radiotherapy in pediatric radiotherapy.

Radiobiological issues in proton therapy

BACKGROUND

The relative biological effectiveness (RBE) for particle therapy is a complex function of particle type, radiation dose, linear energy transfer (LET), cell type, endpoint, etc. In the clinical practice of proton therapy, the RBE is assumed to have a fixed value of 1.1. This assumption, along with the effects of physical uncertainties, may mean that the biologically effective dose distributions received by the patient may be significantly different from what is seen on treatment plans. This may contribute to unforeseen toxicities and/or failure to control the disease. Variability of Proton RBE: It has been shown experimentally that proton RBE varies significantly along the beam path, especially near the end of the particle range. While there is now an increasing acceptance that proton RBE is variable, there is an ongoing debate about whether to change the current clinical practice. Clinical Evidence: A rationale against the change is the uncertainty in the models of variable RBE. Secondly, so far there is no clear clinical evidence of the harm of assuming proton RBE to be 1.1. It is conceivable, however, that the evidence is masked partially by physical uncertainties. It is, therefore, plausible that reduction in uncertainties and their incorporation in the estimation of dose actually delivered may isolate and reveal the variability of RBE in clinical practice. Nevertheless, clinical evidence of RBE variability is slowly emerging as more patients are treated with protons and their response data are analyzed. Modelling and Incorporation of RBE in the Optimization of Proton Therapy: The improvement in the knowledge of RBE could lead to better understanding of outcomes of proton therapy and in the improvement of models to predict RBE. Prospectively, the incorporation of such models in the optimization of intensity-modulated proton therapy could lead to improvements in the therapeutic ratio of proton therapy.

Relating the proton relative biological effectiveness to tumor control and normal tissue complication probabilities assuming interpatient variability in α/β

BACKGROUND

Proton therapy uses a constant relative biological effectiveness (RBE) of 1.1. The use of variable RBE values has been suggested but is currently not feasible due to uncertainties. The impact of variable RBE has solely been studied using dosimetric indices. This work elucidates the impact of RBE variations on tumor control and normal tissue complication probabilities (TCP/NTCP).

METHODS

Models to estimate TCP and NTCP were used in combination with an empirical proton RBE model. Variations in outcome as a function of linear-quadratic model parameters for cellular radiosensitivity were determined for TCP in prostate and ependymoma. In addition, NTCP analysis was done for brainstem necrosis.

RESULTS

Considering a variable proton RBE as a dose-modifying factor for prescription doses and dose constraints is misleading, as TCP/NTCP do not simply scale with RBE. The dependency of RBE on α/β cannot be interpreted independent of TCP/NTCP because variations in radiosensitivity affect both photon and proton treatments. Assuming interpatient variability in radiosensitivity results in lower TCP for patients with low α/β. In proton therapy, the magnitude of TCP variations is reduced due to an RBE increase as α/β decreases. The TCP in proton therapy is less affected by interpatient variability in α/β. On the other hand, patients with a lower α/β would have a lower complication probability, which is counteracted by an increase in RBE as α/β decreases. Toxicities in proton therapy would be more affected by α/β variations compared to photon therapy.

CONCLUSIONS

Assessment of variable RBE in proton therapy should be based on TCP and NTCP. Potential interpatient variability in radiosensitivity causes a smaller variance in TCP but a larger variance in NTCP for proton patients. The relative TCP as a function of α/β was found to be higher than the RBE, whereas the relative NTCP was lower than a calculated RBE.

Clinical radiobiology of proton therapy: modeling of RBE

PURPOSE

To better estimate relative biological effectiveness (RBE) in therapeutic proton beams by using a modeled approach, in order to improve their clinical safety and effectiveness.

INTRODUCTION

Concerns exist about the 1.1 RBE used in proton therapy, since it may lead to unintentional over- and under-dosage in patients and so lead to unexpected clinical outcomes. Late reacting normal tissues (with low α/β values), might be overdosed if RBE >1.1; very radiosensitive tumors (with high α/β), might be under-dosed if RBE <1.1. Some physicists recommend ignoring RBE in favor of a LET × dose product to predict effects.

MATERIAL AND METHODS

Extensive linear-quadratic based modeling is scaled between a standard hospital megavoltage photon reference radiation (low LET of 0.22 keV μm^-1) α and β values and their values at higher LETs, representative of the middle and end of the SOBPs. A previously published energy-efficiency model provide RBE estimates for different α/β (2-27 Gy). The concept of using a LET × dose product is assessed by comparing it with surviving fraction and the equivalent dose in 2 Gy fractions (EQD-2).

RESULTS

Low α/β value biosystems have the widest RBE ranges with dose per fraction changes and increasing LET, often above 1.1 even within the SOBP LET range, with lower values at higher dose per fraction. Highly radiosensitive tumors (α/β 10-27 Gy) have the lowest RBEs, often below 1.1, and are not fraction-sensitive. RBE's generally increase with LET, so curtailment of LET in normal tissues is important. The LET × dose product is insufficiently discriminating when compared with surviving fraction and biological effective dose (BED) or EQD-2.

CONCLUSIONS

An overall research framework is suggested. Proton therapy advantages will only be fully realized if reasonably correct RBE values are used.

Proton radiobiology and its clinical implications

Denser ionisation clustering and complex DNA damage in proton Bragg peaks far exceeds that seen with conventional X-rays. This results in more efficient cell sterilisation, quantified by the relative biological effectiveness (RBE). Currently, a 1.1 RBE is used to determine the clinical proton doses by dividing the usual X-rays dose by this amount. This number, derived from short-term experiments, has been criticised as being irrelevant to late normal tissue (NT) effects following radiotherapy and included many control irradiations using lower voltage X-rays (with elevated RBE values) than those used in the clinic. In principle, an increased RBE could be used for each organ at risk, by using extensions of the clinically successful linear quadratic model.

Protons undoubtedly reduce or eliminate NT radiation dose in tissues distantly located from a tumour, but the necessity to include NT margins around a tumour can result in a higher volume of NT than tumour being irradiated. Deleterious side-effects can follow if the NT RBE exceeds 1.1, including in tissue very close to these margins and which are only partially spared.

Use of a constant 1.1 RBE can ‘overdose’ NT, which may require a greater dose reduction such as 1.2 in the brain; some tumours may be ‘under-dosed’ (since they might require a lesser or no reduction in dose). More sophisticated proton experiments show that RBE values of 1.1–1.5 and higher occur in some situations. There are now mathematical models of varying degrees of complexity that can estimate the RBE from the dose, LET and the low-LET radiosensitivities. True multidisciplinary cooperation is required to implement such new ideas in proton therapy in order to improve safety and effectiveness.

Lateral variations of radiobiological properties of therapeutic fields of 1H, 4He, 12C and 16O ions studied with Geant4 and microdosimetric kinetic model

As known, in cancer therapy with ion beams the relative biological effectiveness (RBE) of ions changes in the course of their propagation in tissues. Such changes are caused not only by increasing the linear energy transfer (LET) of beam particles with the penetration depth towards the Bragg peak, but also by nuclear reactions induced by beam nuclei leading to the production of various secondary particles. Although the changes of RBE along the beam axis have been studied quite well, much less attention has been paid to the evolution of RBE in the transverse direction, perpendicular to the beam axis. In order to fill this gap, we simulated radiation fields of ¹H, ⁴He, ¹²C and ¹⁶O nuclei of 20 mm in diameter by means of a Geant4-based Monte Carlo model for heavy-ion therapy connected with the modified microdosimetric kinetic model to describe the response of normal ([Formula: see text] Gy) and early-responding ([Formula: see text] Gy) tissues. Depth and radial distributions of saturation-corrected dose-mean lineal energy, RBE and RBE-weighted dose are investigated for passive beam shaping and active beam scanning. The field of ⁴He has a small lateral spread as compared with ¹H field, and it is characterised by a modest lateral variation of RBE suggesting the use of fixed RBE values across the field transverse cross section at each depth. Reduced uncertainties of RBE on the boundary of a ⁴He treatment field can be advantageous in a specific case of an organ at risk located in lateral proximity to the target volume. It is found that the lateral distributions of RBE calculated for ¹²C and ¹⁶O fields demonstrate fast variations in the radial direction due to changes of dose and composition of secondary fragments in the field penumbra. Nevertheless, the radiation fields of all four projectiles at radii larger than 20 mm can be characterized by a common RBE value defined by tissue radiosensitivity. These findings can help, in particular, in accessing the transverse homogeneity of radiation fields of ions used in studies in vitro.

Inclusion of a variable RBE into proton and photon plan comparison for various fractionation schedules in prostate radiation therapy

PURPOSE

A constant relative biological effectiveness (RBE) of 1.1 is currently used in proton radiation therapy to account for the increased biological effectiveness compared to photon therapy. However, there is increasing evidence that proton RBE vary with the linear energy transfer (LET), the dose per fraction, and the type of the tissue. Therefore, this study aims to evaluate the impact of disregarding variations in RBE when comparing proton and photon dose plans for prostate treatments for various fractionation schedules using published RBE models and several α/β assumptions.

METHODS

Photon and proton dose plans were created for three generic prostate cancer cases. Three BED_3Gy equivalent schedules were studied, 78, 57.2, and 42.8 Gy in 39, 15, and 7 fractions, respectively. The proton plans were optimized assuming a constant RBE of 1.1. By using the Monte Carlo calculated dose-averaged LET (LET_d ) distribution and assuming α/β values on voxel level, three variable RBE models were applied to the proton dose plans. The impact of the variable RBE was studied in the plan comparison, which was based on the dose distribution, DVHs, and normal tissue complication probabilities (NTCP) for the rectum. Subsequently, the physical proton dose was reoptimized for each proton plan based on the LET_d distribution, to achieve a homogeneous RBE-weighted target dose when applying a specific RBE model and still fulfill the clinical goals for the rectum and bladder.

RESULTS

All the photon and proton plans assuming RBE = 1.1 met the clinical goals with similar target coverage. The proton plans fulfilled the robustness criteria in terms of range and setup uncertainty. Applying the variable RBE models generally resulted in higher target doses and rectum NTCP compared to the photon plans. The increase was most pronounced for the fractionation dose of 2 Gy(RBE), whereas it was of less magnitude and more dependent on model and α/β assumption for the hypofractionated schedules. The reoptimized proton plans proved to be robust and showed similar target coverage and doses to the organs at risk as the proton plans optimized with a constant RBE.

CONCLUSIONS

Model predicted RBE values may differ substantially from 1.1. This is most pronounced for fractionation doses of around 2 Gy(RBE) with higher doses to the target and the OARs, whereas the effect seems to be of less importance for the hypofractionated schedules. This could result in misleading conclusions when comparing proton plans to photon plans. By accounting for a variable RBE in the optimization process, robust and clinically acceptable dose plans, with the potential of lowering rectal NTCP, may be generated by reoptimizing the physical dose. However, the direction and magnitude of the changes in the physical proton dose to the prostate are dependent on RBE model and α/β assumptions and should therefore be used conservatively.

Why RBE must be a variable and not a constant in proton therapy

OBJECTIVE

This article considered why the proton therapy (PT) relative biological effect (RBE) should be a variable rather than a constant.

METHODS

The reasons for a variable proton RBE are enumerated, with qualitative and quantitative arguments. The heterogeneous data sets collated by Paganetti et al (2002) and the more homogeneous data of Britten et al (2013) are further analyzed using linear regression fitting and RBE-inclusive adaptations of the linear-quadratic (LQ) radiation model.

RESULTS

The in vitro data show RBE increasing as dose per fraction is lowered. In the Paganetti et al (2002) data sets, the differences between observed and expected effects are smaller when the LQ model is used, but with such data heterogeneity, firm statistical conclusions cannot be obtained. The more homogeneous data set shows an unequivocal variation in RBE with dose per faction. The in vivo data are inappropriate for assessments of late normal tissue effects in radiotherapy. Also, if there is the same degree of uncertainty in an RBE of 1.1 or in an RBE of 2-3 for C ions, the fractional and biological effective doses can vary considerably and be greater in the proton case. So, errors in RBE assignment are important for protons, just as with C ions.

CONCLUSION

Further experimental programmes are proposed, including late normal tissue end points. Better RBE allocations might further improve PT outcomes.

ADVANCES IN KNOWLEDGE

This study provides a rigorous critique of the 1.1 RBE used for protons, from theoretical and practical standpoints. Data analysis shows that the LQ model is more appropriate than simple linear regression. Comprehensive research programmes are suggested.

Nuclear physics in particle therapy: a review

Charged particle therapy has been largely driven and influenced by nuclear physics. The increase in energy deposition density along the ion path in the body allows reducing the dose to normal tissues during radiotherapy compared to photons. Clinical results of particle therapy support the physical rationale for this treatment, but the method remains controversial because of the high cost and of the lack of comparative clinical trials proving the benefit compared to x-rays. Research in applied nuclear physics, including nuclear interactions, dosimetry, image guidance, range verification, novel accelerators and beam delivery technologies, can significantly improve the clinical outcome in particle therapy. Measurements of fragmentation cross-sections, including those for the production of positron-emitting fragments, and attenuation curves are needed for tuning Monte Carlo codes, whose use in clinical environments is rapidly increasing thanks to fast calculation methods. Existing cross sections and codes are indeed not very accurate in the energy and target regions of interest for particle therapy. These measurements are especially urgent for new ions to be used in therapy, such as helium. Furthermore, nuclear physics hardware developments are frequently finding applications in ion therapy due to similar requirements concerning sensors and real-time data processing. In this review we will briefly describe the physics bases, and concentrate on the open issues.

Radiological protection in ion beam radiotherapy: practical guidance for clinical use of new technology

Recently introduced technologies in radiotherapy have significantly improved the clinical outcome for patients. Ion beam radiotherapy, involving proton and carbon ion beams, provides excellent dose distributions in targeted tumours, with reduced doses to the surrounding normal tissues. However, careful treatment planning is required in order to maximise the treatment efficiency and minimise the dose to normal tissues. Radiation exposure from secondary neutrons and photons, particle fragments, and photons from activated materials should also be considered for radiological protection of the patient and medical staff. Appropriate maintenance is needed for the equipment and air in the treatment room, which may be activated by the particle beam and its secondary radiation. This new treatment requires complex procedures and careful adjustment of parameters for each patient. Therefore, education and training for the personnel involved in the procedure are essential for both effective treatment and patient protection. The International Commission on Radiological Protection (ICRP) has provided recommendations for radiological protection in ion beam radiotherapy in Publication 127 Medical staff should be aware of the possible risks resulting from inappropriate use and control of the equipment. They should also consider the necessary procedures for patient protection when new technologies are introduced into clinical practice.

A phenomenological relative biological effectiveness (RBE) model for proton therapy based on all published in vitro cell survival data

Proton therapy treatments are currently planned and delivered using the assumption that the proton relative biological effectiveness (RBE) relative to photons is 1.1. This assumption ignores strong experimental evidence that suggests the RBE varies along the treatment field, i.e. with linear energy transfer (LET) and with tissue type. A recent review study collected over 70 experimental reports on proton RBE, providing a comprehensive dataset for predicting RBE for cell survival. Using this dataset we developed a model to predict proton RBE based on dose, dose average LET (LETd) and the ratio of the linear-quadratic model parameters for the reference radiation (α/β)x, as the tissue specific parameter. The proposed RBE model is based on the linear quadratic model and was derived from a nonlinear regression fit to 287 experimental data points. The proposed model predicts that the RBE increases with increasing LETd and decreases with increasing (α/β)x. This agrees with previous theoretical predictions on the relationship between RBE, LETd and (α/β)x. The model additionally predicts a decrease in RBE with increasing dose and shows a relationship between both α and β with LETd. Our proposed phenomenological RBE model is derived using the most comprehensive collection of proton RBE experimental data to date. Previously published phenomenological models, based on a limited data set, may have to be revised.

A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions

The aim of this work is to predict relative biological effectiveness (RBE) for protons and clinically relevant heavier ions, by using a simplified semi-empirical process based on rational expectations and published experimental results using different ion species. The model input parameters are: Z (effective nuclear charge) and radiosensitivity parameters α_L and β_L of the control low linear energy transfer (LET) radiation. Sequential saturation processes are assumed for: (a) the position of the turnover point (LET_U) for the LET–RBE relationship with Z, and (b) the ultimate value of α at this point (α_U) being non-linearly related to α_L. Using the same procedure for β, on the logical assumption that the changes in β with LET, although smaller than α, are symmetrical with those of α, since there is symmetry of the fall off of LET–RBE curves with increasing dose, which suggests that LET_U must be identical for α and β. Then, using iso-effective linear quadratic model equations, the estimated RBE is scaled between α_U and α_L and between β_U and β_L from for any input value of Z, α_L, β_L, and dose. The model described is fitted to the data of Barendsen (alpha particles), Weyrather et al. (carbon ions), and Todd for nine different ions (deuterons to Argon), which include variations in cell surviving fraction and dose. In principle, this new system can be used to complement the more complex methods to predict RBE with LET such as the local effect and MKM models which already have been incorporated into treatment planning systems in various countries. It would be useful to have a secondary check to such systems, especially to alert clinicians of potential risks by relatively easy estimation of relevant RBEs. In clinical practice, LET values smaller than LET_U are mostly encountered, but the model extends to higher values beyond LET_U for other purposes such as radiation, protection, and astrobiology. Considerable further research is required, perhaps in a dedicated international laboratory, using a basket of different models to determine what the best system or combination of systems will be to make proton and ion beam radiotherapy as safe as possible and to produce the best possible clinical results.