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Thoracic Computed Tomography to Assess ARDS and COVID-19 Lungs

This review was designed to discuss the role of thoracic-computed tomography (CT) in the evaluation and treatment of patients with ARDS and COVID-19 lung disease. Non-aerated lungs characterize the ARDS lungs, compared to normal lungs in the lowermost lung regions, compressive atelectasis. Heterogen...

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Autor principal: Barbas, Carmen Silvia Valente
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108486/
https://www.ncbi.nlm.nih.gov/pubmed/35586712
http://dx.doi.org/10.3389/fphys.2022.829534
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author Barbas, Carmen Silvia Valente
author_facet Barbas, Carmen Silvia Valente
author_sort Barbas, Carmen Silvia Valente
collection PubMed
description This review was designed to discuss the role of thoracic-computed tomography (CT) in the evaluation and treatment of patients with ARDS and COVID-19 lung disease. Non-aerated lungs characterize the ARDS lungs, compared to normal lungs in the lowermost lung regions, compressive atelectasis. Heterogenous ARDS lungs have a tomographic vertical gradient characterized by progressively more aerated lung tissues from the gravity-dependent to gravity-independent lungs levels. The application of positive pressure ventilation to these heterogeneous ARDS lungs provides some areas of high shear stress, others of tidal hyperdistension or tidal recruitment that increases the chances of appearance and perpetuation of ventilator-induced lung injury. Other than helping to the correct diagnosis of ARDS, thoracic-computed tomography can help to the adjustments of PEEP, ideal tidal volume, and a better choice of patient position during invasive mechanical ventilation. Thoracic tomography can also help detect possible intra-thoracic complications and in the follow-up of the ARDS patients’ evolution during their hospital stay. In COVID-19 patients, thoracic-computed tomography was the most sensitive imaging technique for diagnosing pulmonary involvement. The most common finding is diffuse pulmonary infiltrates, ranging from ground-glass opacities to parenchymal consolidations, especially in the lower portions of the lungs’ periphery. Tomographic lung volume loss was associated with an increased risk for oxygenation support and patient intubation and the use of invasive mechanical ventilation. Pulmonary dual-energy angio-tomography in COVID-19 patients showed a significant number of pulmonary ischemic areas even in the absence of visible pulmonary arterial thrombosis, which may reflect micro-thrombosis associated with COVID-19 pneumonia. A greater thoracic tomography severity score in ARDS was independently related to poor outcomes.
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spelling pubmed-91084862022-05-17 Thoracic Computed Tomography to Assess ARDS and COVID-19 Lungs Barbas, Carmen Silvia Valente Front Physiol Physiology This review was designed to discuss the role of thoracic-computed tomography (CT) in the evaluation and treatment of patients with ARDS and COVID-19 lung disease. Non-aerated lungs characterize the ARDS lungs, compared to normal lungs in the lowermost lung regions, compressive atelectasis. Heterogenous ARDS lungs have a tomographic vertical gradient characterized by progressively more aerated lung tissues from the gravity-dependent to gravity-independent lungs levels. The application of positive pressure ventilation to these heterogeneous ARDS lungs provides some areas of high shear stress, others of tidal hyperdistension or tidal recruitment that increases the chances of appearance and perpetuation of ventilator-induced lung injury. Other than helping to the correct diagnosis of ARDS, thoracic-computed tomography can help to the adjustments of PEEP, ideal tidal volume, and a better choice of patient position during invasive mechanical ventilation. Thoracic tomography can also help detect possible intra-thoracic complications and in the follow-up of the ARDS patients’ evolution during their hospital stay. In COVID-19 patients, thoracic-computed tomography was the most sensitive imaging technique for diagnosing pulmonary involvement. The most common finding is diffuse pulmonary infiltrates, ranging from ground-glass opacities to parenchymal consolidations, especially in the lower portions of the lungs’ periphery. Tomographic lung volume loss was associated with an increased risk for oxygenation support and patient intubation and the use of invasive mechanical ventilation. Pulmonary dual-energy angio-tomography in COVID-19 patients showed a significant number of pulmonary ischemic areas even in the absence of visible pulmonary arterial thrombosis, which may reflect micro-thrombosis associated with COVID-19 pneumonia. A greater thoracic tomography severity score in ARDS was independently related to poor outcomes. Frontiers Media S.A. 2022-05-02 /pmc/articles/PMC9108486/ /pubmed/35586712 http://dx.doi.org/10.3389/fphys.2022.829534 Text en Copyright © 2022 Barbas. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Barbas, Carmen Silvia Valente
Thoracic Computed Tomography to Assess ARDS and COVID-19 Lungs
title Thoracic Computed Tomography to Assess ARDS and COVID-19 Lungs
title_full Thoracic Computed Tomography to Assess ARDS and COVID-19 Lungs
title_fullStr Thoracic Computed Tomography to Assess ARDS and COVID-19 Lungs
title_full_unstemmed Thoracic Computed Tomography to Assess ARDS and COVID-19 Lungs
title_short Thoracic Computed Tomography to Assess ARDS and COVID-19 Lungs
title_sort thoracic computed tomography to assess ards and covid-19 lungs
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108486/
https://www.ncbi.nlm.nih.gov/pubmed/35586712
http://dx.doi.org/10.3389/fphys.2022.829534
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