title: Bayesian inference of the lung alveolar spatial model for the identification of alveolar mechanics associated with acute respiratory distress syndrome.
abstract: Acute respiratory distress syndrome (ARDS) is acute lung failure secondary to severe systemic inflammation, resulting in a derangement of alveolar mechanics (i.e. the dynamic change in alveolar size and shape during tidal ventilation), leading to alveolar instability that can cause further damage to the pulmonary parenchyma. Mechanical ventilation is a mainstay in the treatment of ARDS, but may induce mechano-physical stresses on unstable alveoli, which can paradoxically propagate the cellular and molecular processes exacerbating ARDS pathology. This phenomenon is called ventilator induced lung injury (VILI), and plays a significant role in morbidity and mortality associated with ARDS. In order to identify optimal ventilation strategies to limit VILI and treat ARDS, it is necessary to understand the complex interplay between biological and physical mechanisms of VILI, first at the alveolar level, and then in aggregate at the whole-lung level. Since there is no current consensus about the underlying dynamics of alveolar mechanics, as an initial step we investigate the ventilatory dynamics of an alveolar sac (AS) with the lung alveolar spatial model (LASM), a 3D spatial biomechanical representation of the AS and its interaction with airflow pressure and the surface tension effects of pulmonary surfactant. We use the LASM to identify the mechanical ramifications of alveolar dynamics associated with ARDS. Using graphical processing unit parallel algorithms, we perform Bayesian inference on the model parameters using experimental data from rat lung under control and Tween-induced ARDS conditions. Our results provide two plausible models that recapitulate two fundamental hypotheses about volume change at the alveolar level: (1) increase in alveolar size through isotropic volume change, or (2) minimal change in AS radius with primary expansion of the mouth of the AS, with the implication that the majority of change in lung volume during the respiratory cycle occurs in the alveolar ducts. These two model solutions correspond to significantly different mechanical properties of the tissue, and we discuss the implications of these different properties and the requirements for new experimental data to discriminate between the hypotheses.
authors.affiliation: Department of Surgery, University of Chicago, Chicago, IL 60637, USA.
authors.forename: Scott
authors.initials: S
authors.lastname: Christley
authors.forename: Bryanna
authors.initials: B
authors.lastname: Emr
authors.forename: Auyon
authors.initials: A
authors.lastname: Ghosh
authors.forename: Josh
authors.initials: J
authors.lastname: Satalin
authors.forename: Louis
authors.initials: L
authors.lastname: Gatto
authors.forename: Yoram
authors.initials: Y
authors.lastname: Vodovotz
authors.forename: Gary F
authors.initials: GF
authors.lastname: Nieman
authors.forename: Gary
authors.initials: G
authors.lastname: An
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D001696:Biomechanical Phenomena; D008168:Lung / Q000378:metabolism / Q000473:pathology*; D008954:Models, Biological; D011650:Pulmonary Alveoli / Q000378:metabolism / Q000473:pathology*; D011663:Pulmonary Surfactants / Q000378:metabolism; D051381:Rats; D017207:Rats, Sprague-Dawley; D012128:Respiratory Distress Syndrome / Q000378:metabolism / Q000473:pathology*
chemical_list: D011663:Pulmonary Surfactants