Staging and typing of chest CT images: A quantitative analysis based on an ambispective observational cohort study of 125 patients with COVID-19 in Xiangyang, China

  1. Guoxin Huang
  2. Yong Wang
  3. Xiaxia Wu
  4. Gaojing Qu
  5. Junwen Chen
  6. Hui Yu
  7. Meiling Zhang
  8. Lisha Wang
  9. Jinwei Ai
  10. Haoming Zhu
  11. Lei Chen
  12. Bin Pei

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Abstract

Background

The stage of CT images was rarely studied and the relationship between the severity of Coronavirus Disease 2019 (COVID-19) and CT images has not been studied based on systematic quantitative analysis currently.

Purpose

To investigate the staging duration and classification of CT images of patients with COVID-19 based on quantitative analysis.

Materials and Methods

This is an ambispective observational cohort study based on 125 patients with COVID-19 from Jan 23 to Feb 28, 2020. The stage of CT and pulmonary lesion size were quantitatively analyzed. The categorical regression analysis based on optimal scale (CATREG) was performed to evaluate the association of CT score, age, and gender with the clinical type.

Results

The CT images of 125 patients with COVID-19 (50.13 ± 16.91 years, 66 women) were analyzed in this study. Except for pre-early stage, the duration of early, progression-consolidation, and dissipation stage of CT images was 3.40 ± 2.31, 10.07 ± 4.91, and 20.60 ± 7.64 days, respectively. The median CT score was 5.00 (2.00-8.50) during the first 30 days, which reached a peak on the 11 th day. Significant differences were found between the median CT scores of different clinical types (P<0.05). Besides, the age was correlated with the clinical type (P<0.001), the CT scores of 0.00-11.50, 11.50-16.00, and 16.00-20.00 were separately correlated with the moderate, severe, and critical type with the output accuracy 69.60%.

Conclusion

The four-stage staging method based on quantitative analysis is consistent with the change rules of staging features and COVID-19. Quantitative study by scoring pulmonary lesion sizes accurately revealed the evolvement of pulmonary lesions and differences between different clinical types.

Summary

Quantitative study of the stage duration and classification of chest CT images can objectively reveal the relationship between Coronavirus Disease 2019 (COVID-19) and chest CT images.

Key Results

1. A four-stage staging method was proposed. Except for pre-early stage, the duration of early, progression-consolidation, and dissipation stage of CT images was 3.40 ± 2.31, 10.07 ± 4.91, and 20.60 ± 7.64 days, respectively.

2. The severer the disease, the higher the median CT scores and their peak value.

3. The CT scores of 0.00-11.50, 11.50-16.00, and 16.00-20.00 were separately correlated with the moderate, severe, and critical type.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.25.20219253: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the ethics review board at Xiangyang No.1 People’s Hospital (No. 2020GCP012).
    Consent: Informed consent from patients has been exempted, which neither involves the personal privacy of patients nor incurs greater than the minimal risk.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.10.25.20219253v1 on medRxiv