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CC BY-NC-ND 4.0 · Indian J Radiol Imaging 2021; 31(S 01): S110-S118
DOI: 10.4103/ijri.IJRI_774_20
Original Article

Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19

Bavaharan Rajalingam
DNB, Managing Director, Magnum Imaging & Diagnostics, Trichy, Tamil Nadu
,
Ethirajan Narayanan
Retired Professor, Social & Preventive Medicine, Chidambaram, Trichy, Tamil Nadu
,
Praveen Nirmalan
MPH, Reasearch Head, Amma Education Research Foundation, Kochi
,
Kamalanthan Muthukrishnan
DNB, Consultant, Magnum Imaging & Diagnostics, Trichy, Tamil Nadu
,
Vivek Sundaram
Sundaram Hospital, Director, Saravana Medical Centre, Singarathope, Trichy, Tamil Nadu
,
Saravanan Kumaravelu
Director, Saravana Medical Centre, Trichy, Tamil Nadu
,
Mukundhan Gopalan
ABC Hopsital, Director, GVN Hopsital, Singarathope, Trichy, Tamil Nadu
,
Senthil Jeyapal
Director, GVN Hopsital, Singarathope, Trichy, Tamil Nadu
,
Baskaran Rajalingam
Consultant Physician, GVN Hopsital, Singarathope, Trichy, Tamil Nadu
,
Vijay Khanna
Consultant Critcal Care, Retna global Hopsital, Trichy, Tamil Nadu
,
Praveen Dhoss
Director, Retna Global Hopsital, Trichy, Tamil Nadu
,
Gopinath Gopinath
Emergency Medical Officer, Sundaram Hospital, Trichy, Tamil Nadu, India
› Author Affiliations
Financial support and sponsorship Nil.
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Abstract

Aim: To describe the distribution of lung patterns determined by High Resolution Computed Tomography (HRCT) in COVID patients with mild and moderate lung involvement and outcomes after early identification and management with steroids and anticoagulants. Material and Methods: A cross sectional study of COVID-19 patients with mild and moderate lung involvement presenting at 5 healthcare centres in Trichy district of South TamilNadu in India. Patients underwent HRCT to assess patterns and severity of lung involvement, Inflammatory markers (LDH/Ferritin) and D-Dimer assay and clinical correlation with signs and symptoms. Patients were assessed for oxygen, steroid and anticoagulant therapy, clinical recovery or progression on follow up and details on mortality were collected. The RSNA, Fleischer Society guidelines and CORADS score was used for radiological reporting. New potential classification of patterns of percentage of lung parenchyma involvement in Covid patients is being suggested. Results: The study included 7,340 patients with suspected COVID and 3,963 (53.9%) patients had lung involvement based on HRCT. RT PCR was positive in 74.1% of the CT Positive cases. Crazy Pavement pattern was predominant (n = 2022, 51.0%) and Ground Glass Opacity (GGO) was found in 1,941 (49.0%) patients in the study. Severe lung involvement was more common in the Crazy Pavement pattern. Patients with GGO in moderate lung involvement were significantly more likely to recover faster compared to Crazy Pavement pattern (P value <0.001). Conclusion: HRCT chest and assessment of lung patterns can help triage patients to home quarantine and hospital admission. Early initiation of steroids and anticoagulants based on lung patterns can prevent progression to more severe stages and aid early recovery. HRCT can play a major role to triage and guide management especially as RT PCR testing and results are delayed for the benefit of patients and in a social cause to decrease the spread of the virus

Keywords

COVID 19 - crazy pavement pattern - ground glass opacity - HRCT


Publication History

Received: 18 September 2020

Accepted: 21 December 2020

Article published online:
13 July 2021

© 2021. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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  • References

  • 1 Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W. et al (2020) Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: A report of 1014 cases. Radiology 200642. 10.1148/radiol. 2020200642.
  • 2 Hansell DM, Bankier AA, MacMahon H, McLoud TC, Müller NL, Remy J. 2008; Fleischner society: Glossary of terms for thoracic imaging. Radiology 246: 697-722
    CrossrefPubMedSearch in Google Scholar
  • 3 Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. 2020 Coronavirus disease 2019 (COVID-19): A systematic review of imaging findings in 919 patients. AJR Am J Roentgenol: 1-7. 10.2214/AJR.20.23034.
    PubMed
  • 4 Ye Z, Zhang Y, Wang Y, Huang Z, Song B. 2020 Chest CT manifestations of new coronavirus disease 2019 (COVID-19): A pictorial review. Eur Radiol. 10.1007/s00330-020-06801-0.
    PubMed
  • 5 Prokop M, van Everdingen W, van Rees Vellinga T, Quarles van Ufford J, Stöger L, Beenen L, Geurts B, Gietema H, Krdzalic J, Schaefer-Prokop C, van Ginneken B, Brink M. CO-RADS – A categorical CT-assessment scheme for patients with suspected COVID-19: Definition and evaluation. Radiology 2020. doi: 10.1148/radiol.2020201473.
  • 6 Cascella M, Rajnik M, Cuomo A, Dulebohn SC, Napoli RD. et al. Features, Evaluation, and Treatment of Coronavirus (COVID-19) [Updated 2020 Aug 10]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2020
    Search in Google Scholar
  • 7 Clark A, Jit M, Warren-Gash C, Guthrie B, Wang HHX, Mercer SW, Sanderson C, McKee M, Troeger C, Ong KL, Checchi F, Perel P, Joseph S, Gibbs HP, Banerjee A, Eggo RM. Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: A modelling study. Lancet Glob Health 2020; Aug 8 (08) e1003-e1017
    CrossrefPubMedSearch in Google Scholar
  • 8 Ciceri F, Beretta L, Scandroglio AM, Colombo S, Landoni G, Ruggeri A, Peccatori J, D’Angelo A, De Cobelli F, Rovere-Querini P, Tresoldi M, Dagna L, Zangrillo A. Microvascular COVID-19 lung vessels obstructive thromboinflammatory syndrome (MicroCLOTS): An atypical acute respiratory distress syndrome working hypothesis. Crit Care Resusc 2020; Apr 15 22 (02) 95-97
    PubMedSearch in Google Scholar
  • 9 Flieder DB. Chapter-Normal Anatomy, Tissue Artifacts, and Incidental Structures. In: Zander DS, Farver CF. Pulmonary Pathology. 2017. ISBN: 9780323393089
    Search in Google Scholar
  • 10 Itoh H, Murata K, Kenisha J, Nishimura K, Kitaichi M, Izumi T. Diffuse lung disease: Pathologic basis for the high-resolution computed tomography findings. 1993; Journal of thoracic imaging 8 (03) 176-88 PubMed
    CrossrefPubMedSearch in Google Scholar
  • 11 Heitzman ER, Markarian B, Berger I, Dailey E. The secondary pulmonary lobule: A practical concept for interpretation of chest radiographs. I. Roentgen anatomy of the normal secondary pulmonary lobule. 1969; Radiology 93 (03) 507-12
    CrossrefPubMedSearch in Google Scholar
  • 12 Webb WR. Thin-section CT of the secondary pulmonary lobule: Anatomy and the image--the 2004 Fleischner lecture. 2006; Radiology 239 (02) 322-38
    CrossrefPubMedSearch in Google Scholar
  • 13 Tian S, Hu W, Niu L, Liu H, Xu H, Xiao SY. Pulmonary Pathology of Early-Phase 2019 Novel Coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancer. J Thorac Oncol 2020; May 15 (05) 700-704
    CrossrefPubMedSearch in Google Scholar
  • 14 Zhang H, Zhou P, Wei Y, Yue H, Wang Y, Hu M, Zhang S, Cao T, Yang C, Li M, Guo G, Chen X, Chen Y, Lei M, Liu H, Zhao J, Peng P, Wang CY, Du R. Histopathologic Changes and SARS-CoV-2 Immunostaining in the Lung of a Patient With COVID-19. Ann. Intern. Med 2020; May 05 172 (09) 629-632
    CrossrefPubMedSearch in Google Scholar
  • 15 Menter T, Haslbauer JD, Nienhold R, Savic S, Hopfer H, Deigendesch N, Frank S, Turek D, Willi N, Pargger H, Bassetti S, Leuppi JD, Cathomas G, Tolnay M, Mertz KD, Tzankov A. Postmortem examination of COVID-19 patients reveals diffuse alveolar damage with severe capillary congestion and variegated findings in lungs and other organs suggesting vascular dysfunction. Histopathology. 2020 May 04.
  • 16 Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M. et al. Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA. Radiology: Cardiothoracic Imaging 2020; 2: 2
    CrossrefPubMedSearch in Google Scholar
  • 17 Francone M, Iafrate F, Masci GM, Coco S, Cilia F, Manganaro L, Panebianco V, Andreoli C, Colaiacomo MC, Zingaropoli MA, Ciardi MR, Mastroianni CM, Pugliese F, Alessandri F, Turriziani O, Ricci P, Catalano C. Chest CT score in COVID-19 patients: Correlation with disease severity and short-term prognosis. Eur Radiol. 2020; 4: 1-10 Jul Epub ahead of print. PMID: 32623505; PMCID: PMC7334627
    CrossrefPubMedSearch in Google Scholar
  • 18 Ledford H. Coronavirus breakthrough: Dexamethasone is first drug shown to save lives. Nature 2020; Jun(7813) 582: 469
    CrossrefPubMedSearch in Google Scholar
  • 19 Kollias A, Kyriakoulis KG, Dimakakos E, Poulakou G, Stergiou GS, Syrigos K. Thromboembolic risk and anticoagulant therapy in COVID-19 patients: Emerging evidence and call for action. Br. J. Haematol 2020; Jun 189 (05) 846-847
    CrossrefPubMedSearch in Google Scholar