Purpose: Novel radiotherapy techniques like synchrotron X‐ray microbeam radiation therapy (MRT) require fast dose distribution predictions that are accurate at the sub‐mm level, especially close to tissue/bone/air interfaces. Monte Carlo (MC) physics simulations are recognized to be one of the most accurate tools to predict the dose delivered in a target tissue but can be very time consuming and therefore prohibitive for treatment planning. Faster dose prediction algorithms are usually developed for clinically deployed treatments only. In this work, we explore a new approach for fast and accurate dose estimations suitable for novel treatments using digital phantoms used in preclinical development and modern machine learning techniques. We develop a generative adversarial network (GAN) model, which is able to emulate the equivalent Geant4 MC simulation with adequate accuracy and use it to predict the radiation dose delivered by a broad synchrotron beam to various phantoms.Methods: The energy depositions used for the training of the GAN are obtained using full Geant4 MC simulations of a synchrotron radiation broad beam passing through the phantoms. The energy deposition is scored and predicted in voxel matrices of size 140 × 18 × 18 with a voxel edge length of 1 mm. The GAN model consists of two competing 3D convolutional neural networks, which are conditioned on the photon beam and phantom properties. The generator network has a U‐Net structure and is designed to predict the energy depositions of the photon beam inside three phantoms of variable geometry with increasing complexity. The critic network is a relatively simple convolutional network, which is trained to distinguish energy depositions predicted by the generator from the ones obtained with the full MC simulation.Results: The energy deposition predictions inside all phantom geometries under investigation show deviations of less than 3% of the maximum deposited energy from the simulation for roughly 99% of the voxels in the field of the beam. Inside the most realistic phantom, a simple pediatric head, the model predictions deviate by less than 1% of the maximal energy deposition from the simulations in more than 96% of the in‐field voxels. For all three phantoms, the model generalizes the energy deposition predictions well to phantom geometries, which have not been used for training the model but are interpolations of the training data in multiple dimensions. The computing time for a single prediction is reduced from several hundred hours using Geant4 simulation to less than a second using the GAN model.Conclusions: The proposed GAN model predicts dose distributions inside unknown phantoms with only small deviations from the full MC simulation with computations times of less than a second. It demonstrates good interpolation ability to unseen but similar phantom geometries and is flexible enough to be trained on data with different radiation scenarios without the need for optimization of the model parameter. This proof‐of‐concept encourages to apply and further develop the model for the use in MRT treatment planning, which requires fast and accurate predictions with sub‐mm resolutions.

The production of anthropomorphic phantoms generated from tissue-equivalent materials is challenging but offers an excellent copy of the typical environment encountered in typical patients. High-quality dosimetry measurements and the correlation of the measured dose with the biological effects elicited by it are a prerequisite in preparation of clinical trials with novel radiotherapy approaches. We designed and produced a partial upper arm phantom from tissue-equivalent materials for use in experimental high-dose-rate radiotherapy. The phantom was compared to original patient data using density values and Hounsfield units obtained from CT scans. Dose simulations were conducted for broad-beam irradiation and microbeam radiotherapy (MRT) and compared to values measured in a synchrotron radiation experiment. Finally, we validated the phantom in a pilot experiment with human primary melanoma cells.

Objective. This study aims to design, manufacture, and test 3D printed quality assurance (QA) dosimetry phantoms for synchrotron brain cancer radiation therapy at the Australian synchrotron. Approach. Fabricated 3D printed phantoms from simple slab phantoms, a preclinical rat phantom, and an anthropomorphic head phantom were fabricated and characterized. Attenuation measurements of various polymers, ceramics and metals were acquired using synchrotron monochromatic micro-computed tomography (CT) imaging. Polylactic acid plus, VeroClear, Durable resin, and tricalcium phosphate were used in constructing the phantoms. Furthermore, 3D printed bone equivalent materials were compared relative to ICRU bone and hemihydrate plaster. Homogeneous and heterogeneous rat phantoms were designed and fabricated using tissue-equivalent materials. Geometric accuracy, CT imaging, and consistency were considered. Moreover, synchrotron broad-beam x-rays were delivered using a 3 Tesla superconducting multipole wiggler field for four sets of synchrotron radiation beam qualities. Dose measurements were acquired using a PinPoint ionization chamber and compared relative to a water phantom and a RMI457 Solid Water phantom. Experimental depth doses were compared relative to calculated doses using a Geant4 Monte Carlo simulation. Main results. Polylactic acid (PLA+) shows to have a good match with the attenuation coefficient of ICRU water, while both tricalcium phosphate and hydroxyapatite have good attenuation similarity with ICRU bone cortical. PLA+ material can be used as substitute to RMI457 slabs for reference dosimetry with a maximum difference of 1.84%. Percent depth dose measurement also shows that PLA+ has the best match with water and RMI457 within ±2.2% and ±1.6%, respectively. Overall, PLA+ phantoms match with RMI457 phantoms within ±3%. Significance and conclusion. The fabricated phantoms are excellent tissue equivalent equipment for synchrotron radiation dosimetry QA measurement. Both the rat and the anthropomorphic head phantoms are useful in synchrotron brain cancer radiotherapy dosimetry, experiments, and future clinical translation of synchrotron radiotherapy and imaging.

Successful transition of synchrotron-based microbeam radiation therapy (MRT) from pre-clinical animal studies to human trials is dependent upon ensuring that there are sufficient and adequate measures in place for quality assurance purposes. Transmission detectors provide researchers and clinicians with a real-time quality assurance and beam-monitoring instrument to ensure safe and accurate dose delivery. In this work, the effect of transmission detectors of different thicknesses (10 and 375 µm) upon the photon energy spectra and dose deposition of spatially fractionated synchrotron radiation is quantified experimentally and by means of a dedicated Geant4 simulation study. The simulation and experimental results confirm that the presence of the 375 µm thick transmission detector results in an approximately 1–6% decrease in broad-beam and microbeam peak dose. The capability to account for the reduction in dose and change to the peak-to-valley dose ratio justifies the use of transmission detectors as thick as 375 µm in MRT provided that treatment planning systems are able to account for their presence. The simulation and experimental results confirm that the presence of the 10 µm thick transmission detector shows a negligible impact (<0.5%) on the photon energy spectra, dose delivery and microbeam structure for both broad-beam and microbeam cases. Whilst the use of 375 µm thick detectors would certainly be appropriate, based upon the idea of best practice the authors recommend that 10 µm thick transmission detectors of this sort be utilized as a real-time quality assurance and beam-monitoring tool during MRT.

Objective. This study aims to characterize radiological properties of selected additive manufacturing (AM) materials utilizing both material extrusion and vat photopolymerization technologies. Monochromatic synchrotron x-ray images and synchrotron treatment beam dosimetry were acquired at the hutch 3B and 2B of the Australian Synchrotron-Imaging and Medical Beamline. Approach. Eight energies from 30 keV up to 65 keV were used to acquire the attenuation coefficients of the AM materials. Comparison of theoretical, and experimental attenuation data of AM materials and standard solid water for MV linac was performed. Broad-beam dosimetry experiment through attenuated dose measurement and a Geant4 Monte Carlo simulation were done for the studied materials to investigate its attenuation properties specific for a 4 tesla wiggler field with varying synchrotron radiation beam qualities. Main results. Polylactic acid (PLA) plus matches attenuation coefficients of both soft tissue and brain tissue, while acrylonitrile butadiene styrene, Acrylonitrile styrene acrylate, and Draft resin have close equivalence to adipose tissue. Lastly, PLA, co-polyester plus, thermoplastic polyurethane, and White resins are promising substitute materials for breast tissue. For broad-beam experiment and simulation, many of the studied materials were able to simulate RMI457 Solid Water and bolus within ±10% for the three synchrotron beam qualities. These results are useful in fabricating phantoms for synchrotron and other related medical radiation applications such as orthovoltage treatments. Significance and conclusion. These 3D printing materials were studied as potential substitutes for selected tissues such as breast tissue, adipose tissue, soft-tissue, and brain tissue useful in fabricating 3D printed phantoms for synchrotron imaging, therapy, and orthovoltage applications. Fabricating customizable heterogeneous anthropomorphic phantoms (e.g. breast, head, thorax) and pre-clinical animal phantoms (e.g. rodents, canine) for synchrotron imaging and radiotherapy using AM can be done based on the results of this study.