Prototype of the front-end circuit for the GOSSIP (Gas On Slimmed Silicon Pixel) chip in the 0.13 μm CMOS technology

The new GOSSIP detector, capable to detect single electrons in gas, has certain advantages with respect silicon (pixel) detectors. It does not require a Si sensor; it has a very low detector parasitic capacitance and a zero bias current at the pixel input. These are attractive features to design a compact, low-noise and low-power integrated input circuit. A prototype of the integrated circuit has been developed in 0.13 μm CMOS technology. It includes a few channels equipped with preamplifier, discriminator and the digital circuit to study the feasibility of the TDC-perpixel concept. The design demonstrates very low input referred noise (60e- RMS) in combination with a fast peaking time (40 ns) and an analog power dissipation as low as 2 μW per channel. Switching activity on the clock bus (up to 100 MHz) in the close vicinity of the pixel input pads does not cause noticeable extra noise

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

A Monte-Carlo-based study of a single-2D-detector proton-radiography system

PURPOSE: To assess the feasibility of a proton radiography (pRG) system based on a single thin pixelated detector for water-equivalent path length (WEPL) and relative stopping power (RSP) measurements.METHODS: A model of a pRG system consisting of a single pixelated detector measuring energy deposition and proton fluence was investigated in a Geant4-based Monte Carlo study. At the position directly after an object traversed by a broad proton beam, spatial 2D distributions are calculated of the energy deposition in, and the number of protons entering the detector. Their ratio relates to the 2D distribution of the average stopping power of protons in the detector. The system response is calibrated against the residual range in water of the protons to provide the 2D distribution of the WEPL of the object. The WEPL distribution is converted into the distribution of the RSP of the object. Simulations have been done, where the system has been tested on 13 samples of homogeneous materials of which the RSPs have been calculated and compared with RSPs determined from simulations of residual-range-in-water, which we refer to as reference RSPs.RESULTS: For both human-tissue- and non-human-tissue-equivalent materials, the RSPs derived with the detector agree with the reference values within 1%.CONCLUSION: The study shows that a pRG system based on one thin pixelated detection screen has the potential to provide RSP predictions with an accuracy of 1%.</p

Footprint and height corrections for UAV-borne gamma-ray spectrometry studies

Advancements in the development of gamma-ray spectrometers (GRS) have led to small and lightweight spectrometers that can be used under unmanned aerial vehicles (UAVs). Airborne GRS measurements are used to determine radionuclide concentrations in the ground, among which the natural occurring radionuclides K-40, U-238, and Th-232. For successful applications of these GRS sensors, it is important that absolute values of concentrations can be measured. To extract these absolute radionuclide concentrations, airborne gamma-ray data has to be corrected for measurement height. However, the current analysis models are only valid for the height range of 50-250 m. The purpose of this study is to develop a procedure that correctly predicts the true radionuclide concentration in the ground when measuring in the UAV operating range of 0-40 m. An analytical model is developed to predict the radiation footprint as a function of height. This model is used as a tool to properly determine a source-detector geometry to be used in Monte-Carlo simulations of detector response at various elevations between 0 and 40 m. The analytical model predicts that the smallest achievable footprint at 10 m height lies between 22 and 91 m and between 40 and 140 m at 20 m height. By using Monte-Carlo simulations it is shown that the analytical model correctly predicts the reduction in full energy peak gamma-rays, but does not predict the Compton continuum of a spectrum as a function of height. Therefore, Monte-Carlo simulations should be used to predict the shape and intensity of gamma-ray spectra as a function of height. A finite set of Monte-Carlo simulations at intervals of 5 m were used for the analysis of GRS measurements at heights up to 35 m. The resulting radionuclide concentrations at every height agree with the radionuclide concentration measured on the ground

AYAs' online information and ehealth needs:A comparison with healthcare professionals' perceptions

Background Adolescents and young adults (AYAs) diagnosed with cancer fulfill their cancer-related information needs often via the Internet. Healthcare professionals (HCPs) have a crucial role in guiding patients in finding appropriate online information and eHealth sources, a role that is often overlooked. Misperceptions of AYAs' needs by HCPs may lead to suboptimal guidance. We aimed to examine the extent to which AYAs' online information and eHealth needs corresponded with HCPs' perceptions of these needs. Methods Two cross-sectional online surveys (AYAs, n = 299; HCP, n = 80) on online information and eHealth needs were conducted. HCPs provided indications of their perceptions of AYA's needs. Results AYAs reported significantly more online information needs compared with HCPs' perceptions regarding: survival rates (AYA = 69%, HCP = 35%, p < 0.001), treatment guidelines (AYA = 65%, HCP = 41%, p < 0.001), return of cancer (AYA = 76%, HCP = 59%, p = 0.004), “what can I do myself” (AYA = 68%, HCP = 54%, p = 0.029), and metastases (AYA = 64%, HCP = 50%, p = 0.040). Significantly more unmet eHealth needs were reported by AYAs compared with HCPs relating to access to own test results (AYA = 25, HCP = 0%, p < 0.001), request tests (AYA = 30%, HCP = 7%, p < 0.001), medical information (AYA = 22%, HCP = 0%, p = 0.001), e-consult with nurses (AYA = 30%, HCP = 10%, p < 0.001), e-consult with physicians (AYA = 38%, HCP = 13%, p = 0.001), and request prescriptions (AYA = 33%, HCP = 21%, p = 0.009). Conclusion AYAs' online information and eHealth needs are partially discrepant with the impression HCPs have, which could result in insufficient guidance related to AYAs' needs. AYAs and HCPs should get guidance regarding where to find optimal information in a language they understand. This may contribute to AYAs' access, understanding, and satisfaction regarding online information and eHealth