Using injury cost functions from a predictive single-compartment model to assess the severity of mechanical ventilator-induced lung injuries.

Identifying safe ventilation patterns for patients with acute respiratory distress syndrome remains challenging because of the delicate balance between gas exchange and selection of ventilator settings to prevent further ventilator-induced lung injury (VILI). Accordingly, this work seeks to link ventilator settings to graded levels of VILI to identify injury cost functions that predict injury by using a computational model to process pressures and flows measured at the airway opening. Pressure-volume loops were acquired over the course of ~2 h of mechanical ventilation in four different groups of BALB/c mice. A cohort of these animals were subjected to an injurious bronchoalveolar lavage before ventilation. The data were analyzed with a single-compartment model that predicts recruitment/derecruitment and tissue distension at each time step in measured pressure-volume loops. We compared several injury cost functions to markers of VILI-induced blood-gas barrier disruption. Of the cost functions considered, we conclude that mechanical power dissipation and strain heterogeneity are the best at distinguishing between graded levels of injury and are good candidates for forecasting the development of VILI. This work uses a predictive single-compartment model and injury cost functions to assess graded levels of mechanical ventilator-induced lung injury. The most promising measures include strain heterogeneity and mechanical power dissipation.