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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 keV μ m -1 to ∼40 keV μ m -1 . In the frame of heavy ion therapy using carbon, oxygen or neon ions, where LET d increases beyond 100 keV μ m -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., (Creative Commons Attribution license.)

Objective . Irradiation with ultra-high dose rates (>40 Gy s -1 ), also known as FLASH irradiation, has the potential to shift the paradigm of radiation therapy because of its reduced toxicity to normal tissues compared to that of conventional irradiations. The goal of this study was to (1) achieve FLASH irradiation conditions suitable for pre-clinical i n vitro and in vivo biology experiments using our synchrotron-based proton beamline and (2) commission the FLASH irradiation conditions achieved. Approach . To achieve these suitable FLASH conditions, we made a series of adaptations to our proton beamline, including modifying the spill length and size of accelerating cycles, repurposing the reference monitor for dose control, and expanding the field size with a custom double-scattering system. We performed the dosimetric commissioning with measurements using an Advanced Markus chamber and EBT-XD films as well as with Monte Carlo simulations. Main results . Through adaptations, we have successfully achieved FLASH irradiation conditions, with an average dose rate of up to 375 Gy s -1 . The Advanced Markus chamber was shown to be appropriate for absolute dose calibration under our FLASH conditions with a recombination factor ranging from 1.002 to 1.006 because of the continuous nature of our synchrotron-based proton delivery within a spill. Additionally, the absolute dose measured using the Advanced Markus chamber and EBT-XD films agreed well, with average and maximum differences of 0.32% and 1.63%, respectively. We also performed a comprehensive temporal analysis for FLASH spills produced by our system, which helped us identify a unique relationship between the average dose rate and the dose in our FLASH irradiation. Significance. We have established a synchrotron-based proton FLASH irradiation platform with accurate and precise dosimetry that is suitable for pre-clinical biology experiments. The unique time structure of the FLASH irradiation produced by our synchrotron-based system may shed new light onto the mechanism behind the FLASH effect., (© 2022 Institute of Physics and Engineering in Medicine.)

Microdosimetry is an important tool for assessing energy deposition distributions from ionizing radiation at cellular and cellular nucleus scales. It has served as an input parameter for multiple common mathematical models, including evaluation of relative biological effectiveness (RBE) of carbon ion therapy. The most common detector used for microdosimetry is the tissue-equivalent proportional counter (TEPC). Although it is widely applied, TEPC has various inherent uncertainties. Therefore, this work quantified the magnitude of TEPC measurement uncertainties and their impact on RBE estimates for therapeutic carbon beams. Microdosimetric spectra and frequency-, dose-, and saturation-corrected dose-mean lineal energy (****) were calculated using the Monte Carlo toolkit Geant4 for five monoenergetic and three spread-out Bragg peak carbon beams in water at every millimeter along the central beam axis. We simulated the following influences on these spectra from eight sources of uncertainty: wall effects, pulse pile-up, electronics, gas pressure, W-value, gain instability, low energy cut-off, and counting statistics. Statistic uncertainty was quantified as the standard deviation of perturbed values for each source. Bias was quantified as the difference between default lineal energy values and the mean of perturbed values for each systematic source. Uncertainties were propagated to RBE using the modified microdosimetric kinetic model (MKM). Variance introduced by statistic sources iny¯Fandy¯Daveraged 3.8% and 3.4%, respectively, and 1.5% iny*across beam depths and energies. Bias averaged 6.2% and 7.3% iny¯Fandy¯D,and 4.8% iny*.These uncertainties corresponded to 1.2 ± 0.9% on average in RBE MKM . The largest contributors to variance and bias were pulse pile-up and wall effects. This study established an error budget for microdosimetric carbon measurements by quantifying uncertainty inherent to TEPC measurements. It is necessary to understand how robust the measurement of RBE model input parameters are against this uncertainty in order to verify clinical model implementation., (© 2021 Institute of Physics and Engineering in Medicine.)

Purpose . Molecular breast imaging (MBI) of 99m Tc-sestamibi with dual-headed, pixelated, cadmium-zinc-telluride (CZT) detectors is increasingly used in breast cancer care for screening/detecting lesions, monitoring response to therapy, and predicting risk of cancer. MBI as a truly quantitative tool in these applications, however, is limited due the lack of absolute 99m Tc-sestamibi uptake quantification. To help advance the field of quantitative MBI, we have developed a Monte Carlo simulation application of the GE Discovery NM 750b system. Methods . Our simulation consists of a two-step process using the Geant4 toolkit to model the detector and source geometry and to track photon interactions and a MATLAB script to model the charge transport within the pixelated CZT detector. Simulated detector and detector response model parameters were selected to match measured and simulated standard performance characteristics using various 99m Tc point-, line-, and film-sources in air. The final model parameters were verified by comparing the count profiles, energy spectra, and region of interest counts between simulated and measured images of a breast phantom with two spherical lesions in 5 cm thick medium of air or water. Results . Final performance characteristics with 99m Tc sources in air were: (1) energy resolution: 6.1% measured versus 5.9% simulated photopeak full-width at half-maximum (FWHM), (2) spatial resolution: mean error between measured and simulated FWHM of 0.08 mm across 4.4-14.0 mm FWHM range, and (3) sensitivity: 572 cpm/ μ Ci measured versus 567 cpm/ μ Ci simulated (<1% error). Good agreement was observed in the breast phantom line profiles through the spherical lesions and overall energy spectra, with <5% difference in sphere counts between simulated and measured data. Conclusion . A pixelated CZT charge transport and induction model was successfully implemented and validated to simulate imaging with the GE Discovery NM 750b system. This work will enable investigations improving MBI image quality and developing algorithms for uptake quantification., (© 2021 Institute of Physics and Engineering in Medicine.)

In charged particle therapy, the objective is to exploit both the physical and radiobiological advantages of charged particles to improve the therapeutic index. Use of the beam scanning technique provides the flexibility to implement biological dose optimized intensity-modulated ion therapy (IMIT). An easy-to-implement algorithm was developed in the current study to rapidly generate a uniform biological dose distribution, namely the product of physical dose and the relative biological effectiveness (RBE), within the target volume using scanned ion beams for charged particle radiobiological studies. Protons, helium ions and carbon ions were selected to demonstrate the feasibility and flexibility of our method. The general-purpose Monte Carlo simulation toolkit Geant4 was used for particle tracking and generation of physical and radiobiological data needed for later dose optimizations. The dose optimization algorithm was developed using the Python (version 3) programming language. A constant RBE-weighted dose (RWD) spread-out Bragg peak (SOBP) in a water phantom was selected as the desired target dose distribution to demonstrate the applicability of the optimization algorithm. The mechanistic repair-misrepair-fixation (RMF) model was incorporated into the Monte Carlo particle tracking to generate radiobiological parameters and was used to predict the RBE of cell survival in the iterative process of the biological dose optimization for the three selected ions. The post-optimization generated beam delivery strategy can be used in radiation biology experiments to obtain radiobiological data to further validate and improve the accuracy of the RBE model. This biological dose optimization algorithm developed for radiobiology studies could potentially be extended to implement biologically optimized IMIT plans for patients.