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

Bavaharan Rajalingam; Ethirajan Narayanan; Praveen Nirmalan; Kamalanthan Muthukrishnan; Vivek Sundaram; Saravanan Kumaravelu; Mukundhan Gopalan; Senthil Jeyapal; Baskaran Rajalingam; Vijay Khanna; Praveen Dhoss; Gopinath Gopinath

doi:10.4103/ijri.IJRI_774_20

Indian Journal of Radiology and Imaging, Table of Contents

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

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

Full Text

References

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