Mechanical ventilation is an essential lifesaving therapy in acute respiratory distress syndrome (ARDS) that may cause ventilator-induced lung injury (VILI) through a positive feedback between altered alveolar mechanics, edema, surfactant inactivation, and injury. Although the biophysical forces that cause VILI are well documented, a knowledge gap remains in the quantitative link between altered parenchymal structure (namely alveolar derecruitment and flooding), pulmonary function, and VILI. This information is essential to developing diagnostic criteria and ventilation strategies to reduce VILI and improve ARDS survival. To address this unmet need, we mechanically ventilated mice to cause VILI. Lung structure was measured at three air inflation pressures using design-based stereology, and the mechanical function of the pulmonary system was measured with the forced oscillation technique. Assessment of the pulmonary surfactant included total surfactant, distribution of phospholipid aggregates, and surface tension lowering activity. VILI-induced changes in the surfactant included reduced surface tension lowering activity in the typically functional fraction of large phospholipid aggregates and a significant increase in the pool of surface-inactive small phospholipid aggregates. The dominant alterations in lung structure at low airway pressures were alveolar collapse and flooding. At higher airway pressures, alveolar collapse was mitigated and the flooded alveoli remained filled with proteinaceous edema. The loss of ventilated alveoli resulted in decreased alveolar gas volume and gas-exchange surface area. These data characterize three alveolar phenotypes in murine VILI: flooded and non-recruitable alveoli, unstable alveoli that derecruit at airway pressures below 5 cmH 2 O, and alveoli with relatively normal structure and function. The fraction of alveoli with each phenotype is reflected in the proportional changes in pulmonary system elastance at positive end expiratory pressures of 0, 3, and 6 cmH 2 O.

Background: CT screening for lung cancer results in a significant mortality reduction but is complicated by invasive procedures performed for evaluation of the many detected benign nodules. The purpose of this study was to evaluate measures of nodule location within the lung as predictors of malignancy. Methods: We analyzed images and data from 3,483 participants in the National Lung Screening Trial (NLST). All nodules (4-20 mm) were characterized by 3D geospatial location using a Cartesian coordinate system and evaluated in logistic regression analysis. Model development and probability cutpoint selection was performed in the NLST testing set. The Geospatial test was then validated in the NLST testing set, and subsequently replicated in a new cohort of 147 participants from The Detection of Early Lung Cancer Among Military Personnel (DECAMP) Consortium. Results: The Geospatial Test, consisting of the superior-inferior distance (Z distance), nodule diameter, and radial distance (carina to nodule) performed well in both the NLST validation set (AUC 0.85) and the DECAMP replication cohort (AUC 0.75). A negative Geospatial Test resulted in a less than 2% risk of cancer across all nodule diameters. The Geospatial Test correctly reclassified 19.7% of indeterminate nodules with a diameter over 6mm as benign, while only incorrectly classifying 1% of cancerous nodules as benign. In contrast, the parsimonious Brock Model applied to the same group of nodules correctly reclassified 64.5% of indeterminate nodules as benign but resulted in misclassification of a cancer as benign in 18.2% of the cases. Applying the Geospatial test would result in reducing invasive procedures performed for benign lesions by 11.3% with a low rate of misclassification (1.3%). In contrast, the Brock model applied to the same group of patients results in decreasing invasive procedures for benign lesion by 39.0% but misclassifying 21.1% of cancers as benign.