Pressure‐ and time‐dependent alveolar recruitment/derecruitment in a spatially resolved patient‐specific computational model for injured human lungs

Author:

Geitner Carolin M.1ORCID,Köglmeier Lea J.1,Frerichs Inéz2ORCID,Langguth Patrick3ORCID,Lindner Matthias2,Schädler Dirk2ORCID,Weiler Norbert2,Becher Tobias2ORCID,Wall Wolfgang A.1ORCID

Affiliation:

1. Institute for Computational Mechanics, Department of Engineering Physics & Computation, TUM School of Engineering and Design Technical University of Munich Garching b. Muenchen Germany

2. Department of Anesthesiology and Intensive Care Medicine University Medical Center Schleswig‐Holstein Campus Kiel Kiel Germany

3. Department of Radiology and Neuroradiology University Medical Center Schleswig‐Holstein Campus Kiel Kiel Germany

Abstract

AbstractWe present a novel computational model for the dynamics of alveolar recruitment/derecruitment (RD), which reproduces the underlying characteristics typically observed in injured lungs. The basic idea is a pressure‐ and time‐dependent variation of the stress‐free reference volume in reduced dimensional viscoelastic elements representing the acinar tissue. We choose a variable reference volume triggered by critical opening and closing pressures in a time‐dependent manner from a straightforward mechanical point of view. In the case of (partially and progressively) collapsing alveolar structures, the volume available for expansion during breathing reduces and vice versa, eventually enabling consideration of alveolar collapse and reopening in our model. We further introduce a method for patient‐specific determination of the underlying critical parameters of the new alveolar RD dynamics when integrated into the tissue elements, referred to as terminal units, of a spatially resolved physics‐based lung model that simulates the human respiratory system in an anatomically correct manner. Relevant patient‐specific parameters of the terminal units are herein determined based on medical image data and the macromechanical behavior of the lung during artificial ventilation. We test the whole modeling approach for a real‐life scenario by applying it to the clinical data of a mechanically ventilated patient. The generated lung model is capable of reproducing clinical measurements such as tidal volume and pleural pressure during various ventilation maneuvers. We conclude that this new model is an important step toward personalized treatment of ARDS patients by considering potentially harmful mechanisms—such as cyclic RD and overdistension—and might help in the development of relevant protective ventilation strategies to reduce ventilator‐induced lung injury (VILI).

Funder

Deutsche Forschungsgemeinschaft

Free To Breathe

Publisher

Wiley

Subject

Applied Mathematics,Computational Theory and Mathematics,Molecular Biology,Modeling and Simulation,Biomedical Engineering,Software

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