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Ventilation treatment of acute lung injury (ALI) requires the application of positive airway pressure at the end of expiration (PEEP app ) to avoid lung collapse. However, the total pressure exerted on the alveolar walls (PEEP tot ) is the sum of PEEP app and intrinsic PEEP (PEEP i ), a hidden component. To measure PEEP tot , ventilation must be discontinued with an end-expiratory hold maneuver (EEHM). We hypothesized that artificial neural networks (ANN) could estimate the PEEP tot from flow and pressure tracings during ongoing mechanical ventilation. Ten pigs were mechanically ventilated, and the time constant of their respiratory system (τ RS ) was measured. We shortened their expiratory time (TE) according to multiples of τ RS , obtaining different respiratory patterns (R pat ). Pressure (P AW ) and flow (V' AW ) at the airway opening during ongoing mechanical ventilation were simultaneously recorded, with and without the addition of external resistance. The last breath of each R pat included an EEHM, which was used to compute the reference PEEP tot . The entire protocol was repeated after the induction of ALI with i.v. injection of oleic acid, and 382 tracings were obtained. The ANN had to extract the PEEP tot , from the tracings without an EEHM. ANN agreement with reference PEEP tot was assessed with the Bland-Altman method. Bland Altman analysis of estimation error by ANN showed -0.40 ± 2.84 (expressed as bias ± precision) and ±5.58 as limits of agreement (data expressed as cmH 2 O). The ANNs estimated the PEEP tot well at different levels of PEEP app under dynamic conditions, opening up new possibilities in monitoring PEEP i in critically ill patients who require ventilator treatment.

Objectives: Positive pressure ventilation exposes the lung to mechanical stresses that can exacerbate injury. The exact mechanism of this pathologic process remains elusive. The goal of this study was to describe recruitment/derecruitment at acinar length scales over short-time frames and test the hypothesis that mechanical interdependence between neighboring lung units determines the spatial and temporal distributions of recruitment/derecruitment, using a computational model., Design: Experimental animal study., Setting: International synchrotron radiation laboratory., Subjects: Four anesthetized rabbits, ventilated in pressure controlled mode., Interventions: The lung was consecutively imaged at ~ 1.5-minute intervals using phase-contrast synchrotron imaging, at positive end-expiratory pressures of 12, 9, 6, 3, and 0 cm H2O before and after lavage and mechanical ventilation induced injury. The extent and spatial distribution of recruitment/derecruitment was analyzed by subtracting subsequent images. In a realistic lung structure, we implemented a mechanistic model in which each unit has individual pressures and speeds of opening and closing. Derecruited and recruited lung fractions (Fderecruited, Frecruited) were computed based on the comparison of the aerated volumes at successive time points., Measurements and Main Results: Alternative recruitment/derecruitment occurred in neighboring alveoli over short-time scales in all tested positive end-expiratory pressure levels and despite stable pressure controlled mode. The computational model reproduced this behavior only when parenchymal interdependence between neighboring acini was accounted for. Simulations closely mimicked the experimental magnitude of Fderecruited and Frecruited when mechanical interdependence was included, while its exclusion gave Frecruited values of zero at positive end-expiratory pressure greater than or equal to 3 cm H2O., Conclusions: These findings give further insight into the microscopic behavior of the injured lung and provide a means of testing protective-ventilation strategies to prevent recruitment/derecruitment and subsequent lung damage.

Computed tomography (CT), together with image analysis technologies, enable the construction of regional volume (VREG) and local transpulmonary pressure (PTP,REG) maps of the lung. Purpose of this study is to assess the distribution of VREG vs PTP,REG along the gravitational axis in healthy (HL) and experimental acute lung injury conditions (eALI) at various positive end-expiratory pressures (PEEPs) and inflation volumes. Mechanically ventilated pigs underwent inspiratory hold maneuvers at increasing volumes simultaneously with lung CT scans. eALI was induced via the iv administration of oleic acid. We computed voxel-level VREG vs PTP,REG curves into eleven isogravitational planes by applying polynomial regressions. Via F-test, we determined that VREG vs PTP,REG curves derived from different anatomical planes (p-values<1.4E-3), exposed to different PEEPs (p-values<1.5E-5) or subtending different lung status (p-values<3E-3) were statistically different (except for two cases of adjacent planes). Lung parenchyma exhibits different elastic behaviors based on its position and the density of superimposed tissue which can increase during lung injury., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Computed tomography (CT) can yield quantitative information about volume distribution in the lung. By combining information provided by CT and respiratory mechanics, this study aims at quantifying regional lung compliance (CL) and its distribution and homogeneity in mechanically ventilated pigs. The animals underwent inspiratory hold maneuvers at 12 lung volumes with simultaneous CT exposure at two end-expiratory pressure levels and before and after acute lung injury (ALI) by oleic acid administration. CL and the sum of positive voxel compliances from CT were linearly correlated; negative compliance areas were found. A remarkably heterogeneous distribution of voxel compliance was found in the injured lungs. As the lung inflation increased, the homogeneity increased in healthy lungs but decreased in injured lungs. Image analysis brought novel findings regarding spatial homogeneity of compliance, which increases in ALI but not in healthy lungs by applying PEEP after a recruitment maneuver. [ABSTRACT FROM AUTHOR]