A simulation framework for preclinical proton irradiation workflow.

Objective.The integration of proton beamlines with x-ray imaging/irradiation platforms has opened up possibilities for image-guided Bragg peak irradiations in small animals. Such irradiations allow selective targeting of normal tissue substructures and tumours. However, their small size and location pose challenges in designing experiments. This work presents a simulation framework useful for optimizing beamlines, imaging protocols, and design of animal experiments. The usage of the framework is demonstrated, mainly focusing on the imaging part.Approach.The fastCAT toolkit was modified with Monte Carlo (MC)-calculated primary and scatter data of a small animal imager for the simulation of micro-CT scans. The simulated CT of a mini-calibration phantom from fastCAT was validated against a full MC TOPAS CT simulation. A realistic beam model of a preclinical proton facility was obtained from beam transport simulations to create irradiation plans in matRad. Simulated CT images of a digital mouse phantom were generated using single-energy CT (SECT) and dual-energy CT (DECT) protocols and their accuracy in proton stopping power ratio (SPR) estimation and their impact on calculated proton dose distributions in a mouse were evaluated.Main results.The CT numbers from fastCAT agree within 11 HU with TOPAS except for materials at the centre of the phantom. Discrepancies for central inserts are caused by beam hardening issues. The root mean square deviation in the SPR for the best SECT (90 kV/Cu) and DECT (50 kV/Al-90 kV/Al) protocols are 3.7% and 1.0%, respectively. Dose distributions calculated for SECT and DECT datasets revealed range shifts <0.1 mm, gamma pass rates (3%/0.1 mm) greater than 99%, and no substantial dosimetric differences for all structures. The outcomes suggest that SECT is sufficient for proton treatment planning in animals.Significance.The framework is a useful tool for the development of an optimized experimental configuration without using animals and beam time.

Proton therapy induces a local microglial neuroimmune response.

BACKGROUND AND PURPOSE: Although proton therapy is increasingly being used in the treatment of paediatric and adult brain tumours, there are still uncertainties surrounding the biological effect of protons on the normal brain. Microglia, the brain-resident macrophages, have been shown to play a role in the development of radiation-induced neurotoxicity. However, their molecular and hence functional response to proton irradiation remains unknown. This study investigates the effect of protons on microglia by comparing the effect of photons and protons as well as the influence of age and different irradiated volumes. MATERIALS AND METHODS: Rats were irradiated with 14 Gy to the whole brain with photons (X-rays), plateau protons, spread-out Bragg peak (SOBP) protons or to 50 % anterior, or 50 % posterior brain sub-volumes with plateau protons. RNA sequencing, validation of microglial priming gene expression using qPCR and high-content imaging analysis of microglial morphology were performed in the cortex at 12 weeks post irradiation. RESULTS: Photons and plateau protons induced a shared transcriptomic response associated with neuroinflammation. This response was associated with a similar microglial priming gene expression signature and distribution of microglial morphologies. Expression of the priming gene signature was less pronounced in juvenile rats compared to adults and slightly increased in rats irradiated with SOBP protons. High-precision partial brain irradiation with protons induced a local microglial priming response and morphological changes. CONCLUSION: Overall, our data indicate that the brain responds in a similar manner to photons and plateau protons with a shared local upregulation of microglial priming-associated genes, potentially enhancing the immune response to subsequent inflammatory challenges.

Deep learning-based segmentation of the thorax in mouse micro-CT scans.

For image-guided small animal irradiations, the whole workflow of imaging, organ contouring, irradiation planning, and delivery is typically performed in a single session requiring continuous administration of anaesthetic agents. Automating contouring leads to a faster workflow, which limits exposure to anaesthesia and thereby, reducing its impact on experimental results and on animal wellbeing. Here, we trained the 2D and 3D U-Net architectures of no-new-Net (nnU-Net) for autocontouring of the thorax in mouse micro-CT images. We trained the models only on native CTs and evaluated their performance using an independent testing dataset (i.e., native CTs not included in the training and validation). Unlike previous studies, we also tested the model performance on an external dataset (i.e., contrast-enhanced CTs) to see how well they predict on CTs completely different from what they were trained on. We also assessed the interobserver variability using the generalized conformity index ([Formula: see text]) among three observers, providing a stronger human baseline for evaluating automated contours than previous studies. Lastly, we showed the benefit on the contouring time compared to manual contouring. The results show that 3D models of nnU-Net achieve superior segmentation accuracy and are more robust to unseen data than 2D models. For all target organs, the mean surface distance (MSD) and the Hausdorff distance (95p HD) of the best performing model for this task (nnU-Net 3d_fullres) are within 0.16 mm and 0.60 mm, respectively. These values are below the minimum required contouring accuracy of 1 mm for small animal irradiations, and improve significantly upon state-of-the-art 2D U-Net-based AIMOS method. Moreover, the conformity indices of the 3d_fullres model also compare favourably to the interobserver variability for all target organs, whereas the 2D models perform poorly in this regard. Importantly, the 3d_fullres model offers 98% reduction in contouring time.

Characterization of a new tissue equivalent proportional counter for dosimetry of neutron and photon fields: comparison of measurements and Monte Carlo simulations.

The tissue equivalent proportional counter (TEPC) is widely recognized as an important dosimetric technique particularly for complex radiation fields. The Korea Astronomy and Space Science Institute (KASI) has recently developed a new spherical TEPC to monitor the space radiation environment in the low earth orbit. The purpose of this study is to examine the performance of the TEPC against standard photon (137Cs) and neutron (252Cf) sources through ground-based measurements and Monte Carlo simulations prior to its actual implementation. Lineal energy distributions, microdosimetric spectra and dosimetric quantities for a 2 µm simulated site in pure propane gas were determined for both sources. Both the measured and calculated 137Cs spectra were shown to occur below 11 keV µm-1 that is the typical range covered by photon sources. Complete coincidence of their electron edge regions was also observed. Meanwhile, the proton edge from the measured 252Cf spectra was found to be in good agreement with those from the simulated ones and the literature. The gamma, recoil proton and heavy ions peaks expected for neutron sources were well defined, albeit deviations in the gamma region. The absorbed dose and dose equivalent for both irradiation conditions were also successfully obtained. The dose equivalent for 252Cf was found to be ten times the absorbed dose whereas it remained the same for 137Cs. The discrepancies observed in the low lineal energy region for both irradiation conditions were caused by intrinsic limitations on the experimental set-up and simulation configurations. This mainly contributed to a difference in the measured and calculated dose mean lineal energies of about 4.1% and 8.7% for the photon and neutron cases, respectively. Nevertheless, fair consistency with published data suggested that our TEPC could adequately reproduce the expected microdosimetric distributions for complex radiation fields.