The potential impact of relative biological effectiveness uncertainty on charged particle treatment prescriptions

Proposing a Clinical Model for RBE Based on Proton Track-End Counts

PURPOSE

In proton therapy, the clinical application of linear energy transfer (LET) optimization remains contentious, in part because of challenges associated with the definition and calculation of LET and its exact relationship with relative biological effectiveness (RBE) because of large variation in experimental in vitro data. This has raised interest in other metrics with favorable properties for biological optimization, such as the number of proton track ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track end counts.

METHODS AND MATERIALS

We developed an effective dose concept to translate between the total proton track-end count per unit mass in a voxel and a proton RBE value. Dose, track end, and dose-averaged LET (LETd) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track ends and regions of elevated biological effectiveness in comparison to LETd-based models of RBE.

RESULTS

Track ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LETd. In patient simulations, our track end model identified the same biological hotspots as predicted by LETd-based radiobiological models of proton RBE.

CONCLUSIONS

These results suggest that, for clinical optimization and evaluation, an RBE model based on proton track end counts may match LETd-based models in terms of information provided while also offering superior statistical properties.

Mechanisms and Review of Clinical Evidence of Variations in Relative Biological Effectiveness in Proton Therapy

Proton therapy is increasingly being used as a radiation therapy modality. There is uncertainty about the biological effectiveness of protons relative to photon therapies as it depends on several physical and biological parameters. Radiation oncology currently applies a constant and generic value for the relative biological effectiveness (RBE) of 1.1, which was chosen conservatively to ensure tumor coverage. The use of a constant value has been challenged particularly when considering normal tissue constraints. Potential variations in RBE have been assessed in several published reviews but have mostly focused on data from clonogenic cell survival experiments with unclear relevance for clinical proton therapy. The goal of this review is to put in vitro findings in relation to clinical observations. Relevant in vivo pathways determining RBE for tumors and normal tissues are outlined, including not only damage to tumor cells and parenchyma but also vascular damage and immune response. Furthermore, the current clinical evidence of varying RBE is reviewed. The assessment can serve as guidance for treatment planning, personalized dose prescriptions, and outcome analysis.

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.

Particle therapy in the future of precision therapy

The first hospital-based treatment facilities for particle therapy started operation about thirty years ago. Since then, the clinical experience with protons and carbon ions has grown continuously and more than 200,000 patients have been treated to date. The promising clinical results led to a rapidly increasing number of treatment facilities and many new facilities are planned or under construction all over the world. An inverted depth-dose profile combined with potential radiobiological advantages make charged particles a precious tool for the treatment of tumours that are particularly radioresistant or located nearby sensitive structures. A rising number of trials have already confirmed the benefits of particle therapy in selected clinical situations and further improvements in beam delivery, image guidance and treatment planning are expected. This review summarises some physical and biological characteristics of accelerated charged particles and gives some examples of their clinical application. Furthermore, challenges and future perspectives of particle therapy will be discussed.

Neutron activation of gadolinium for ion therapy: a Monte Carlo study of charged particle beams

This study investigates the photon production from thermal neutron capture in a gadolinium (Gd) infused tumor as a result of secondary neutrons from particle therapy. Gadolinium contrast agents used in MRI are distributed within the tumor volume and can act as neutron capture agents. As a result of particle therapy, secondary neutrons are produced and absorbed by Gd in the tumor providing potential enhanced localized dose in addition to a signature photon spectrum that can be used to produce an image of the Gd enriched tumor. To investigate this imaging application, Monte Carlo (MC) simulations were performed for 10 different particles using a 5-10 cm spread out-Bragg peak (SOBP) centered on an 8 cm3, 3 mg/g Gd infused tumor. For a proton beam, 1.9 × 106 neutron captures per RBE weighted Gray Equivalent dose (GyE) occurred within the Gd tumor region. Antiprotons ([Formula: see text]), negative pions (- π), and helium (He) ion beams resulted in 10, 17 and 1.3 times larger Gd neutron captures per GyE than protons, respectively. Therefore, the characteristic photon based spectroscopic imaging and secondary Gd dose enhancement could be viable and likely beneficial for these three particles.

Hybrid 3D analytical linear energy transfer calculation algorithm based on precalculated data from Monte Carlo simulations

PURPOSE

The dose-averaged linear energy transfer (LET_d ) for intensity-modulated proton therapy (IMPT) calculated by one-dimensional (1D) analytical models deviates from more accurate but time-consuming Monte Carlo (MC) simulations. We developed a fast hybrid three-dimensional (3D) analytical LET_d calculation that is more accurate than 1D analytical model.

METHODS

We used the Geant4 MC code to generate 3D LET_d distributions of monoenergetic proton beams in water for all energies and used a customized error function to fit the LET_d lateral profiles at various depths to the MC simulation. The 3D LET_d calculation kernel was a lookup table of these fitted coefficients, and LET_d was determined directly from spot energies and voxel coordinates during analytical dose calculations. We validated our new method by comparing the calculated LET_d distributions to MC results using 3D Gamma index analysis with 3%/2 mm criteria in 12 patient geometries. The significance of the improvement in Gamma index analysis passing rates over the 1D analytical model was determined using the Wilcoxon rank-sum test.

RESULTS

The passing rate of 3D Gamma analysis comparing LET_d distributions from the hybrid 3D method and the 1D method to MC simulations was significantly improved from 94.0% ± 2.5% to 98.0% ± 1.0% (P = 0.0003). The typical time to calculate dose and LET_d simultaneously using an Intel Xeon E5-2680 2.50 GHz workstation was approximately 2.5 min.

CONCLUSIONS

Our new method significantly improved the LET_d calculation accuracy compared to the 1D method while maintaining significantly shorter calculation time even comparing with the GPU-based fast MC code.

Report of the AAPM TG-256 on the relative biological effectiveness of proton beams in radiation therapy

The biological effectiveness of proton beams relative to photon beams in radiation therapy has been taken to be 1.1 throughout the history of proton therapy. While potentially appropriate as an average value, actual relative biological effectiveness (RBE) values may differ. This Task Group report outlines the basic concepts of RBE as well as the biophysical interpretation and mathematical concepts. The current knowledge on RBE variations is reviewed and discussed in the context of the current clinical use of RBE and the clinical relevance of RBE variations (with respect to physical as well as biological parameters). The following task group aims were designed to guide the current clinical practice: Assess whether the current clinical practice of using a constant RBE for protons should be revised or maintained. Identifying sites and treatment strategies where variable RBE might be utilized for a clinical benefit. Assess the potential clinical consequences of delivering biologically weighted proton doses based on variable RBE and/or LET models implemented in treatment planning systems. Recommend experiments needed to improve our current understanding of the relationships among in vitro, in vivo, and clinical RBE, and the research required to develop models. Develop recommendations to minimize the effects of uncertainties associated with proton RBE for well-defined tumor types and critical structures.

Proton Relative Biological Effectiveness - Uncertainties and Opportunities

Proton therapy treatments are prescribed using a biological effectiveness relative to photon therapy of 1.1, that is, proton beams are considered to be 10% more biologically effective. Debate is ongoing as to whether this practice needs to be revised. This short review summarizes current knowledge on relative biological effectiveness variations and uncertainties in vitro and in vivo. Clinical relevance is discussed and strategies toward biologically guided treatment planning are presented.

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.

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.

Evaluation of the relative biological effectiveness of spot-scanning proton irradiation in vitro

Variations in relative biological effectiveness (RBE) from a fixed value of 1.1 are critical in proton beam therapy. To date, studies estimating RBE at multiple positions relative to the spread-out Bragg peak (SOBP) have been predominantly performed using passive scattering methods, and limited data are available for spot-scanning beams. Thus, to investigate the RBE of spot-scanning beams, Chinese hamster fibroblast V79 cells were irradiated using the beam line at the Hokkaido University Hospital Proton Therapy Center. Cells were placed at six different depths, including the entrance of the proton beam and the proximal and distal part of the SOBP. Surviving cell fractions were analyzed using colony formation assay, and cell survival curves were obtained by the curve fitted using a linear-quadratic model. RBE10 and RBE37 were 1.15 and 1.21 at the center of the SOBP, respectively. In contrast, the distal region showed higher RBE values (1.50 for RBE10 and 1.85 for RBE37). These results are in line with those of previous studies conducted using passive scattering proton beams. Taken together, these data strongly suggest that variations in RBE should be considered during treatment planning for spot-scanning beams as well as for passive scattering proton beams.

Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer

Proton therapy treatments are based on a proton RBE (relative biological effectiveness) relative to high-energy photons of 1.1. The use of this generic, spatially invariant RBE within tumors and normal tissues disregards the evidence that proton RBE varies with linear energy transfer (LET), physiological and biological factors, and clinical endpoint. Based on the available experimental data from published literature, this review analyzes relationships of RBE with dose, biological endpoint and physical properties of proton beams. The review distinguishes between endpoints relevant for tumor control probability and those potentially relevant for normal tissue complication. Numerous endpoints and experiments on sub-cellular damage and repair effects are discussed. Despite the large amount of data, considerable uncertainties in proton RBE values remain. As an average RBE for cell survival in the center of a typical spread-out Bragg peak (SOBP), the data support a value of ~1.15 at 2 Gy/fraction. The proton RBE increases with increasing LETd and thus with depth in an SOBP from ~1.1 in the entrance region, to ~1.15 in the center, ~1.35 at the distal edge and ~1.7 in the distal fall-off (when averaged over all cell lines, which may not be clinically representative). For small modulation widths the values could be increased. Furthermore, there is a trend of an increase in RBE as (α/β)x decreases. In most cases the RBE also increases with decreasing dose, specifically for systems with low (α/β)x. Data on RBE for endpoints other than clonogenic cell survival are too diverse to allow general statements other than that the RBE is, on average, in line with a value of ~1.1. This review can serve as a source for defining input parameters for applying or refining biophysical models and to identify endpoints where additional radiobiological data are needed in order to reduce the uncertainties to clinically acceptable levels.

Relative biological effectiveness variation along monoenergetic and modulated Bragg peaks of a 62-MeV therapeutic proton beam: a preclinical assessment

PURPOSE

The biological optimization of proton therapy can be achieved only through a detailed evaluation of relative biological effectiveness (RBE) variations along the full range of the Bragg curve. The clinically used RBE value of 1.1 represents a broad average, which disregards the steep rise of linear energy transfer (LET) at the distal end of the spread-out Bragg peak (SOBP). With particular attention to the key endpoint of cell survival, our work presents a comparative investigation of cell killing RBE variations along monoenergetic (pristine) and modulated (SOBP) beams using human normal and radioresistant cells with the aim to investigate the RBE dependence on LET and intrinsic radiosensitvity.

METHODS AND MATERIALS

Human fibroblasts (AG01522) and glioma (U87) cells were irradiated at 6 depth positions along pristine and modulated 62-MeV proton beams at the INFN-LNS (Catania, Italy). Cell killing RBE variations were measured using standard clonogenic assays and were further validated using Monte Carlo simulations and the local effect model (LEM).

RESULTS

We observed significant cell killing RBE variations along the proton beam path, particularly in the distal region showing strong dose dependence. Experimental RBE values were in excellent agreement with the LEM predicted values, indicating dose-averaged LET as a suitable predictor of proton biological effectiveness. Data were also used to validate a parameterized RBE model.

CONCLUSIONS

The predicted biological dose delivered to a tumor region, based on the variable RBE inferred from the data, varies significantly with respect to the clinically used constant RBE of 1.1. The significant RBE increase at the distal end suggests also a potential to enhance optimization of treatment modalities such as LET painting of hypoxic tumors. The study highlights the limitation of adoption of a constant RBE for proton therapy and suggests approaches for fast implementation of RBE models in treatment planning.