Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19

Objective:    to determine the prognostic value of quantification of well ventilated lungs obtained on baseline chest CT in patients with covid-19 pneumonia。

Methods:    open source software (% s-wall and absolute volume, vol-wall) and CT were used for visual quantification (% v-wall) and quantitative analysis (% s-wall and absolute volume, vol-wall) of well ventilated lungs. Clinical parameters included demographics, comorbidity, symptoms and duration of symptoms, oxygen saturation, and laboratory values. Logistic regression analysis was used to evaluate the relationship between clinical parameters, CT indicators and patient prognosis (ICU admission / death and no ICU admission / death). The model performance is determined by calculating the area under the receiver operating characteristic curve (AUC).

Results: 236 patients (59 / 123, 25%; median age, 68 years) were included in this study. Compared with the clinical model containing only clinical parameters (AUC, 0.83), all three quantitative models showed higher diagnostic performance (AUC of 0.86 for all models).

Conclusion: in patients with confirmed covid-19 pneumonia, visualization or software quantification of CT lung abnormalities is a predictor of ICU admission or death


CT quantitative display of well ventilated lungs is helpful to evaluate the filling of alveoli during ventilation or predict the prognosis of patients with acute respiratory distress syndrome


Open source 3D slicer software (version 4.10.2, https://www.slicer.org )。 B40f kernel is used to realize automatic segmentation and analysis of lung parenchymal histogram. When the lung segmentation effect is not ideal, the user uses manual tools to correct the lung contour

Filtering of data:

Patients were divided into two groups:Patients admitted to ICU or died (ICU / death) and patients discharged without admission to ICU. The time between CT and ICU admission or death was recorded


The results of this study suggest that the proportion of well ventilated lungs assessed by chest CT obtained in the emergency department is associated with a better prognosis in patients with covid-19 pneumonia, but not with other clinical parameters


Obesity has been described as a common comorbidity in hospitalized patients with H1N1 influenza infection. Previous observations suggest that covid-19 may have a more severe course in obese patients. Therefore, CT evaluation of adipose tissue may be an objective marker of obesity and has prognostic significance.

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