Role Of Radiology Imaging In Covid-19 Management And Diagnosis Recommendations
Main Article Content
Abstract
A disease in 2019 known as COVID-19 emerged from china and spread to the whole world1. Patient diagnosis : COVID-19 infection was confirmed by RTPCR test for throat swabs, nasopharyngeal2 . The scoring : lung involvement scoring was done by giving a score from 0-4 to the lung on the basis of the involvements the score was considered to be 0,1,2,3 and 4 and the score was distributed as 0= least or no involvements , 1= more than 25 involvements , 2= in between 25-50, 3= in between 50-75, 4= more than 75% involvement3. RALE classification : In march 2020 the system was introduced to radiology , which was used to identify the severity of the findings in the covid-19 patients ,. Scoring on the CXR : The method was introduced to assess the involvements and pathologies in covid-19 patients . CRX : it was considered to have least sensitivity in early stage of covid-19 to detect the abnormalities , but was found active in progressive stage covid-19 patients to find the abnormalities . Computed tomograpy scans played a vital role for detecting lung diseases in corona virus pandemic as compared to cest x rays5. Differential Disease finding :
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Chamorro EM, Tascón AD, Sanz LI, Vélez SO, Nacenta SB. Radiologic diagnosis of patients with COVID-19. Radiología (English Edition). 2021 Jan 1;63(1):56-73. https://scholar.google.com/scholar?cites=11303051106331023197&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
2.Moroni C, Cozzi D, Albanesi M, Cavigli E, Bindi A, Luvarà S, Busoni S, Mazzoni LN, Grifoni S, Nazerian P, Miele V. Chest X-ray in the emergency department during COVID-19 pandemic descending phase in Italy: Correlation with patients’ outcome. La radiologia medica. 2021 May;126(5):6618 https://doi.org/10.1007/s11547-020-01327-3 https://scholar.google.com/scholar?cites=8119564795094566940&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
3.Kaleemi R, Hilal K, Arshad A, Martins RS, Nankani A, Tu H, Basharat S, Ansar Z. The 0patients with COVID-19 presenting to the emergency department of a tertiary care hospital in Pakistan. PLoS One. 2021 Jan 5;16(1):e0244886. https://doi.org/10.1371/journal.pone.0244886 https://scholar.google.com/scholar?cites=2485372348720312908&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
5.Cleverley J, Piper J, Jones MM. The role of chest radiography in confirming covid-19 pneumonia. bmj. 2020 Jul 16;370. http://dx.doi.org/10.1136/bmj.m2426https://scholar.google.com/scholar?cites=14475537418461932549&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
6.Yang W, Sirajuddin A, Zhang X, Liu G, Teng Z, Zhao S, Lu M. The role of imaging in 2019 novel coronavirus pneumonia (COVID-19). European radiology. 2020 Apr 15:1-9. https://doi.org/10.1007/s00330-020-06827-4 https://scholar.google.com/scholar?cites=6598210955425181470&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
7.Palwa AR, Zafar SI, Nisar U, Halim A, Riaz S, Nayyar B. SPECTRUM OF CHEST X-RAY FINDINGS IN COVID-19 POSITIVE PATIENTS UTILIZING MODIFIED RALE SCORE FOR SEVERITY ASSESSMENT. PAFMJ. 2020 Sep 3;70(2):S494-500. https://scholar.google.com/scholar?cites=10552551605524533572&as_sdt=2005&sciodt=0,5&hl=en
8.Rousan LA, Elobeid E, Karrar M, Khader Y. Chest x-ray findings and temporal lung changes in patients with COVID-19 pneumonia. BMC Pulmonary Medicine. 2020 Dec;20(1):1-9. https://doi.org/10.1186/s12890-020-01286-5 https://scholar.google.com/scholar?cites=3371329690622780366&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
9.Cozzi D, Albanesi M, Cavigli E, Moroni C, Bindi A, Luvarà S, Lucarini S, Busoni S, Mazzoni LN, Miele V. Chest X-ray in new Coronavirus Disease 2019 (COVID-19) infection: findings and correlation with clinical outcome. La radiologia medica. 2020 Aug;125:730-7. https://doi.org/10.1007/s11547-020-01232-9 https://scholar.google.com/scholar?cites=14804095624286829568&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
10.Smith DL, Grenier JP, Batte C, Spieler B. A Characteristic Chest Radiographic Pattern in the Setting of the COVID-19 Pandemic. Radiology: Cardiothoracic Imaging. 2020 Sep 3;2(5):e200280. https://doi.org/10.1148/ryct.202020028 https://scholar.google.com/scholar?cites=8433330497141687845&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-
11.Li MD, Arun NT, Gidwani M, Chang K, Deng F, Little BP, Mendoza DP, Lang M, Lee SI, O’Shea A, Parakh A. Automated assessment and tracking of COVID-19 pulmonary disease severity on chest radiographs using convolutional siamese neural networks. Radiology: Artificial Intelligence. 2020 Jul 22;2(4):e200079. https://doi.org/10.1148/ryai.2020200079 https://scholar.google.com/scholar?cites=5055667000560704421&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
12.Kwon YJ, Toussie D, Finkelstein M, Cedillo MA, Maron SZ, Manna S, Voutsinas N, Eber C, Jacobi A, Bernheim A, Gupta YS. Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency Department. Radiology: Artificial Intelligence. 2020 Dec 16;3(2):e200098. https://doi.org/10.1148/ryai.2020200098 https://scholar.google.com/scholar?cites=3566451389687028852&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
13.Ng MY, Lee EY, Yang J, Yang F, Li X, Wang H, Lui MM, Lo CS, Leung B, Khong PL, Hui CK. Imaging profile of the COVID-19 infection: radiologic findings and literature review. Radiology: Cardiothoracic Imaging. 2020 Feb 13;2(1):e200034. https://doi.org/10.1148/ryct.2020200034 https://scholar.google.com/scholar?cites=4249711248896066062&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
14.Wong HY, Lam HY, Fong AH, Leung ST, Chin TW, Lo CS, Lui MM, Lee JC, Chiu KW, Chung TW, Lee EY. Frequency and distribution of chest radiographic findings in patients positive for COVID-19. Radiology. 2020 Aug;296(2):E72-8. https://doi.org/10.1148/radiol.2020201160 https://scholar.google.com/scholar?cites=641843427615545027&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
15.Toussie D, Voutsinas N, Finkelstein M, Cedillo MA, Manna S, Maron SZ, Jacobi A, Chung M, Bernheim A, Eber C, Concepcion J. Clinical and chest radiography features determine patient outcomes in young and middle-aged adults with COVID-19. Radiology. 2020 Oct;297(1):E197-206. https://doi.org/10.1148/radiol.2020201754 https://scholar.google.com/scholar?cites=7606797573324369691&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
20.Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus disease 2019 (COVID-19): a systematic review of imaging findings in 919 patients. American Journal of Roentgenology. 2020 Jul;215(1):87-93. doi.org/10.2214/AJR.20.23034 https://scholar.google.com/scholar?cites=678459639070219410&as_sdt=2005&sciodt=0,5&hl=en&scioq=spectrum+of+chest+x+ray+findings+in+COVID-19
21.Ebrahimian S, Homayounieh F, Rockenbach MA, Putha P, Raj T, Dayan I, Bizzo BC, Buch V, Wu D, Kim K, Li Q. Artificial intelligence matches subjective severity assessment of pneumonia for prediction of patient outcome and need for mechanical ventilation: a cohort study. Scientific Reports. 2021 Jan 13;11(1):1-0. https://doi.org/10.1038/s41598-020-79470-0 https://www.nature.com/articles/s41598-020-7947