Proton radiography to improve proton radiotherapy: Simulation study at different proton beam energies

To improve the quality of cancer treatment with protons, a translation of X-ray Computed Tomography (CT) images into a map of the proton stopping powers needs to be more accurate. Proton stopping powers determined from CT images have systematic uncertainties in the calculated proton range in a patient of typically 3-4\% and even up to 10\% in region containing bone~\cite{USchneider1995,USchneider1996,WSchneider2000,GCirrone2007,HPaganetti2012,TPlautz2014,GLandry2013,JSchuemann2014}. As a consequence, part of a tumor may receive no dose, or a very high dose can be delivered in healthy ti\-ssues and organs at risks~(e.g. brain stem)~\cite{ACKnopf2013}. A transmission radiograph of high-energy protons measuring proton stopping powers directly will allow to reduce these uncertainties, and thus improve the quality of treatment. The best way to obtain a sufficiently accurate radiograph is by tracking individual protons traversing the phantom (patient)~\cite{GCirrone2007,TPlautz2014,VSipala2013}. In our simulations we have used an ideal position sensitive detectors measuring a single proton before and after a phantom, while the residual energy of a proton was detected by a BaF$_{2}$ crystal. To obtain transmission radiographs, diffe\-rent phantom materials have been irradiated with a 3x3~cm$^{2}$ scattered proton beam, with various beam energies. The simulations were done using the Geant4 simulation package~\cite{SAgostinelli2003}. In this study we focus on the simulations of the energy loss radiographs for various proton beam energies that are clinically available in proton radiotherapy.Comment: 6 pages, 6 figures, Presented at Jagiellonian Symposium on Fundamental and Applied Subatomic Physics, 7-12 June, 2015, Krak\'ow, Polan

Latent risk factors in operating theatres and intensive care units

The safety of an organization can be improved by investigating and correcting the many processes that shape performance at the __sharp end__. Errors do not occur of themselves, but arise within the context of the work environment. Where the environment is one that makes errors by individuals more likely, we can identify the underlying problems that will have been present in the system, often recognized but long tolerated. The factors that make errors more likely, can be characterized as Latent Risk Factors (LRFs). The prospective identification of LRFs can lead to removal of error-inducing conditions before they can contribute to patient injury. Identifying LRFs will improve patient safety by improving the conditions that set the working environment for the occurrence of errors. Interventions aimed at unfavorable LRFs may contribute to patient safety in the Operating Theatre. Staff from Operating Theatre and Intensive Care Unit is able to detect these shortcomings but differ in their scope of the present risks. Unfavorable LRFs can act as stressful triggers at the workplace. If staff cannot control such stress this may negatively affect their well-being. The key to a healthy workplace is to control the deficiencies in the structure of the working environment.UBL - phd migration 201

Sustainable heating requires integral approach

In the Netherlands, large amounts of natural gas are used to heat houses and offices. This leads to a significant amount of greenhouse gas emissions. As such, developing sustainable heating alternatives is an important part of the Dutch energy and climate policy, to create a climate neutral energy supply in 2050. For most sustainable heating alternatives, the energy carrier of the heating system changes. As a consequence, the related energy infrastructure should be involved as well. In other words, decision makers need to think outside of the building's 'box'

Characterisation of Medipix3 Silicon Detectors in a Charged-Particle Beam

While designed primarily for X-ray imaging applications, the Medipix3 ASIC can also be used for charged-particle tracking. In this work, results from a beam test at the CERN SPS with irradiated and non-irradiated sensors are presented and shown to be in agreement with simulation, demonstrating the suitability of the Medipix3 ASIC as a tool for characterising pixel sensors.Comment: 16 pages, 13 figure