Tidal changes in PaO2 and their relationship to cyclical lung recruitment/derecruitment in a porcine lung injury model.

BACKGROUND: Tidal recruitment/derecruitment (R/D) of collapsed regions in lung injury has been presumed to cause respiratory oscillations in the partial pressure of arterial oxygen (PaO2). These phenomena have not yet been studied simultaneously. We examined the relationship between R/D and PaO2 oscillations by contemporaneous measurement of lung-density changes and PaO2. METHODS: Five anaesthetised pigs were studied after surfactant depletion via a saline-lavage model of R/D. The animals were ventilated with a mean fraction of inspired O2 (FiO2) of 0.7 and a tidal volume of 10 ml kg-1. Protocolised changes in pressure- and volume-controlled modes, inspiratory:expiratory ratio (I:E), and three types of breath-hold manoeuvres were undertaken. Lung collapse and PaO2 were recorded using dynamic computed tomography (dCT) and a rapid PaO2 sensor. RESULTS: During tidal ventilation, the expiratory lung collapse increased when I:E <1 [mean (standard deviation) lung collapse=15.7 (8.7)%; P<0.05], but the amplitude of respiratory PaO2 oscillations [2.2 (0.8) kPa] did not change during the respiratory cycle. The expected relationship between respiratory PaO2 oscillation amplitude and R/D was therefore not clear. Lung collapse increased during breath-hold manoeuvres at end-expiration and end-inspiration (14% vs 0.9-2.1%; P<0.0001). The mean change in PaO2 from beginning to end of breath-hold manoeuvres was significantly different with each type of breath-hold manoeuvre (P<0.0001). CONCLUSIONS: This study in a porcine model of collapse-prone lungs did not demonstrate the expected association between PaO2 oscillation amplitude and the degree of recruitment/derecruitment. The results suggest that changes in pulmonary ventilation are not the sole determinant of changes in PaO2 during mechanical ventilation in lung injury.

Simulation-based optimisation to quantify heterogeneity of specific ventilation and perfusion in the lung by the Inspired Sinewave Test.

The degree of specific ventilatory heterogeneity (spatial unevenness of ventilation) of the lung is a useful marker of early structural lung changes which has the potential to detect early-onset disease. The Inspired Sinewave Test (IST) is an established noninvasive 'gas-distribution' type of respiratory test capable of measuring the cardiopulmonary parameters. We developed a simulation-based optimisation for the IST, with a simulation of a realistic heterogeneous lung, namely a lognormal distribution of spatial ventilation and perfusion. We tested this method in datasets from 13 anaesthetised pigs (pre and post-lung injury) and 104 human subjects (32 healthy and 72 COPD subjects). The 72 COPD subjects were classified into four COPD phenotypes based on 'GOLD' classification. This method allowed IST to identify and quantify heterogeneity of both ventilation and perfusion, permitting diagnostic distinction between health and disease states. In healthy volunteers, we show a linear relationship between the ventilatory heterogeneity versus age ([Formula: see text]). In a mechanically ventilated pig, IST ventilatory heterogeneity in noninjured and injured lungs was significantly different (p < 0.0001). Additionally, measured indices could accurately identify patients with COPD (area under the receiver operating characteristic curve is 0.76, p < 0.0001). The IST also could distinguish different phenotypes of COPD with 73% agreement with spirometry.