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Radiometric evaluation of Ouratea miersii (Planch.) Engl. From the Municipal Natural Park of Niterói, Brazilian Atlantic Rainforest remnant.
Appl Radiat Isot
November 2024
Federal Fluminense University, Department of General Biology (LARARA / LASBIV / LCR / PPGDOT), São Domingos, Niterói, RJ, 24210-201, Brazil. Electronic address:
Concern about radiation exposure to non-human biota and the environment has increased since the 1990s, resulting in several publications by UNSCEAR, IAEA, ICRP, among other agencies, which highlighted significant gaps in knowledge regarding non-human biota and resulted in the establishment of Reference Animals and Plants (RAPs). In Brazil, the Atlantic Forest biome has vast biodiversity, but there is a lack of information on the radiometric profile of plant species growing there. Thus, the objective of this study was to evaluate the radiometric profile of Ouratea miersii (Malpighiales), endemic to the Atlantic Rainforest, collected in the State of Rio de Janeiro, city of Niterói, at the Municipal Natural Park (PARNIT), which covers a region of protected Atlantic Rainforest.
View Article and Find Full Text PDFComparative effectiveness of digital variance and subtraction angiography in lower limb angiography: A Monte Carlo modelling approach.
Phys Med
December 2024
Semmelweis University, Department of Biophysics and Radiation Biology, Budapest, Hungary; Kinepict Health Ltd., Budapest, Hungary.
Objective: By modelling patient exposures of interventional procedures, this study compares the reduction of radiation detriment between Digital Variance Angiography (DVA) and Digital Subtraction Angiography (DSA).
Methods: The paper presents a retrospective risk assessment using an in-house developed tool on 107 patient exposures from a clinical trial of DVA used to diagnose peripheral arterial disease (PAD). DICOM exposure parameters were used to initiate the PENELOPE (PENetration and Energy LOss of Positrons and Electrons) Monte Carlo simulation, radiation quality and quantity, and irradiation geometry.
A strategy for achieving optimisation of radiological protection in digital radiology proposed by ICRP.
J Radiol Prot
November 2024
International Atomic Energy Agency, Vienna International Centre, 1400 Vienna, Austria.
Radiology is now predominantly a digital medium and this has extended the flexibility, efficiency and application of medical imaging. Achieving the full benefit of digital radiology requires images to be of sufficient quality to make a reliable diagnosis for each patient, while minimising risks from radiation exposure, and so involves a careful balance between competing objectives. When an optimisation programme is undertaken, a knowledge of patient doses from surveys can be valuable in identifying areas needing attention.
View Article and Find Full Text PDFA new tool for estimation of the in vivo distribution of intake radionuclides.
Radiat Prot Dosimetry
November 2024
Institute of Radiation Medicine, Fudan University, Shanghai 200032, China.
This study developed a more universal tool for estimating the in vivo distribution of intake radionuclides. The biokinetic models and transfer rates for intake radionuclides were cited from the publications of the International Commission on Radiological Protection (ICRP), and the models were transformed into a series of linear differential equations and numerically solved using the Scipy algorithm in Python. The user interfaces for model selection, data input and in vivo distribution calculations were designed using PyQt5.
View Article and Find Full Text PDFDevelopment of age-specific population-based paediatric computational phantoms for image-based data mining and other radiotherapy applications.
Biomed Phys Eng Express
November 2024
Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.
Computational anatomical models have many applications in paediatric radiotherapy. Age-specific computational anatomical models were historically developed to represent average and/or healthy individuals, where cancer patients may present with anatomical variations caused by the disease and/or treatment effects. We developed RT-PAL, a library of computational age-specific voxelized anatomical models tailored to represent the paediatric radiotherapy population.
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