4.7 Article

Inhomogeneity of Lung Parenchyma during the Open Lung Strategy A Computed Tomography Scan Study

Journal

Publisher

AMER THORACIC SOC
DOI: 10.1164/rccm.200901-0156OC

Keywords

acute lung injury; mechanical ventilation; alveolar recruitment; ventilator-induced lung injury

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Rationale The open lung strategy aims at reopening (recruitment) of nonaerated lung areas in patients with acute respiratory distress syndrome, avoiding tidal alveolar hyperinflation in the limited area of normally aerated tissue (baby lung). Objectives: We tested the hypothesis that recruited lung areas do not resume elastic properties of adjacent baby lung. Methods: Twenty-five anesthetized, mechanically ventilated pigs were studied. Four lung-healthy pigs served as controls and the remaining 21 were divided into three groups (n = 7 each) in which lung injury was produced by surfactant lavage, lipopolysaccharide infusion, or hydrochloride inhalation. Computed tomography scans, respiratory mechanics, and gas exchange parameters were recorded under three conditions: at baseline, during lung recruitment maneuver, and at end-expiration and end-inspiration when ventilating after an open lung protocol. Measurements and Main Results: During recruitment maneuver and open lung protocol, the gas volume entering the insufficiently aerated compartment was 96% (75-117%) and 48% (41-63%) (median [interquartile range]) of the functional residual capacity measured before and at zero end-expiratory pressure, respectively. Nonetheless, the volume of hyperinflated lung increased during both recruitment maneuver (by 1-28% of total lung volume; P < 0.01) and open lung protocol ventilation at end-inspiration (by 1-15% of total lung volume; P < 0.01). Regional elastance of recruited lung tissue was consistently higher than that of the baby lung regardless of the ARDS model (P < 0.01). Conclusions: Alveolar recruitment is not protective against hyperinflation of the baby lung because lung parenchyma is inhomogeneous during ventilation with the open lung strategy.

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