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Radiation, Volume 1, Issue 2 (June 2021) – 7 articles

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9 pages, 4065 KiB  
Article
Increased Radiation Dose Exposure in Thoracic Computed Tomography in Patients with Covid-19
by Massimo Cristofaro, Nicoletta Fusco, Ada Petrone, Fabrizio Albarello, Federica Di Stefano, Elisa Pianura, Vincenzo Schininà, Stefania Ianniello and Paolo Campioni
Radiation 2021, 1(2), 153-161; https://doi.org/10.3390/radiation1020014 - 08 Jun 2021
Cited by 5 | Viewed by 4120
Abstract
The CT manifestation of COVID-19 patients is now well known and essentially reflects pathological changes in the lungs. Actually, there is insufficient knowledge on the long-term outcomes of this new disease, and several chest CTs might be necessary to evaluate the outcomes. The [...] Read more.
The CT manifestation of COVID-19 patients is now well known and essentially reflects pathological changes in the lungs. Actually, there is insufficient knowledge on the long-term outcomes of this new disease, and several chest CTs might be necessary to evaluate the outcomes. The aim of this study is to evaluate the radiation dose for chest CT scans in COVID-19 patients compared to a cohort with pulmonary infectious diseases at the same time of the previous year to value if there is any modification of exposure dose. The analysis of our data shows an increase in the overall mean dose in COVID-19 patients compared with non-COVID-19 patients. In our results, the higher dose increase occurs in the younger age groups (+86% range 21–30 years and +67% range 31–40 years). Our results show that COVID-19 patients are exposed to a significantly higher dose of ionizing radiation than other patients without COVID infectious lung disease, and especially in younger age groups, although some authors have proposed the use of radiotherapy in these patients, which is yet to be validated. Our study has limitations: the use of one CT machine in a single institute and a limited number of patients. Full article
(This article belongs to the Section Radiation in Medical Imaging)
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8 pages, 737 KiB  
Article
Geochemical and Isotope Anomalies in Sioma River Gorge, Western Tajikistan
by Djamshed A. Abdushukurov, Daler Abdusamadzoda, Octavian G. Duliu and Marina V. Frontasyeva
Radiation 2021, 1(2), 145-152; https://doi.org/10.3390/radiation1020013 - 20 May 2021
Viewed by 2491
Abstract
For a better understanding of the previously observed increased natural radioactivity at the confluence of the Varzob and Sioma rivers, Central Tajikistan, the activity concentration of natural radioactive 40K, Th and U daughters as well as of the anthropogenic 137Cs were [...] Read more.
For a better understanding of the previously observed increased natural radioactivity at the confluence of the Varzob and Sioma rivers, Central Tajikistan, the activity concentration of natural radioactive 40K, Th and U daughters as well as of the anthropogenic 137Cs were determined in nine locations covering the entire Sioma River. The radiometric determinations evidenced, in addition to increased activity concentrations of Th and U daughter radionuclides, an anomalous accumulation of anthropic 137Cs and natural 210Pb in the middle of the Sioma gorge. Complementarily, the mass fractions of natural Th and U determined by instrumental neutron activation analysis evidenced an increased presence of Th and U, which, in some places, overpasses six-times the average mass fraction found in the upper continental crust. The possible influence of active air transport from the southern Tadjik plane during the Afghani storms, as well as the presence of actinide-rich minerals, were analyzed and discussed. Full article
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14 pages, 20750 KiB  
Article
LiF Nanoparticles Enhance Targeted Degradation of Organic Material under Low Dose X-ray Irradiation
by Felix Maye and Ayse Turak
Radiation 2021, 1(2), 131-144; https://doi.org/10.3390/radiation1020012 - 06 May 2021
Cited by 3 | Viewed by 3389
Abstract
The targeted irradiation of structures by X-rays has seen application in a variety of fields. Herein, the use of 5–10 nm LiF nanoparticles to locally enhance the degradation of an organic thin film, diindenoperylene, under hard X-ray irradiation, at relatively low ionizing radiation [...] Read more.
The targeted irradiation of structures by X-rays has seen application in a variety of fields. Herein, the use of 5–10 nm LiF nanoparticles to locally enhance the degradation of an organic thin film, diindenoperylene, under hard X-ray irradiation, at relatively low ionizing radiation doses, is shown. X-ray reflectivity analysis indicated that the film thickness increased 12.04 Å in air and 11.34 Å in a helium atmosphere, under a radiation dose of ∼65 J/cm2 for 3 h illumination with a bi-layer structure that contained submonolayer coverage of thermally evaporated LiF. This was accompanied by significant modification of the surface topography for the organic film, which initially formed large flat islands. Accelerated aging experiments suggested that localized heating was not a major mechanism for the observed changes, suggesting a photochemical mechanism due to the formation of reactive species from LiF under irradiation. As LiF has a tendency to form active defects under radiation across the energy spectrum, this could could open a new direction to explore the efficacy of LiF or similar optically active materials that form electrically active defects under irradiation in various applications that could benefit from enhanced activity, such as radiography or targeted X-ray irradiation therapies. Full article
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8 pages, 1696 KiB  
Article
Advances in CdZnTeSe for Radiation Detector Applications
by Utpal N. Roy, Giuseppe S. Camarda, Yonggang Cui and Ralph B. James
Radiation 2021, 1(2), 123-130; https://doi.org/10.3390/radiation1020011 - 25 Apr 2021
Cited by 16 | Viewed by 3906
Abstract
Detection of X- and gamma-rays is essential to a wide range of applications from medical imaging to high energy physics, astronomy, and homeland security. Cadmium zinc telluride (CZT) is the most widely used material for room-temperature detector applications and has been fulfilling the [...] Read more.
Detection of X- and gamma-rays is essential to a wide range of applications from medical imaging to high energy physics, astronomy, and homeland security. Cadmium zinc telluride (CZT) is the most widely used material for room-temperature detector applications and has been fulfilling the requirements for growing detection demands over the last three decades. However, CZT still suffers from the presence of a high density of performance-limiting defects, such as sub-grain boundary networks and Te inclusions. Cadmium zinc telluride selenide (CZTS) is an emerging material with compelling properties that mitigate some of the long-standing issues seen in CZT. This new quaternary is free from sub-grain boundary networks and possesses very few Te inclusions. In addition, the material offers a high degree of compositional homogeneity. The advancement of CZTS has accelerated through investigations of the material properties and virtual Frisch-grid (VFG) detector performance. The excellent material quality with highly reduced performance-limiting defects elevates the importance of CZTS as a potential replacement to CZT at a substantially lower cost. Full article
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7 pages, 2593 KiB  
Article
Quality of Hand Radiograph Collimation Determined by Artificial Intelligence Algorithm Correlates with Radiograph Quality Scores Assigned by Radiologists
by Oganes Ashikyan, Donald Chan, Daniel S. Moore, Uma Thakur and Avneesh Chhabra
Radiation 2021, 1(2), 116-122; https://doi.org/10.3390/radiation1020010 - 08 Apr 2021
Cited by 1 | Viewed by 3343
Abstract
Providing direct feedback to technologists has become challenging for radiologists due to geographic separation and other reasons. As such, there is a need for automated solutions to solve quality issues in radiography. We evaluated the feasibility of using a computer vision artificial intelligence [...] Read more.
Providing direct feedback to technologists has become challenging for radiologists due to geographic separation and other reasons. As such, there is a need for automated solutions to solve quality issues in radiography. We evaluated the feasibility of using a computer vision artificial intelligence (AI) algorithm to classify hand radiographs into quality categories in order to automate quality assurance processes in radiology. A bounding box was placed over the hand on 300 hand radiographs. These inputs were employed to train the computational neural network (CNN) to automatically detect hand boundaries. The trained CNN detector was used to place bounding boxes over the hands on an additional 100 radiographs, independently of the training or validation sets. A computer algorithm processed each output image to calculate unused air spaces. The same 100 images were classified by two musculoskeletal radiologists into four quality categories. The correlation between the AI-calculated unused space metric and radiologist-assigned quality scores was determined using the Spearman correlation coefficient. The kappa statistic was used to calculate the inter-reader agreement. The best negative correlation between the AI-assigned metric and the radiologists’ assigned quality scores was achieved using the calculation of the unused space at the top of the image. The Spearman correlation coefficients were −0.7 and −0.6 for the two radiologists. The kappa correlation coefficient for interobserver agreement between the two radiologists was 0.6. Automatic calculation of the percentage of unused space or indirect collimation at the top of hand radiographs correlates moderately well with radiographic collimation quality. Full article
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21 pages, 340 KiB  
Review
Use of Biological Dosimetry for Monitoring Medical Workers Occupationally Exposed to Ionizing Radiation
by Igor Piotrowski, Aleksandra Dawid, Katarzyna Kulcenty and Wiktoria Maria Suchorska
Radiation 2021, 1(2), 95-115; https://doi.org/10.3390/radiation1020009 - 31 Mar 2021
Cited by 4 | Viewed by 4472
Abstract
Medical workers are the largest group exposed to man-made sources of ionizing radiation. The annual doses received by medical workers have decreased over the last several decades, however for some applications, like fluoroscopically guided procedures, the occupational doses still remain relatively high. Studies [...] Read more.
Medical workers are the largest group exposed to man-made sources of ionizing radiation. The annual doses received by medical workers have decreased over the last several decades, however for some applications, like fluoroscopically guided procedures, the occupational doses still remain relatively high. Studies show that for some procedures the operator and staff still use insufficient protective and dosimetric equipment, which might cause an underestimation of medical exposures. Physical dosimetry methods are a staple for estimating occupational exposures, although due to the inconsistent use of protection measures, an alternative method such as biological dosimetry might complement the physical methods to achieve a more complete picture. Such methods were used to detect exposures to doses as low as 0.1 mSv/year, and could be useful for a more accurate assessment of genotoxic effects of ionizing radiation in medical workers. Biological dosimetry is usually based on the measurement of the effects present in peripheral blood lymphocytes. Although some methods, such as chromosome aberration scoring or micronucleus assay, show promising results, currently there is no one method recognized as most suitable for dosimetric application in the case of chronic, low-dose exposures. In this review we decided to evaluate different methods used for biological dosimetry in assessment of occupational exposures of medical workers. Full article
16 pages, 14687 KiB  
Article
Automated Cytogenetic Biodosimetry at Population-Scale
by Peter K. Rogan, Eliseos J. Mucaki, Ben C. Shirley, Yanxin Li, Ruth C. Wilkins, Farrah Norton, Olga Sevriukova, Ngoc-Duy Pham, Ed Waller and Joan H. M. Knoll
Radiation 2021, 1(2), 79-94; https://doi.org/10.3390/radiation1020008 - 29 Mar 2021
Cited by 2 | Viewed by 4315
Abstract
The dicentric chromosome (DC) assay accurately quantifies exposure to radiation; however, manual and semi-automated assignment of DCs has limited its use for a potential large-scale radiation incident. The Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software automates unattended DC detection and determines [...] Read more.
The dicentric chromosome (DC) assay accurately quantifies exposure to radiation; however, manual and semi-automated assignment of DCs has limited its use for a potential large-scale radiation incident. The Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software automates unattended DC detection and determines radiation exposures, fulfilling IAEA criteria for triage biodosimetry. This study evaluates the throughput of high-performance ADCI (ADCI-HT) to stratify exposures of populations in 15 simulated population scale radiation exposures. ADCI-HT streamlines dose estimation using a supercomputer by optimal hierarchical scheduling of DC detection for varying numbers of samples and metaphase cell images in parallel on multiple processors. We evaluated processing times and accuracy of estimated exposures across census-defined populations. Image processing of 1744 samples on 16,384 CPUs required 1 h 11 min 23 s and radiation dose estimation based on DC frequencies required 32 sec. Processing of 40,000 samples at 10 exposures from five laboratories required 25 h and met IAEA criteria (dose estimates were within 0.5 Gy; median = 0.07). Geostatistically interpolated radiation exposure contours of simulated nuclear incidents were defined by samples exposed to clinically relevant exposure levels (1 and 2 Gy). Analysis of all exposed individuals with ADCI-HT required 0.6–7.4 days, depending on the population density of the simulation. Full article
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