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01-12-2020 | Computed Tomography | Chest

Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation

Authors: Ezio Lanza, Riccardo Muglia, Isabella Bolengo, Orazio Giuseppe Santonocito, Costanza Lisi, Giovanni Angelotti, Pierandrea Morandini, Victor Savevski, Letterio Salvatore Politi, Luca Balzarini

Published in: European Radiology | Issue 12/2020

Abstract

Objective

Lombardy (Italy) was the epicentre of the COVID-19 pandemic in March 2020. The healthcare system suffered from a shortage of ICU beds and oxygenation support devices. In our Institution, most patients received chest CT at admission, only interpreted visually. Given the proven value of quantitative CT analysis (QCT) in the setting of ARDS, we tested QCT as an outcome predictor for COVID-19.

Methods

We performed a single-centre retrospective study on COVID-19 patients hospitalised from January 25, 2020, to April 28, 2020, who received CT at admission prompted by respiratory symptoms such as dyspnea or desaturation. QCT was performed using a semi-automated method (3D Slicer). Lungs were divided by Hounsfield unit intervals. Compromised lung (%CL) volume was the sum of poorly and non-aerated volumes (− 500, 100 HU). We collected patient’s clinical data including oxygenation support throughout hospitalisation.

Results

Two hundred twenty-two patients (163 males, median age 66, IQR 54–6) were included; 75% received oxygenation support (20% intubation rate). Compromised lung volume was the most accurate outcome predictor (logistic regression, p < 0.001). %CL values in the 6–23% range increased risk of oxygenation support; values above 23% were at risk for intubation. %CL showed a negative correlation with PaO₂/FiO₂ ratio (p < 0.001) and was a risk factor for in-hospital mortality (p < 0.001).

Conclusions

QCT provides new metrics of COVID-19. The compromised lung volume is accurate in predicting the need for oxygenation support and intubation and is a significant risk factor for in-hospital death. QCT may serve as a tool for the triaging process of COVID-19.

Key Points

• Quantitative computer-aided analysis of chest CT (QCT) provides new metrics of COVID-19.

• The compromised lung volume measured in the − 500, 100 HU interval predicts oxygenation support and intubation and is a risk factor for in-hospital death.

• Compromised lung values in the 6–23% range prompt oxygenation therapy; values above 23% increase the need for intubation.

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Title: Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation
Authors: Ezio Lanza
Riccardo Muglia
Isabella Bolengo
Orazio Giuseppe Santonocito
Costanza Lisi
Giovanni Angelotti
Pierandrea Morandini
Victor Savevski
Letterio Salvatore Politi
Luca Balzarini
Publication date: 01-12-2020
Publisher: Springer Berlin Heidelberg
Keywords: Computed Tomography
Computed Tomography
COVID-19
Published in: European Radiology / Issue 12/2020
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-020-07013-2

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation

Abstract

Objective

Methods

Results

Conclusions

Key Points

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objective

Methods

Results

Conclusions

Key Points

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