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Reduced-Dimension Modeling Approach for Simulating Recruitment/De-recruitment Dynamics in the Lung

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Abstract

Acute respiratory distress syndrome is a pulmonary disease that requires the use of mechanical ventilation for patient recovery. However, this can lead to development of ventilator-induced lung injury caused by the over-distension of alveolar tissue and by the repetitive closure (de-recruitment) and reopening (recruitment) of airways. In this study, we developed a multi-scale model of the lung from a reduced-dimension approach to investigate the dynamics of ventilation in the lung during airway collapse and reopening. The model consisted of an asymmetric network geometry with 16 generations of liquid-lined airways with airflow driven by a variable pleural pressure. During the respiratory cycle changes in airway radii and film thickness yield the formation of liquid plugs that propagate and rupture throughout the airway network. Simulations were conducted with constant surface tension values \(15 \le \gamma \le 25\) dyn/cm. It was observed that the time onset of plug creation and rupture depended on the surface tension, as well as the plug aggregation/splitting behavior at bifurcations. Additionally, the plug propagation behavior was significantly influenced by presence of plugs in adjacent airways (i.e. parent and daughters) that affected the driving pressure distribution locally at bifurcations and resulted in complex aggregation and splitting behavior. This model provides an approach that has the ability to simulate normal and pathophysiological lung conditions with the potential to be used in personalized clinical medicine.

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Acknowledgments

This study was supported by National Science Foundation Grant CBET-1033619 and Research Traineeship Grant DMS-1043626. Computational resources were supported in part using high performance computing (HPC) resources and services provided by Technology Services at Tulane University, New Orleans, LA.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Tulane University, 534 Lindy Boggs Building, New Orleans, LA, 70118, USA

    Jason Ryans & Donald P. Gaver

  2. Center for Computational Science, Tulane University, New Orleans, LA, USA

    Hideki Fujioka

  3. Department of Mathematics, University of Alabama, Tuscaloosa, AL, USA

    David Halpern

Authors
  1. Jason Ryans
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  2. Hideki Fujioka
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  3. David Halpern
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  4. Donald P. Gaver
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Corresponding author

Correspondence to Donald P. Gaver.

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Associate Editor Aleksander S. Popel oversaw the review of this article.

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Ryans, J., Fujioka, H., Halpern, D. et al. Reduced-Dimension Modeling Approach for Simulating Recruitment/De-recruitment Dynamics in the Lung. Ann Biomed Eng 44, 3619–3631 (2016). https://doi.org/10.1007/s10439-016-1672-9

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  • DOI: https://doi.org/10.1007/s10439-016-1672-9

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