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10.1259/bjr.20200538 http://scihub22266oqcxt.onion/10.1259/bjr.20200538 32758014!7465853!32758014     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Br+J+Radiol 2020 ; 93 (1113): 20200538 Nephropedia Template TP {{tp|p=32758014|t=2020. Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances |pdf=|usr=}}{{32758014}} gab.com Text Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances JO: Br J Radiol http://www.kidney.de/pget.php?&tw=1&pmid=32758014 #FOAvip COVID-19 pneumonia is a newly recognized lung infection. Initially, CT imaging was demonstrated to be one of the most sensitive tests for the detection of infection. Currently, with broader availability of polymerase chain reaction for disease diagnosis, CT is mainly used for the identification of complications and other defined clinical indications in hospitalized patients. Nonetheless, radiologists are interpreting lung imaging in unsuspected patients as well as in suspected patients with imaging obtained to rule out other relevant clinical indications. The knowledge of pathological findings is also crucial for imagers to better interpret various imaging findings. Identification of the imaging findings that are commonly seen with the disease is important to diagnose and suggest confirmatory testing in unsuspected cases. Proper precautionary measures will be important in such unsuspected patients to prevent further spread. In addition to understanding the imaging findings for the diagnosis of the disease, it is important to understand the growing set of tools provided by artificial intelligence. The goal of this review is to highlight common imaging findings using illustrative examples, describe the evolution of disease over time, discuss differences in imaging appearance of adult and pediatric patients and review the available literature on quantitative CT for COVID-19. We briefly address the known pathological findings of the COVID-19 lung disease that may help better understand the imaging appearance, and we provide a demonstration of novel display methodologies and artificial intelligence applications serving to support clinical observations. Twit Text FOAVip Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances ????Br J Radiol http://www.kidney.de/pget.php?&tw=1&pmid=32758014 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32758014 #FOAvip English Wikipedia <ref>{{Cite pmid|32758014}}</ref> Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances #MMPMID32758014 Nagpal P; Narayanasamy S; Vidholia A; Guo J; Shin KM; Lee CH; Hoffman EA Br J Radiol 2020[Sep]; 93 (1113): 20200538 PMID32758014show ga COVID-19 pneumonia is a newly recognized lung infection. Initially, CT imaging was demonstrated to be one of the most sensitive tests for the detection of infection. Currently, with broader availability of polymerase chain reaction for disease diagnosis, CT is mainly used for the identification of complications and other defined clinical indications in hospitalized patients. Nonetheless, radiologists are interpreting lung imaging in unsuspected patients as well as in suspected patients with imaging obtained to rule out other relevant clinical indications. The knowledge of pathological findings is also crucial for imagers to better interpret various imaging findings. Identification of the imaging findings that are commonly seen with the disease is important to diagnose and suggest confirmatory testing in unsuspected cases. Proper precautionary measures will be important in such unsuspected patients to prevent further spread. In addition to understanding the imaging findings for the diagnosis of the disease, it is important to understand the growing set of tools provided by artificial intelligence. The goal of this review is to highlight common imaging findings using illustrative examples, describe the evolution of disease over time, discuss differences in imaging appearance of adult and pediatric patients and review the available literature on quantitative CT for COVID-19. We briefly address the known pathological findings of the COVID-19 lung disease that may help better understand the imaging appearance, and we provide a demonstration of novel display methodologies and artificial intelligence applications serving to support clinical observations. |*Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/*diagnostic imaging/*pathology[MESH] |Humans[MESH] |Lung/diagnostic imaging/pathology[MESH] |Pandemics[MESH] |Pneumonia, Viral/*diagnostic imaging/*pathology[MESH] |Polymerase Chain Reaction/*methods[MESH] |SARS-CoV-2[MESH]Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances (epmc).pdf DeepDyve Pubget Overpricing