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. 2021 Jun 21;25(1):214.
doi: 10.1186/s13054-021-03610-9.

Lung distribution of gas and blood volume in critically ill COVID-19 patients: a quantitative dual-energy computed tomography study

Lorenzo Ball  1   2 , Chiara Robba  3   4 , Jacob Herrmann  5 , Sarah E Gerard  6 , Yi Xin  7 , Maura Mandelli  4 , Denise Battaglini  4 , Iole Brunetti  4 , Giuseppe Minetti  8 , Sara Seitun  8 , Giulio Bovio  8 , Antonio Vena  9 , Daniele Roberto Giacobbe  9 , Matteo Bassetti  9   10 , Patricia R M Rocco  11 , Maurizio Cereda  12 , Rahim R Rizi  7 , Lucio Castellan  13 , Nicolò Patroniti  3   4 , Paolo Pelosi  3   4 ; Collaborators of the GECOVID Group
Collaborators, Affiliations

Lung distribution of gas and blood volume in critically ill COVID-19 patients: a quantitative dual-energy computed tomography study

Lorenzo Ball et al. Crit Care. .

Abstract

Background: Critically ill COVID-19 patients have pathophysiological lung features characterized by perfusion abnormalities. However, to date no study has evaluated whether the changes in the distribution of pulmonary gas and blood volume are associated with the severity of gas-exchange impairment and the type of respiratory support (non-invasive versus invasive) in patients with severe COVID-19 pneumonia.

Methods: This was a single-center, retrospective cohort study conducted in a tertiary care hospital in Northern Italy during the first pandemic wave. Pulmonary gas and blood distribution was assessed using a technique for quantitative analysis of dual-energy computed tomography. Lung aeration loss (reflected by percentage of normally aerated lung tissue) and the extent of gas:blood volume mismatch (percentage of non-aerated, perfused lung tissue-shunt; aerated, non-perfused dead space; and non-aerated/non-perfused regions) were evaluated in critically ill COVID-19 patients with different clinical severity as reflected by the need for non-invasive or invasive respiratory support.

Results: Thirty-five patients admitted to the intensive care unit between February 29th and May 30th, 2020 were included. Patients requiring invasive versus non-invasive mechanical ventilation had both a lower percentage of normally aerated lung tissue (median [interquartile range] 33% [24-49%] vs. 63% [44-68%], p < 0.001); and a larger extent of gas:blood volume mismatch (43% [30-49%] vs. 25% [14-28%], p = 0.001), due to higher shunt (23% [15-32%] vs. 5% [2-16%], p = 0.001) and non-aerated/non perfused regions (5% [3-10%] vs. 1% [0-2%], p = 0.001). The PaO2/FiO2 ratio correlated positively with normally aerated tissue (ρ = 0.730, p < 0.001) and negatively with the extent of gas-blood volume mismatch (ρ = - 0.633, p < 0.001).

Conclusions: In critically ill patients with severe COVID-19 pneumonia, the need for invasive mechanical ventilation and oxygenation impairment were associated with loss of aeration and the extent of gas:blood volume mismatch.

Keywords: ARDS; COVID-19; Dual energy computed tomography; Lung imaging.

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Conflict of interest statement

Dr. Bassetti reports personal fees and other from Angelini, personal fees and other from AstraZeneca, other from Bayer, personal fees and other from Cubist, personal fees and other from Pfizer, personal fees and other from Menarini, personal fees and other from MSD, other from Nabriva, other from Paratek, other from Roche, other from Shionogi, other from Tetraphase, other from The Medicine Company, personal fees and other from Astellas Pharma Inc., personal fees from Gilead Sciences, personal fees from Teva, personal fees from Novartis, grants from Ranbaxy, personal fees from Correvio, personal fees from Molteni, personal fees from Thermo Fisher, outside the submitted work. Dr. Herrmann is a cofounder and shareholder of OscillaVent, Inc, and consultant for ZOLL Medical Corporation, both outside the submitted work. Dr. Giacobbe reports personal fees from Stepstone Pharma GmbH, personal fees from MSD Italia, personal fees from Correvio Italia, outside the submitted work. Dr. Rocco reports personal fees from SANOFI as a DSMB member. All other authors declared no conflict of interest.

Figures

Fig. 1
Fig. 1
Patient inclusion flow. Date of first admission of a COVID-19 patient: February 29th, 2020; date of introduction of DECT scan in routine practice: March 26th, 2020; last DECT scan included in this analysis: May 30th, 2020
Fig. 2
Fig. 2
Representative DECT scans of patients receiving non-invasive (top panels) and invasive (bottom panels) respiratory support. The images on the left represent the virtual non-contrast image used for the assessment of aeration, while those on the right represent the pulmonary blood volume map superimposed onto the virtual non-contrast image. The patient in non-invasive ventilation shows areas of ground-glass with both high (yellow) and low (gray) pulmonary blood volume. The patient receiving invasive ventilation shows a more advanced disease characterized by diffuse ground-glass and consolidative lesions, with vast areas of lack of pulmonary blood volume (grey zones) especially in the dorsal dependent regions. DECT dual-energy computed tomography
Fig. 3
Fig. 3
Quantitative DECT analysis in patients receiving non-invasive versus invasive respiratory support. Lung tissue mass, divided into four aeration compartments, is reported as percent of total lung mass (a); striped bars represent non-perfused regions. The bottom panel (b) illustrates the lung mass divided according to the aeration-perfusion matching compartments. *Significant difference between patients receiving non-invasive and invasive ventilation (p < 0.05). DECT dual-energy computed tomography. Bars and error bars represent the mean and standard error of the mean, respectively
Fig. 4
Fig. 4
Pulmonary gas:blood volume matching in invasive (upper panel) and non-invasive (lower panel) groups. The curves represent the distribution of voxels according to their gas:blood volume ratio values in the four aeration compartments, where 1 represents voxels with proportionally matched aeration and perfusion
Fig. 5
Fig. 5
Correlations between PaO2/FiO2 ratio and lung aeration and gas:blood volume mismatch. Gas:blood volume mismatch is the percent of lung mass accounted for shunt, dead space and non-aerated non-perfused regions. *Significant correlation
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