A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography

Mariangela Pellegrini, Aleksandra Larina, Evangelos Mourtos, Robert Frithiof, Miklos Lipcsey, Michael Hultström, Monica Segelsjö, Tomas Hansen, Gaetano Perchiazzi, Mariangela Pellegrini, Aleksandra Larina, Evangelos Mourtos, Robert Frithiof, Miklos Lipcsey, Michael Hultström, Monica Segelsjö, Tomas Hansen, Gaetano Perchiazzi

Abstract

Background: Typical features differentiate COVID-19-associated lung injury from acute respiratory distress syndrome. The clinical role of chest computed tomography (CT) in describing the progression of COVID-19-associated lung injury remains to be clarified. We investigated in COVID-19 patients the regional distribution of lung injury and the influence of clinical and laboratory features on its progression.

Methods: This was a prospective study. For each CT, twenty images, evenly spaced along the cranio-caudal axis, were selected. For regional analysis, each CT image was divided into three concentric subpleural regions of interest and four quadrants. Hyper-, normally, hypo- and non-inflated lung compartments were defined. Nonparametric tests were used for hypothesis testing (α = 0.05). Spearman correlation test was used to detect correlations between lung compartments and clinical features.

Results: Twenty-three out of 111 recruited patients were eligible for further analysis. Five hundred-sixty CT images were analyzed. Lung injury, composed by hypo- and non-inflated areas, was significantly more represented in subpleural than in core lung regions. A secondary, centripetal spread of lung injury was associated with exposure to mechanical ventilation (p < 0.04), longer spontaneous breathing (more than 14 days, p < 0.05) and non-protective tidal volume (p < 0.04). Positive fluid balance (p < 0.01), high plasma D-dimers (p < 0.01) and ferritin (p < 0.04) were associated with increased lung injury.

Conclusions: In a cohort of COVID-19 patients with severe respiratory failure, a predominant subpleural distribution of lung injury is observed. Prolonged spontaneous breathing and high tidal volumes, both causes of patient self-induced lung injury, are associated to an extensive involvement of more central regions. Positive fluid balance, inflammation and thrombosis are associated with lung injury. Trial registration Study registered a priori the 20th of March, 2020. Clinical Trials ID NCT04316884.

Keywords: ARDS; Acute respiratory distress syndrome; COVID-19; Computed tomography; Mechanical ventilation; SARS-CoV2.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
CT image analysis. Left panel. Coronal representation of lungs. Twenty CT images were selected along the cranial-caudal axis. Central panel. Upper part: representative image of an original CT image from a patients included in the study. Lower part: region of interest (ROI) applied to CT image. Right panel: representative image of three ROIs (areas concentric to the visceral pleura: between 0 and 1 cm in blue; 1 and 2 cm in green; and 2 and 3 cm in orange) and quadrants: internal dependent, external dependent, internal non-dependent + external non-dependent). The identification of quadrants was based on the detection of the centroid (or geometrical center) univocally characterizing each lung for each analyzed CT image
Fig. 2
Fig. 2
Boxplot showing regional distribution of lung compartments in the whole lung parenchyma. Each subgroup of boxplot shows how lung compartments are divided among different subpleural regions of interest (blue for 0–1 cm subpleural area, green for 1–2 cm subpleural area, orange for 2–3 cm subpleural area, black for the whole analyzed area). The regional distribution of lung compartments is expressed in % of total lung volume for each CT slice (y-axis). Friedman's test was used to detect statistical differences. Pairwise comparisons (adjustment for multiple comparisons was applied according to the Bonferroni method) were used if the analysis of variance detected a significant difference inside the tested group of ROIs. * to indicate statistical differences
Fig. 3
Fig. 3
Regional distribution of non-inflated lung compartment in patients’ subgroups defined based on dichotomous variables. A exposure to mechanical ventilation before the chest CT (yes/not); B exposure to a mean tidal volume higher/lower than 6 mL/kg PBW; C duration of spontaneous breathing for more/less than 14 days before the chest CT; D plasma ferritin lower/higher than 1000 ug/L. * to indicate statistical difference. The regional distribution of lung compartments is expressed in % of total parenchyma (y-axis) for all the reported graphs. For p-values, see Supplementary materials. Vt: tidal volume, PBW: predicted body weight, SB: spontaneous breathing

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