Carolin M. Geitner, Lea J. Köglmeier, Inéz Frerichs, Patrick Langguth, Matthias Lindner, Dirk Schädler, Norbert Weiler, Tobias Becher, Wolfgang A. Wall
{"title":"在一个空间分辨的患者特异性损伤人肺计算模型中,压力和时间依赖性肺泡恢复/消失。","authors":"Carolin M. Geitner, Lea J. Köglmeier, Inéz Frerichs, Patrick Langguth, Matthias Lindner, Dirk Schädler, Norbert Weiler, Tobias Becher, Wolfgang A. Wall","doi":"10.1002/cnm.3787","DOIUrl":null,"url":null,"abstract":"<p>We 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).</p>","PeriodicalId":50349,"journal":{"name":"International Journal for Numerical Methods in Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cnm.3787","citationCount":"0","resultStr":"{\"title\":\"Pressure- and time-dependent alveolar recruitment/derecruitment in a spatially resolved patient-specific computational model for injured human lungs\",\"authors\":\"Carolin M. Geitner, Lea J. 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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. 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Pressure- and time-dependent alveolar recruitment/derecruitment in a spatially resolved patient-specific computational model for injured human lungs
We 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).
期刊介绍:
All differential equation based models for biomedical applications and their novel solutions (using either established numerical methods such as finite difference, finite element and finite volume methods or new numerical methods) are within the scope of this journal. Manuscripts with experimental and analytical themes are also welcome if a component of the paper deals with numerical methods. Special cases that may not involve differential equations such as image processing, meshing and artificial intelligence are within the scope. Any research that is broadly linked to the wellbeing of the human body, either directly or indirectly, is also within the scope of this journal.