Clinical evaluation of SARS-CoV-2 Lung HRCT and RT-PCR Techniques: Towards risk factor based diagnosis of infectious diseases

Fariba Asadi, Razieh Shahnazari, Nikhil Bhalla, Amir Farokh Payam

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
29 Downloads (Pure)

Abstract

This study uses image analysis techniques for comparative analysis of the lung HRCT features and RT-PCR of 325 suspected patients to COVID-19 pneumonia. Our findings propose more caution in the interpretation of RT-PCR data, promoting, instead, also the quantification of age and sex-based risk factors using HRCT images. Statistical analysis of our methodology reveals a direct relation between intensity, skewness and kurtosis of the radiological features and the gender of patients. Moreover, we investigate the effect of the age of patients on the appearance of COVID-19 pneumonia in the HRCT images. We have also applied our methodology to investigate the effect of time on the severity of COVID-19 pneumonia within the lungs. Subsequently, we find a strong relationship between image analysis and the informed medical diagnosis asserted by the radiologists. Additionally, our results also indicate increase in the severity of lung infection in the first and second week after the onset of the SARS-CoV-2 symptoms. Thereafter, a gradual decrease in the lung damage is observed during the third week. The proposed image analysis methodology can be used as a simple complementary tool for infectious disease diagnostics as demonstrated in this study with an example of SARS-CoV-2 to provide better understanding of the disease for drug and vaccine development. [Abstract copyright: © 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.]
Original languageEnglish
Pages (from-to)2699-2707
Number of pages9
JournalComputational and Structural Biotechnology Journal
Volume19
Early online date30 Apr 2021
DOIs
Publication statusPublished - 2021

Bibliographical note

Publisher Copyright:
© 2021

© 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

Keywords

  • Age
  • COVID-19
  • Coronaviruses
  • Gender
  • HRCT
  • RT-PCR

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