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Our main object is the development of a model that takes the novel step of incorporating the dynamics of airway recruitment\/derecruitment into an anatomically accurate, spatially resolved model of respiratory system mechanics, and the relation of these dynamics to airway dimensions and the biophysical properties of the lining fluid. The importance of our approach is that it potentially allows for more accurate predictions of where mechanical stress foci arise in the lungs, since it is at these locations that injury is thought to arise and propagate from. We match the model to data from a patient with acute respiratory distress syndrome (ARDS) to demonstrate the potential of the model for revealing the underlying derangements in ARDS in a patient\u2010specific manner. To achieve this, the specific geometry of the lung and its heterogeneous pattern of injury are extracted from medical CT images. The mechanical behavior of the model is tailored to the patient's respiratory mechanics using measured ventilation data. In retrospective simulations of various clinically performed, pressure\u2010driven ventilation profiles, the model adequately reproduces clinical quantities measured in the patient such as tidal volume and change in pleural pressure. The model also exhibits physiologically reasonable lung recruitment dynamics and has the spatial resolution to allow the study of local mechanical quantities such as alveolar strains. This modeling approach advances our ability to perform patient\u2010specific studies in silico, opening the way to personalized therapies that will optimize patient outcomes.<\/jats:p>","DOI":"10.1002\/cnm.3745","type":"journal-article","created":{"date-parts":[[2023,7,5]],"date-time":"2023-07-05T07:11:39Z","timestamp":1688541099000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["An approach to study recruitment\/derecruitment dynamics in a patient\u2010specific computational model of an injured human lung"],"prefix":"10.1002","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0370-2265","authenticated-orcid":false,"given":"Carolin M.","family":"Geitner","sequence":"first","affiliation":[{"name":"Institute for Computational Mechanics, Department of Engineering Physics &amp; Computation, TUM School of Engineering and Design Technical University of Munich  Garching b. Muenchen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2026-7629","authenticated-orcid":false,"given":"Tobias","family":"Becher","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Intensive Care Medicine University Medical Center Schleswig\u2010Holstein, Campus Kiel  Kiel Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7712-6539","authenticated-orcid":false,"given":"In\u00e9z","family":"Frerichs","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Intensive Care Medicine University Medical Center Schleswig\u2010Holstein, Campus Kiel  Kiel Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norbert","family":"Weiler","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Intensive Care Medicine University Medical Center Schleswig\u2010Holstein, Campus Kiel  Kiel Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6062-6377","authenticated-orcid":false,"given":"Jason H. 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