Towards a multi-scale computer modeling workflow for simulation of pulmonary ventilation in advanced COVID-19 Article Swipe
Shea Middleton
,
Elizabeth Dimbath
,
Anup Pant
,
Stephanie M. George
,
Veeranna Maddipati
,
M. Sean Peach
,
Kaida Yang
,
Andrew Ju
,
Ali Vahdati
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.compbiomed.2022.105513
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.compbiomed.2022.105513
Physics-based multi-scale in silico models offer an excellent opportunity to study the effects of heterogeneous tissue damage on airflow and pressure distributions in COVID-19-afflicted lungs. The main objective of this study is to develop a computational modeling workflow, coupling airflow and tissue mechanics as the first step towards a virtual hypothesis-testing platform for studying injury mechanics of COVID-19-afflicted lungs. We developed a CT-based modeling approach to simulate the regional changes in lung dynamics associated with heterogeneous subject-specific COVID-19-induced damage patterns in the parenchyma. Furthermore, we investigated the effect of various levels of inflammation in a meso-scale acinar mechanics model on global lung dynamics. Our simulation results showed that as the severity of damage in the patient's right lower, left lower, and to some extent in the right upper lobe increased, ventilation was redistributed to the least injured right middle and left upper lobes. Furthermore, our multi-scale model reasonably simulated a decrease in overall tidal volume as the level of tissue injury and surfactant loss in the meso-scale acinar mechanics model was increased. This study presents a major step towards multi-scale computational modeling workflows capable of simulating the effect of subject-specific heterogenous COVID-19-induced lung damage on ventilation dynamics.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.compbiomed.2022.105513
- OA Status
- hybrid
- Cited By
- 9
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4223637094
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4223637094Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.compbiomed.2022.105513Digital Object Identifier
- Title
-
Towards a multi-scale computer modeling workflow for simulation of pulmonary ventilation in advanced COVID-19Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-04-12Full publication date if available
- Authors
-
Shea Middleton, Elizabeth Dimbath, Anup Pant, Stephanie M. George, Veeranna Maddipati, M. Sean Peach, Kaida Yang, Andrew Ju, Ali VahdatiList of authors in order
- Landing page
-
https://doi.org/10.1016/j.compbiomed.2022.105513Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.compbiomed.2022.105513Direct OA link when available
- Concepts
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Ventilation (architecture), Parenchyma, Scale (ratio), Workflow, Computer science, Computational fluid dynamics, Airflow, Mechanics, Simulation, Lung, Mechanical ventilation, Medicine, Physics, Mechanical engineering, Engineering, Pathology, Meteorology, Internal medicine, Quantum mechanics, DatabaseTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
9Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 4, 2023: 3Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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