Chest CT features and progression of patients with coronavirus disease 2019

Linjun Xie1, Keke Hou2, Huayan Xu1

  • 1Department of Radiology; Key Laboratory of Obstetric & Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education; West China Second University Hospital, Sichuan University;20# South Renmin Road, Chengdu, Sichuan 610041, China.

Insights

Chest CT scans reveal distinct patterns in COVID-19 patients, with severe cases showing more extensive lung lesions. CT severity and MuLBSTA scores can aid in assessing disease progression and outcomes.

Area of Science:

  • Radiology
  • Infectious Diseases
  • Pulmonology

Background:

  • Coronavirus disease 2019 (COVID-19) is a significant global health threat.
  • Understanding the radiological manifestations and disease progression is crucial for patient management.

Purpose of the Study:

  • To investigate chest CT findings in COVID-19 patients.
  • To evaluate the progression of COVID-19 based on CT imaging.
  • To compare CT features across different severity types of COVID-19.

Main Methods:

  • Retrospective analysis of chest CT scans from 49 adult COVID-19 patients.
  • Evaluation of thin-section chest CT features and disease progression.
  • Comparison of clinical and imaging findings between common, severe, and critically severe COVID-19 cases.
  • Calculation of CT severity score and MuLBSTA score for mortality risk prediction.

Main Results:

  • Severe COVID-19 cases showed significantly more GGO with consolidation and fibrosis compared to common cases.
  • Severe cases exhibited higher CT severity and MuLBSTA scores, correlating with ICU admission.
  • CT follow-up scans demonstrated progressive improvement in lung lesions over time.

Conclusions:

  • Chest CT is valuable for assessing COVID-19 radiographical features and disease dynamics.
  • CT severity score and MuLBSTA score can assist in evaluating COVID-19 severity and progression.
  • The MuLBSTA score may require updates to incorporate COVID-19-related coagulation disorders.
Abstract

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