132 research outputs found

    Optically stimulated nanodosimeters with high storage capacity

    Get PDF
    In this work we report on the thermoluminescence (TL) and optically stimulated luminescence (OSL) properties of beta-Na(Gd,Lu)F-4:Tb3+ nanophosphors prepared via a standard high-temperature coprecipitation route. Irradiating this phosphor with X-rays not only produces radioluminescence but also leads to a bright green afterglow that is detectable up to hours after excitation has stopped. The storage capacity of the phosphor was found to be (2.83 +/- 0.05) x 10(16) photons/gram, which is extraordinarily high for nano-sized particles and comparable to the benchmark bulk phosphor SrAl2O4:Eu2+,Dy3+. By combining TL with OSL, we show that the relatively shallow traps, which dominate the TL glow curves and are responsible for the bright afterglow, can also be emptied optically using 808 or 980 nm infrared light while the deeper traps can only be emptied thermally. This OSL at therapeutically relevant radiation doses is of high interest to the medical dosimetry community, and is demonstrated here in uniform, solution-processable nanocrystals

    Model-based scenario analysis of the impact of remediation measures on metal leaching from soils contaminated by historic smelter emissions

    Get PDF
    A spatially distributed model for leaching of Cd from the unsaturated zone was developed for the Belgian-Dutch transnational Kempen region. The model uses as input land-use maps, atmospheric deposition data, and soil data and is part of a larger regional model that simulates transport of Cd in soil, groundwater, and surface water. A new method for deriving deposition from multiple sites was validated using soil data in different wind directions. Leaching was calculated for the period 1890 to 2010 using a reconstruction of metal loads in the region. The model was able to reproduce spatial patterns of concentrations in soil and groundwater and predicted the concentration in shallow groundwater adequately well for the purpose of evaluating management options. For 42% of the data points, measurements and calculations were within the same concentration class. The model was used for forecasting under a reference scenario, an autonomous development scenario including climate change, and a scenario with implementation of remediation measures. The impact of autonomous development (under the most extreme scenario of climatic change) amounted to an increase of 10% in cumulative Cd flux after 100 yr as compared with the reference scenario. The impact of remediation measures was mainly local and is less pronounced (i.e., only 3% change in cumulative flux at the regional scale). The integrated model served as a tool to assist in developing management strategies and prioritization of remediation of the wide-spread heavy metal contamination in the region

    Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer

    Full text link
    Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics is foreseen as an essential prognostic tool for cancer risk assessment and the quantification of intratumoural heterogeneity. In this work, 1615 radiomic features (quantifying tumour image intensity, shape, texture) extracted from pre-treatment FDG-PET and CT images of 300 patients from four different cohorts were analyzed for the risk assessment of locoregional recurrences (LR) and distant metastases (DM) in head-and-neck cancer. Prediction models combining radiomic and clinical variables were constructed via random forests and imbalance-adjustment strategies using two of the four cohorts. Independent validation of the prediction and prognostic performance of the models was carried out on the other two cohorts (LR: AUC = 0.69 and CI = 0.67; DM: AUC = 0.86 and CI = 0.88). Furthermore, the results obtained via Kaplan-Meier analysis demonstrated the potential of radiomics for assessing the risk of specific tumour outcomes using multiple stratification groups. This could have important clinical impact, notably by allowing for a better personalization of chemo-radiation treatments for head-and-neck cancer patients from different risk groups.Comment: (1) Paper: 33 pages, 4 figures, 1 table; (2) SUPP info: 41 pages, 7 figures, 8 table

    A fast Monte Carlo code for proton transport in radiation therapy based on MCNPX

    No full text
    An important requirement for proton therapy is a software for dose calculation. Monte Carlo is the most accurate method for dose calculation, but it is very slow. In this work, a method is developed to improve the speed of dose calculation. The method is based on pre-generated tracks for particle transport. The MCNPX code has been used for generation of tracks. A set of data including the track of the particle was produced in each particular material (water, air, lung tissue, bone, and soft tissue). This code can transport protons in wide range of energies (up to 200 MeV for proton). The validity of the fast Monte Carlo (MC) code is evaluated with data MCNPX as a reference code. While analytical pencil beam algorithm transport shows great errors (up to 10%) near small high density heterogeneities, there was less than 2% deviation of MCNPX results in our dose calculation and isodose distribution. In terms of speed, the code runs 200 times faster than MCNPX. In the Fast MC code which is developed in this work, it takes the system less than 2 minutes to calculate dose for 10 6 particles in an Intel Core 2 Duo 2.66 GHZ desktop computer
    corecore