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.

https://iopscience.iop.org/article/10.1088/0031-9155/59/22/R419/pdf

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

The health risks of space radiation are arguably the most serious challenge to space exploration, possibly preventing these missions due to safety concerns or increasing their costs to amounts beyond what would be acceptable. Radiation in space is substantially different from Earth: high-energy ($E$) and charge ($Z$) particles (HZE) provide the main contribution to the equivalent dose in deep space, whereas $\ensuremath{\gamma}$ rays and low-energy $\ensuremath{\alpha}$ particles are major contributors on Earth. This difference causes a high uncertainty on the estimated radiation health risk (including cancer and noncancer effects), and makes protection extremely difficult. In fact, shielding is very difficult in space: the very high energy of the cosmic rays and the severe mass constraints in spaceflight represent a serious hindrance to effective shielding. Here the physical basis of space radiation protection is described, including the most recent achievements in space radiation transport codes and shielding approaches. Although deterministic and Monte Carlo transport codes can now describe well the interaction of cosmic rays with matter, more accurate double-differential nuclear cross sections are needed to improve the codes. Energy deposition in biological molecules and related effects should also be developed to achieve accurate risk models for long-term exploratory missions. Passive shielding can be effective for solar particle events; however, it is limited for galactic cosmic rays (GCR). Active shielding would have to overcome challenging technical hurdles to protect against GCR. Thus, improved risk assessment and genetic and biomedical approaches are a more likely solution to GCR radiation protection issues.

Physical basis of radiation protection in space travel

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.

/pdf/a-phenomenological-relative-biological-effectiveness-rbe-2tusstsaye.pdf

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

For tumor therapy with light ions and for experimental aspects in particle radiobiology the relative biological effectiveness (RBE) is an important quantity to describe the increased effectiveness of particle radiation. By establishing and analysing a database of ion and photon cell survival data, some remarkable properties of RBE-related quantities were observed. The database consists of 855 in vitro cell survival experiments after ion and photon irradiation. The experiments comprise curves obtained in different labs, using different ion species, different irradiation modalities, the whole range of accessible energies and linear energy transfers (LETs) and various cell types. Each survival curve has been parameterized using the linear-quadratic (LQ) model. The photon parameters, α and β, appear to be slightly anti-correlated, which might point toward an underlying biological mechanism. The RBE values derived from the survival curves support the known dependence of RBE on LET, on particle species and dose. A positive correlation of RBE with the ratio α/β of the photon LQ parameters is found at low doses, which unexpectedly changes to a negative correlation at high doses. Furthermore, we investigated the course of the β coefficient of the LQ model with increasing LET, finding typically a slight initial increase and a final falloff to zero. The observed fluctuations in RBE values of comparable experiments resemble overall RBE uncertainties, which is of relevance for treatment planning. The database can also be used for extensive testing of RBE models. We thus compare simulations with the local effect model to achieve this goal.

Systematic analysis of RBE and related quantities using a database of cell survival experiments with ion beam irradiation

The paper examines the prospects of using laser plasma as a source of high-energy ions for the purpose of hadron beam therapy — an approach which is based on both theory and experimental results (ions are routinely observed to be accelerated in the interaction of high-power laser radiation with matter). Compared to therapy accelerators like synchrotrons and cyclotrons, laser technology is advantageous in that it is more compact and is simpler in delivering ions from the accelerator to the treatment room. Special target designs allow radiation therapy requirements for ion beam quality to be satisfied. (reviews of topical problems)

/pdf/laser-ion-acceleration-for-hadron-therapy-cnjq2asjgl.pdf

Laser ion acceleration for hadron therapy

Purpose: To present the first direct experimental in vitro comparison of the biological effectiveness of rangeequivalent protons and carbon ion beams for Chinese hamsterovary cells exposed in a three-dimensional phantom using a pencil beam scanning technique and to compare the experimental data with a novel biophysical model. Methodsand Materials:Cell survivalwasmeasuredinthe phantomafter irradiation withtwo opposingfields,thus mimicking the typical patient treatment scenario. The novel biophysical model represents a substantial extension of the local effect model, previously used for treatment planning in carbon ion therapy for more than 400 patients, and potentially can be used to predict effectiveness of all ion species relevant for radiotherapy. A key feature of the new approach is the more sophisticated consideration of spatially correlated damage induced by ion irradiation. Results: The experimental data obtained for Chinese hamster ovary cells clearly demonstrate that higher cell killing is achieved in the target region with carbon ions as compared with protons when the effects in the entrance channel are comparable. The model predictions demonstrate agreement with these experimental data and with data obtained with helium ions under similar conditions. Good agreement is also achieved with relative biological effectiveness values reported in the literature for other cell lines for monoenergetic proton, helium, and carbon ions. Conclusion: Both the experimental data and the new modeling approach are supportive of the advantages of carbon ions as compared with protons for treatment-like field configurations. Because the model predicts the effectiveness for several ion species with similar accuracy, it represents a powerful tool for further optimization and utilization of the potential of ion beams in tumor therapy. 2010 Elsevier Inc. Ion beam therapy, Relative biological effectiveness (RBE), Biophysical model, Treatment planning.

Quantification of the Relative Biological Effectiveness for Ion Beam Radiotherapy: Direct Experimental Comparison of Proton and Carbon Ion Beams and a Novel Approach for Treatment Planning

Precision measurements of Bragg curves of light-ion beams in water

Purpose: Most treatment planning systems apply deterministic numerical algorithms for dose calculation and optimization, which are fast and reliable but show certain deficiencies when dealing with inhomogeneities. Monte Carlo simulations may improve these special cases. We report on a novel approach implementing an efficient Monte Carlo engine in the framework of the TRiP98 (treatment planning for particles) treatment planning system, now in use for research purposes. Materials and Methods: To reduce the calculation time, history repetition was used and the physical interactions were restricted to the major ones: energy loss, fragmentation, attenuation, energy loss straggling, and multiple scattering. The dose calculations are performed on the computed tomography grid, whose regularity greatly reduces the complexity of the irradiation volume we have to deal with. Results: We implemented a Monte Carlo algorithm within the clinically tested TRiP98 treatment planning system. We performed simulations...

Gheorghe Iancu

Papers

Quantification of the Relative Biological Effectiveness for Ion Beam Radiotherapy: Direct Experimental Comparison of Proton and Carbon Ion Beams and a Novel Approach for Treatment Planning

Precision measurements of Bragg curves of light-ion beams in water

Implementation of an Efficient Monte Carlo Algorithm in TRiP: Physical Dose Calculation