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Examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation
BACKGROUND: Mechanical ventilation is often employed to facilitate breathing in patients suffering from respiratory illnesses and disabilities. Despite the benefits, there are risks associated with ventilator-induced lung injuries and death, driving investigations for alternative ventilation techniq...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999998/ https://www.ncbi.nlm.nih.gov/pubmed/35410291 http://dx.doi.org/10.1186/s12931-022-01999-7 |
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author | Mariano, C. A. Sattari, S. Quiros, K. A. M. Nelson, T. M. Eskandari, M. |
author_facet | Mariano, C. A. Sattari, S. Quiros, K. A. M. Nelson, T. M. Eskandari, M. |
author_sort | Mariano, C. A. |
collection | PubMed |
description | BACKGROUND: Mechanical ventilation is often employed to facilitate breathing in patients suffering from respiratory illnesses and disabilities. Despite the benefits, there are risks associated with ventilator-induced lung injuries and death, driving investigations for alternative ventilation techniques to improve mechanical ventilation, such as multi-oscillatory and high-frequency ventilation; however, few studies have evaluated fundamental lung mechanical local deformations under variable loading. METHODS: Porcine whole lung samples were analyzed using a novel application of digital image correlation interfaced with an electromechanical ventilation system to associate the local behavior to the global volume and pressure loading in response to various inflation volumes and breathing rates. Strains, anisotropy, tissue compliance, and the evolutionary response of the inflating lung were analyzed. RESULTS: Experiments demonstrated a direct and near one-to-one linear relationship between applied lung volumes and resulting local mean strain, and a nonlinear relationship between lung pressures and strains. As the applied air delivery volume was doubled, the tissue surface mean strains approximately increased from 20 to 40%, and average maximum strains measured 70–110%. The tissue strain anisotropic ratio ranged from 0.81 to 0.86 and decreased with greater inflation volumes. Local tissue compliance during the inflation cycle, associating evolutionary strains in response to inflation pressures, was also quantified. CONCLUSION: Ventilation frequencies were not found to influence the local stretch response. Strain measures significantly increased and the anisotropic ratio decreased between the smallest and greatest tidal volumes. Tissue compliance did not exhibit a unifying trend. The insights provided by the real-time continuous measures, and the kinetics to kinematics pulmonary linkage established by this study offers valuable characterizations for computational models and establishes a framework for future studies to compare healthy and diseased lung mechanics to further consider alternatives for effective ventilation strategies. |
format | Online Article Text |
id | pubmed-8999998 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89999982022-04-12 Examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation Mariano, C. A. Sattari, S. Quiros, K. A. M. Nelson, T. M. Eskandari, M. Respir Res Research BACKGROUND: Mechanical ventilation is often employed to facilitate breathing in patients suffering from respiratory illnesses and disabilities. Despite the benefits, there are risks associated with ventilator-induced lung injuries and death, driving investigations for alternative ventilation techniques to improve mechanical ventilation, such as multi-oscillatory and high-frequency ventilation; however, few studies have evaluated fundamental lung mechanical local deformations under variable loading. METHODS: Porcine whole lung samples were analyzed using a novel application of digital image correlation interfaced with an electromechanical ventilation system to associate the local behavior to the global volume and pressure loading in response to various inflation volumes and breathing rates. Strains, anisotropy, tissue compliance, and the evolutionary response of the inflating lung were analyzed. RESULTS: Experiments demonstrated a direct and near one-to-one linear relationship between applied lung volumes and resulting local mean strain, and a nonlinear relationship between lung pressures and strains. As the applied air delivery volume was doubled, the tissue surface mean strains approximately increased from 20 to 40%, and average maximum strains measured 70–110%. The tissue strain anisotropic ratio ranged from 0.81 to 0.86 and decreased with greater inflation volumes. Local tissue compliance during the inflation cycle, associating evolutionary strains in response to inflation pressures, was also quantified. CONCLUSION: Ventilation frequencies were not found to influence the local stretch response. Strain measures significantly increased and the anisotropic ratio decreased between the smallest and greatest tidal volumes. Tissue compliance did not exhibit a unifying trend. The insights provided by the real-time continuous measures, and the kinetics to kinematics pulmonary linkage established by this study offers valuable characterizations for computational models and establishes a framework for future studies to compare healthy and diseased lung mechanics to further consider alternatives for effective ventilation strategies. BioMed Central 2022-04-11 2022 /pmc/articles/PMC8999998/ /pubmed/35410291 http://dx.doi.org/10.1186/s12931-022-01999-7 Text en © The Author(s) 2022, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Mariano, C. A. Sattari, S. Quiros, K. A. M. Nelson, T. M. Eskandari, M. Examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation |
title | Examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation |
title_full | Examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation |
title_fullStr | Examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation |
title_full_unstemmed | Examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation |
title_short | Examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation |
title_sort | examining lung mechanical strains as influenced by breathing volumes and rates using experimental digital image correlation |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999998/ https://www.ncbi.nlm.nih.gov/pubmed/35410291 http://dx.doi.org/10.1186/s12931-022-01999-7 |
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