Synchrotron facilities produce ultra-high dose rate X-rays that can be used for selective cancer treatment when combined with micron-sized beams. Synchrotron microbeam radiation therapy (MRT) has been shown to inhibit cancer growth in small animals, whilst preserving healthy tissue function. However, the underlying mechanisms that produce successful MRT outcomes are not well understood, either in vitro or in vivo. This study provides new insights into the relationships between dosimetry, radiation transport simulations, in vitro cell response, and pre-clinical brain cancer survival using intracerebral gliosarcoma (9LGS) bearing rats. As part of this ground-breaking research, a new image-guided MRT technique was implemented for accurate tumor targeting combined with a pioneering assessment of tumor dose-coverage; an essential parameter for clinical radiotherapy. Based on the results of our study, we can now (for the first time) present clear and reproducible relationships between the in vitro cell response, tumor dose-volume coverage and survival post MRT irradiation of an aggressive and radioresistant brain cancer in a rodent model. Our innovative and interdisciplinary approach is illustrated by the results of the first long-term MRT pre-clinical trial in Australia. Implementing personalized synchrotron MRT for brain cancer treatment will advance this international research effort towards clinical trials.

Gold nanoparticles have demonstrated significant radiosensitization of cancer treatment with x-ray radiotherapy. To understand the mechanisms at the basis of nanoparticle radiosensitization, Monte Carlo simulations are used to investigate the dose enhancement, given a certain nanoparticle concentration and distribution in the biological medium. Earlier studies have ordinarily used condensed history physics models to predict nanoscale dose enhancement with nanoparticles. This study uses Geant4-DNA complemented with novel track structure physics models to accurately describe electron interactions in gold and to calculate the dose surrounding gold nanoparticle structures at nanoscale level. The computed dose in silico due to a clinical kilovoltage beam and the presence of gold nanoparticles was related to in vitro brain cancer cell survival using the local effect model. The comparison of the simulation results with radiobiological experimental measurements shows that Geant4-DNA and local effect model can be used to predict cell survival in silico in the case of x-ray kilovoltage beams.

Nanoparticles, with their distinct properties that vary from their bulk material equivalent, continue to gain popularity for studies into multi-modal applications in medicine. This research introduces the use of thulium oxide nanoparticles for biological applications and characterizes the potential of this novel nanoparticle for image-guided radiotherapy of brain cancer. In this study, we investigate the structural characteristics of this nanoparticle, and reveal a significant dose enhancement towards radioresistant brain tumour cells in vitro that also underlies an improvement in the CT image contrast of brain tumours in vivo . The thulium oxide nanoparticles utilized in the investigations described in this article were measured to be 40–45 nm from x-ray diffraction and scanning electron microscopy data. In vitro investigations assessed the cell survival and DNA damage in 9 l gliosarcoma cells following irradiation with 150 kVp orthovoltage x-rays. Immediately after the 150 kVp irradiation (15 min) an increase in the number of γ -H2AX induced foci indicates the production of more double-strand DNA breaks. Following from the short time-frame irradiation outcomes, clonogenic cell survival assays confirmed long-term radio-sensitization, with the cell sensitivity increasing by a factor of 1.32 (measured at the 10% survival fraction) for the irradiated 9 l cells exposed to thulium nanoparticles. A simple CT experiment shows that our thulium nanoparticles suspended in water at concentrations >0.5 mg ml ⁻¹ (0.05–20 mg ml ⁻¹ investigated) are clearly observable against water. Extending the CT experiment to an in vivo investigation, cellular uptake of the nanoparticles was demonstrated through CT image enhancement of the cancer site in 9- to 10-week-old Fisher rats bearing 9 l gliosarcomas, 12 days after cell implantation. The 9 l cancer is clearly visible on the CT image after injecting 40 μ g of nanoparticles (2 μ l at 20 mg ml ⁻¹ ) directly to the cancer site (5.5 mm from the dura and 3.5 mm right laterally of the bregma, 5 mm depth). To our knowledge, this work demonstrates the first application of thulium nanoparticles in biology and medicine, for radiotherapy and image guidance purposes

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.

Microbeam radiation therapy (MRT) utilizes coplanar synchrotron radiation beamlets and is a proposed treatment approach for several tumor diagnoses that currently have poor clinical treatment outcomes, such as gliosarcomas. Monte Carlo (MC) simulations are one of the most used methods at the Imaging and Medical Beamline, Australian Synchrotron to calculate the dose in MRT preclinical studies. The steep dose gradients associated with the 50$\mathsf{\mu }$m-wide coplanar beamlets present a significant challenge for precise MC simulation of the dose deposition of an MRT irradiation treatment field in a short time frame. The long computation times inhibit the ability to perform dose optimization in treatment planning or apply online image-adaptive radiotherapy techniques to MRT. Much research has been conducted on fast dose estimation methods for clinically available treatments. However, such methods, including GPU Monte Carlo implementations and machine learning (ML) models, are unavailable for novel and emerging cancer radiotherapy options such as MRT. In this work, the successful application of a fast and accurate ML dose prediction model for a preclinical MRT rodent study is presented for the first time. The ML model predicts the peak doses in the path of the microbeams and the valley doses between them, delivered to the tumor target in rat patients. A CT imaging dataset is used to generate digital phantoms for each patient. Augmented variations of the digital phantoms are used to simulate with Geant4 the energy depositions of an MRT beam inside the phantoms with 15% (high-noise) and 2% (low-noise) statistical uncertainty. The high-noise MC simulation data are used to train the ML model to predict the energy depositions in the digital phantoms. The low-noise MC simulations data are used to test the predictive power of the ML model. The predictions of the ML model show an agreement within 3% with low-noise MC simulations for at least 77.6% of all predicted voxels (at least 95.9% of voxels containing tumor) in the case of the valley dose prediction and for at least 93.9% of all predicted voxels (100.0% of voxels containing tumor) in the case of the peak dose prediction. The successful use of high-noise MC simulations for the training, which are much faster to produce, accelerates the production of the training data of the ML model and encourages transfer of the ML model to different treatment modalities for other future applications in novel radiation cancer therapies.

Recommendations for an experimental protocol for beam alignment/optimization and dosimetry relating to in vitro studies at the Imaging and Medical Beam Line of the Australian Synchrotron are presented. An evaluation of the protocol, based upon the consistency and reproducibility of in vitro experiments performed over several years at the Australian Synchrotron, is provided for the community.