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. 2021 May;31(5):2726-2736.
doi: 10.1007/s00330-020-07271-0. Epub 2020 Oct 30.

Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumonia

Affiliations

Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumonia

Davide Ippolito et al. Eur Radiol. 2021 May.

Abstract

Objectives: To evaluate a semi-automated segmentation and ventilated lung quantification on chest computed tomography (CT) to assess lung involvement in patients affected by SARS-CoV-2. Results were compared with clinical and functional parameters and outcomes.

Methods: All images underwent quantitative analyses with a dedicated workstation using a semi-automatic lung segmentation software to compute ventilated lung volume (VLV), Ground-glass opacity (GGO) volume (GGO-V), and consolidation volume (CONS-V) as absolute volume and as a percentage of total lung volume (TLV). The ratio between CONS-V, GGO-V, and VLV (CONS-V/VLV and GGO-V/VLV, respectively), TLV (CONS-V/TLV, GGO-V/TLV, and GGO-V + CONS-V/TLV respectively), and the ratio between VLV and TLV (VLV/TLV) were calculated.

Results: A total of 108 patients were enrolled. GGO-V/TLV significantly correlated with WBC (r = 0.369), neutrophils (r = 0.446), platelets (r = 0.182), CRP (r = 0.190), PaCO2 (r = 0.176), HCO3- (r = 0.284), and PaO2/FiO2 (P/F) values (r = - 0.344). CONS-V/TLV significantly correlated with WBC (r = 0.294), neutrophils (r = 0.300), lymphocytes (r = -0.225), CRP (r = 0.306), PaCO2 (r = 0.227), pH (r = 0.162), HCO3- (r = 0.394), and P/F (r = - 0.419) values. Statistically significant differences between CONS-V, GGO-V, GGO-V/TLV, CONS-V/TLV, GGO-V/VLV, CONS-V/VLV, GGO-V + CONS-V/TLV, VLV/TLV, CT score, and invasive ventilation by ET were found (all p < 0.05).

Conclusion: The use of quantitative semi-automated algorithm for lung CT elaboration effectively correlates the severity of SARS-CoV-2-related pneumonia with laboratory parameters and the need for invasive ventilation.

Key points: • Pathological lung volumes, expressed both as GGO-V and as CONS-V, can be considered a useful tool in SARS-CoV-2-related pneumonia. • All lung volumes, expressed themselves and as ratio with TLV and VLV, correlate with laboratory data, in particular C-reactive protein and white blood cell count. • All lung volumes correlate with patient's outcome, in particular concerning invasive ventilation.

Keywords: Artificial intelligence; Computed tomography, X-ray; Infection, coronavirus; Lung volume measurements; Pneumonia.

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Conflict of interest statement

Two of the authors (M.P. and S.T.) are affiliated with PHILIPS HEALTHCARE, as a specialist product, and they helped and supervised us during the use of COPD Software, without any financial support. The other authors of manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Figures

Fig. 1
Fig. 1
Automatic lobe segmentation process, derived from native unenhanced CT images in axial, coronal, and sagittal planes (a right, middle, and left panel, respectively), and the sequential segmentation of airways, lungs, and lobes (b right, middle, and left panel, respectively) in a 65-year-old man with SARS-CoV-2-related pneumonia
Fig. 2
Fig. 2
Flow chart of the study
Fig. 3
Fig. 3
A 61-year-old man with SARS-CoV-2-related pneumonia. CT images in axial (a) and coronal (b) planes, with window width and level for the evaluation of the lung parenchyma. The images show the presence of bilateral ground-glass opacities and partial crazy-paving pattern. Final CT score: 12. Post-processed CT images in axial (d) and coronal (e) sections showing low attenuation areas based on thresholds of − 700 HU that correspond to ventilated lung volume (VLV). CT density histogram based on the attenuation lung analysis showing both long volumes that correspond to TLV (purple line), left (blue line), and right (green line) lung volumes (c). Post-processing volumes of different lung segments calculated by the software (f)
Fig. 4
Fig. 4
A 63-year-old man with SARS-CoV-2-related pneumonia. CT images in axial (a) and coronal (b) planes, showing the presence of bilateral and peripheral ground-glass opacities associated with septa thickening and crazy-paving pattern, bronchiectasis, and band thickening. Final CT score: 18. Post-processed CT images in axial (c), coronal (d) sections, and 3D reconstruction displaying the ventilated lung volume, characterized by attenuation value lower than − 700 HU (f). The density histogram (e) summarizes the distribution of lung parenchymal density of total lung volume (purple line), left lung volume (green line), and right lung volume (blue line)
Fig. 5
Fig. 5
A 67-year-old man with SARS-CoV-2 related pneumonia. CT images in axial (a) and coronal (b) planes, showing bilateral multiple lobular ground-glass opacities associated with consolidations especially in the lower lobes. Final CT score: 24. Post-processed CT images in axial (c), coronal (d) sections and 3D reconstruction showing the ventilated lung volume (red colored), with an attenuation value lower than − 700 HU, and consolidation volumes (green colored) (e). The remaining volume is referred to as ground-glass opacities volume with a density between − 700 HU and − 350 HU

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