Review
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Sep 28, 2021; 13(9): 258-282
Published online Sep 28, 2021. doi: 10.4329/wjr.v13.i9.258
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
Aman Pal, Abulhassan Ali, Timothy R Young, Juan Oostenbrink, Akul Prabhakar, Amogh Prabhakar, Nina Deacon, Amar Arnold, Ahmed Eltayeb, Charles Yap, Subramanian Lakshmanan, Ying Yi Lim, Pramath Kakodkar, School of Medicine, National University of Ireland Galway, Galway H91 TK33, Galway, Ireland
David M Young, Department of Computer Science, Yale University, New Haven, CO 06520, United States
Alan Tang, Department of Health Science, Duke University, Durham, NC 27708, United States
Martha Pokarowski, The Hospital for Sick Kids, University of Toronto, Toronto M5S, Ontario, Canada
Author contributions: Pal A, Ali A, Young TR, Oostenbrink J, Prabhakar A, Prabhakar A, Deacon N, Arnold A, Yap C, Young DM, Tang A, Lakshmanan S, and Kakodkar P performed acquisition and curation of the data; Pal A, Ali A, Young TR and Kakodkar P analyzed the data; Pal A, Ali A, Oostenbrink J, Prabhakar A, Prabhakar A, Deacon N, Arnold A, Eltayeb A, Eltayeb A, Yap C, Young DM, Tang A, and Kakodkar P performed interpretation of the data; Pal A, Ali A, Young TR, Oostenbrink J, Prabhakar A, Prabhakar A, Deacon N, Arnold A, Eltayeb A, Yap C, Young DM, Tang A, Lakshmanan S, Lim YY, Pokarowski M, and Kakodkar P wrote the original draft; Pal A, Lim YY, Pokarowski M, and Kakodkar P performed the critical revision; All authors have read and approved the final manuscript.
Conflict-of-interest statement: Authors declare no conflict of interest for this article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Pramath Kakodkar, MD, Doctor, School of Medicine, National University of Ireland Galway, University Road, Galway H91 TK33, Galway, Ireland. p.kakodkar1@nuigalway.ie
Received: February 6, 2021
Peer-review started: February 6, 2021
First decision: March 17, 2021
Revised: March 28, 2021
Accepted: August 4, 2021
Article in press: August 4, 2021
Published online: September 28, 2021
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 systems such as MuLBSTA, Radiological Assessment of Lung Edema, and Brixia in this pandemic are reviewed as they integrate the radiographic findings into an objective scoring system to risk stratify the patients and predict the severity of disease. Furthermore, current progress in the utilization of artificial intelligence via radiomics is evaluated. Lastly, the lesson from the first wave and preparation for the second wave from the point of view of radiology are summarized.

Keywords: Coronavirus, COVID-19, Computed tomography, Ultrasound, MuLBSTA Scoring system, Radiological Assessment of Lung Edema classification, Brixia score

Core Tip: Since there is a rapid expansion and knowledge regarding the radiological findings in coronavirus disease 2019 (COVID-19), it is important to condense and collate the most important findings into a one-stop guide. We tried to undertake the same and provide digital images with markings that would be helpful for anyone interested in understanding the typical radiological features alongside the evidence-based findings of COVID-19 pneumonia. Additionally, we highlight and provide evidence-based findings regarding the predominantly utilized clinical scoring systems that integrate radiology.