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Comprehensive literature review on the radiographic findings, imaging modalities, and the role of radiology in the COVID-19 pandemic

Aman Pal, Abulhassan Ali, Timothy R. Young, Juan Oostenbrink, Akul Prabhakar, Amogh Prabhakar, Nina Deacon, Amar Arnold, Ahmed Eltayeb, Charles Yap, David M. Young, Alan Tang, Subramanian Lakshmanan, Ying Yi Lim, Martha Pokarowski, Pramath Kakodkar

2021World Journal of Radiology14 citationsDOIOpen Access PDF

Abstract

Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, over 103214008 cases have been reported, with more than 2231158 deaths as of January 31, 2021. Although the gold standard for diagnosis of this disease remains the reverse-transcription polymerase chain reaction of nasopharyngeal and oropharyngeal swabs, its false-negative rates have ignited the use of medical imaging as an important adjunct or alternative. Medical imaging assists in identifying the pathogenesis, the degree of pulmonary damage, and the characteristic features in each imaging modality. This literature review collates the characteristic radiographic findings of COVID-19 in various imaging modalities while keeping the preliminary focus on chest radiography, computed tomography (CT), and ultrasound scans. Given the higher sensitivity and greater proficiency in detecting characteristic findings during the early stages, CT scans are more reliable in diagnosis and serve as a practical method in following up the disease time course. As research rapidly expands, we have emphasized the CO-RADS classification system as a tool to aid in communicating the likelihood of COVID-19 suspicion among healthcare workers. Additionally, the utilization of other scoring Pal A et al. Review of COVID-19 radiographic findings

Topics & Concepts

MedicineRadiographyRadiologyCoronavirus disease 2019 (COVID-19)Gold standard (test)PandemicModalitiesChest radiographMedical physicsDiseaseMedical imagingModality (human–computer interaction)PathologyInfectious disease (medical specialty)Computer scienceSocial scienceSociologyHuman–computer interactionCOVID-19 diagnosis using AIUltrasound in Clinical ApplicationsCOVID-19 Clinical Research Studies