Roadmap: helium ion therapy

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

Physical characterization of3He ion beams for radiotherapy and comparison with4He

There is increasing interest in using helium ions for radiotherapy, complementary to protons and carbon ions. A large number of patients were treated with⁴He ions in the US heavy ion therapy project and novel⁴He ion treatment programs are under preparation, for instance in Germany and Japan.³He ions have been proposed as an alternative to⁴He ions because the acceleration of³He is technically less difficult than⁴He. In particular, beam contaminations have been pointed out as a potential safety issue for⁴He ion beams. This motivated a series of experiments with³He ion beams at Gesellschaft für Schwerionenforschung (GSI), Darmstadt. Measured³He Bragg curves and fragmentation data in water are presented in this work. Those experimental data are compared with FLUKA Monte Carlo simulations. The physical characteristics of³He ion beams are compared to those of⁴He, for which a large set of data became available in recent years from the preparation work at the Heidelberger Ionenstrahl-Therapiezentrum (HIT). The dose distributions (spread out Bragg peaks, lateral profiles) that can be achieved with³He ions are found to be competitive to⁴He dose distributions. The effect of beam contaminations on⁴He depth dose distribution is also addressed. It is concluded that³He ions can be a viable alternative to⁴He, especially for future compact therapy accelerator designs and upgrades of existing ion therapy facilities.

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

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

MODELLING DSB REPAIR KINETICS FOR DNA DAMAGE INDUCED BY PROTON AND CARBON IONS

Proton and carbon therapy are the main choices of particle therapy for cancer treatment. Particle dose distribution is superior to conventional photon therapy dose distribution due to Bragg peak. However, the basic biology of cellular damage and cell death is not well understood. The aim of this work is to present a mechanistic model of double strand break (DSB) repair that predicts the repair kinetics of damage induced by particles employed in cancer therapy. Monte Carlo Track Damage Simulation (MCDS) was employed to model DNA damage. The frequency of DSB and SSB was computed for proton and carbon ions. DSBs were subjected to repair model to calculate the repair kinetics. Two distinct DSB repair models dependent on the cell cycle were proposed. The DSB repair model contains non-homologous end joining (NHEJ), homologous recombination (HR) and back up non-homologous end joining (B-NHEJ) repair processes. The DSB complexity results in the switch in the repair pathway from NHEJ to a slower process that starts with DSB end resection. DSB end resection in early S and G1 phases of the cell cycle enhances the B-NHEJ repair pathway, while in late S and G2 phases of the cell cycle promotes HR repair pathway. The repair model was transformed to a set of nonlinear differential equations. The model calculates the overall repair kinetics and protein temporal repair activity at the site of damage. The damage and repair model provides a detailed mechanistic understanding of all processes that are involved in the damage induction and repair. The number of DSB and their complexity increase as the particle energy decreases due to the proximity of particle interactions in water. The repair kinetics show a biphasic behaviour that is due to the NHEJ fast repair of simple type DSB and HR slow repair of complex type DSB.

Radiobiological quantities in proton-therapy: Estimation and validation using Geant4-based Monte Carlo simulations

PURPOSE

The Geant4 Monte Carlo simulation toolkit was used to reproduce radiobiological parameters measured by irradiating three different cancerous cell lines with monochromatic and clinical proton beams.

METHODS

The experimental set-up adopted for irradiations was fully simulated with a dedicated open-source Geant4 application. Cells survival fractions was calculated coupling the Geant4 simulations with two analytical radiobiological models: one based on the LEM (Local Effect Model) approach and the other on a semi-empirical parameterisation. Results was evaluated and compared with experimental data.

RESULTS AND CONCLUSIONS

The results demonstrated the Geant4 ability to reproduce radiobiological quantities for different cell lines.

Report of a National Cancer Institute special panel: Characterization of the physical parameters of particle beams for biological research

PURPOSE

To define the physical parameters needed to characterize a particle beam in order to allow intercomparison of different experiments performed using different ions at the same facility and using the same ion at different facilities.

METHODS

At the request of the National Cancer Institute (NCI), a special panel was convened to review the current status of the field and to provide suggested metrics for reporting the physical parameters of particle beams to be used for biological research. A set of physical parameters and measurements that should be performed by facilities and understood and reported by researchers supported by NCI to perform pre-clinical radiobiology and medical physics of heavy ions were generated.

RESULTS

Standard measures such as radiation delivery technique, beam modifiers used, nominal energy, field size, physical dose and dose rate should all be reported. However, more advanced physical measurements, including detailed characterization of beam quality by microdosimetric spectrum and fragmentation spectra, should also be established and reported. Details regarding how such data should be incorporated into Monte Carlo simulations and the proper reporting of simulation details are also discussed.

CONCLUSIONS

In order to allow for a clear relation of physical parameters to biological effects, facilities and researchers should establish and report detailed physical characteristics of the irradiation beams utilized including both standard and advanced measures. Biological researchers are encouraged to actively engage facility staff and physicists in the design and conduct of experiments. Modeling individual experimental setups will allow for the reporting of the uncertainties in the measurement or calculation of physical parameters which should be routinely reported.

Physical parameter optimization scheme for radiobiological studies of charged particle therapy

We have developed an easy-to-implement method to optimize the spatial distribution of a desired physical quantity for charged particle therapy. The basic methodology requires finding the optimal solutions for the weights of the constituent particle beams that together form the desired spatial distribution of the specified physical quantity, e.g., dose or dose-averaged linear energy transfer (LETd), within the target region. We selected proton, 4He ion, and 12C ion beams to demonstrate the feasibility and flexibility of our method. The pristine dose Bragg curves in water for all ion beams and the LETd for proton beams were generated from Geant4 Monte Carlo simulations. The optimization algorithms were implemented using the Python programming language. High-accuracy optimization results of the spatial distribution of the desired physical quantity were then obtained for different cases. The relative difference between the real value and the expected value of a given quantity was approximately within ±1.0% in the whole target region. The optimization examples include a flat dose spread-out Bragg peak (SOBP) for the three selected ions, an upslope dose SOBP for protons, and a downslope dose SOBP for protons. The relative difference was approximately within ±2.0% for the case with a flat LETd (target value = 4 keV/µm) distribution for protons. These one-dimensional optimization algorithms can be extended to two or three dimensions if the corresponding physical data are available. In addition, this physical quantity optimization strategy can be conveniently extended to encompass biological dose optimization if appropriate biophysical models are invoked.

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

Monte Carlo (MC) simulation is considered as the most accurate method for calculation of absorbed dose and fundamental physics quantities related to biological effects in carbon ion therapy. To improve its computational efficiency, we have developed a GPU-oriented fast MC package named goCMC, for carbon therapy. goCMC simulates particle transport in voxelized geometry with kinetic energy up to 450 MeV u-1. Class II condensed history simulation scheme with a continuous slowing down approximation was employed. Energy straggling and multiple scattering were modeled. δ-electrons were terminated with their energy locally deposited. Four types of nuclear interactions were implemented in goCMC, i.e. carbon-hydrogen, carbon-carbon, carbon-oxygen and carbon-calcium inelastic collisions. Total cross section data from Geant4 were used. Secondary particles produced in these interactions were sampled according to particle yield with energy and directional distribution data derived from Geant4 simulation results. Secondary charged particles were transported following the condensed history scheme, whereas secondary neutral particles were ignored. goCMC was developed under OpenCL framework and is executable on different platforms, e.g. GPU and multi-core CPU. We have validated goCMC with Geant4 in cases with different beam energy and phantoms including four homogeneous phantoms, one heterogeneous half-slab phantom, and one patient case. For each case [Formula: see text] carbon ions were simulated, such that in the region with dose greater than 10% of maximum dose, the mean relative statistical uncertainty was less than 1%. Good agreements for dose distributions and range estimations between goCMC and Geant4 were observed. 3D gamma passing rates with 1%/1 mm criterion were over 90% within 10% isodose line except in two extreme cases, and those with 2%/1 mm criterion were all over 96%. Efficiency and code portability were tested with different GPUs and CPUs. Depending on the beam energy and voxel size, the computation time to simulate [Formula: see text] carbons was 9.9-125 s, 2.5-50 s and 60-612 s on an AMD Radeon GPU card, an NVidia GeForce GTX 1080 GPU card and an Intel Xeon E5-2640 CPU, respectively. The combined accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon ion therapy.