A comparison of COVID-19 and imaging radiation risk in clinical patient populations.
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2020-10-07
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Abstract
OBJECTIVE: The outbreak of coronavirus SARS-COV2 affected more than 180 countries necessitating fast and accurate diagnostic tools. Reverse transcriptase polymerase chain reaction (RT-PCR) has been identified as a gold standard test with Chest CT and Chest Radiography showing promising results as well. However, radiological solutions have not been used extensively for the diagnosis of COVID-19 disease, partly due to radiation risk. This study aimed to provide quantitative comparison of imaging radiation risk versus COVID risk. METHODS: The analysis was performed in terms of mortality rate per age group. COVID-19 mortality was extracted from epidemiological data across 299,004 patients published by ISS-Integrated surveillance of COVID-19 in Italy. For radiological risk, the study considered 659 Chest CT performed in adult patients. Organ doses were estimated using a Monte Carlo method and then used to calculate Risk Index that was converted into an upper bound for related mortality rate following NCI-SEER data. RESULTS: COVID-19 mortality showed a rapid rise for ages >30 years old (min:0.30%; max:30.20%), whereas only 1 death was reported in the analyzed patient cohort for ages <20 years old. The rates decreased for radiation risk across age groups. The median mortality rate across all ages for Chest-CT and Chest-Radiography were 0.007% (min:0.005%; max:0.011%) and 0.0003% (min:0.0002%; max:0.0004%), respectively. CONCLUSIONS: COVID-19, Chest Radiography, and Chest CT mortality rates showed different magnitudes and trends across age groups. In higher ages, the risk of COVID-19 far outweighs that of radiological exams. Based on risk comparison alone, Chest Radiography and CT for COVID-19 care is justified for patients older than 20 and 30 years old, respectively. Notwithstanding other aspects of diagnosis, the present results capture a component of risk consideration associated with the use of imaging for COVID. Once integrated with other diagnostic factors, they may help inform better management of the pandemic.
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Ria, Francesco, Wanyi Fu, Hamid Chalian, Ehsan Abadi, Paul W Segars, Rafael Fricks, Pegah Khoshpouri, Ehsan Samei, et al. (2020). A comparison of COVID-19 and imaging radiation risk in clinical patient populations. J Radiol Prot. 10.1088/1361-6498/abbf3b Retrieved from https://hdl.handle.net/10161/21590.
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Francesco Ria
Dr. Francesco Ria is a medical physicist and he serves as an Assistant Professor in the Department of Radiology. Francesco has an extensive expertise in the assessment of procedure performances in radiology. In particular, his research activities focus on the simultaneous evaluation of radiation dose and image quality in vivo in computed tomography providing a comprehensive evaluation of radiological exams. Moreover, Francesco is developing and investigating novel mathematical models that, uniquely in the radiology field, can incorporate a comprehensive and quantitative risk-to-benefit assessment of the procedures; he is continuing to apply his expertise towards the definition of new patient specific risk metrics, and in the assessment of image quality in vivo also using state-of-the-art imaging technology, such as photon counting computed tomography scanners, and machine learning reconstruction algorithms.
Dr. Ria is a member of the American Association of Physicists in Medicine (AAPM) task group 392 (Investigation and Quality Control of Automatic Exposure Control System in CT), of the AAPM task group 430 (Comprehensive quantification and dissemination of patient-model-based organ and effective dose estimations and their associated uncertainties for CT examinations), of the AAPM Medicine Public Education working group (WGATE), and of the Italian Association of Medical Physics task group Dose Monitoring in Diagnostic Imaging.
Ehsan Abadi
Ehsan Abadi, PhD is an imaging scientist at Duke University. He serves as an Associate Professor in the departments of Radiology and Electrical & Computer Engineering, a faculty member in the Medical Physics Graduate Program and Carl E. Ravin Advanced Imaging Laboratories, and a co-Lead in the Center for Virtual Imaging Trials. Ehsan’s research focuses on quantitative imaging and optimization, computational human modeling, medical imaging simulation, and CT imaging in cardiothoracic and musculoskeletal applications. He is actively involved in developing computational anthropomorphic models with various diseases such as COPD, and scanner-specific simulation platforms (e.g., DukeSim) for imaging systems. Currently, his work is centered on identifying and optimizing imaging systems to ensure accurate and precise quantifications of lung and bone diseases.
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