MECHANICS OF ACUTE LUNG INJURY

University Of Vermont & St Agric College, Burlington VT

Investigators

Linked publications & trials

Abstract

[unreadable] DESCRIPTION (provided by applicant): Acute lung injury (ALI) is a common entity in critically ill people, and is fatal in roughly 40 percent of cases. Mechanical ventilation of patients with ALI may further damage the lung, leading to ventilator-induced lung injury (VILI) which is characterized by leakage of fluid from the vasculature into the alveolar spaces with concomitant collapse of large regions of the lung. It is common practice to re-open (recruit) collapsed lung using a recruitment maneuver - a deep inflation (Dl) of appropriate depth and duration. However, the benefits of a Dl in are transient, and can be very brief in severe ALI. Furthermore, while Dl's favor the maintenance of open lung, they also increase the stress applied to the lung tissues and so may favor the development of VILI. The central hypothesis of this proposal is that the Dl's can be delivered with a frequency, duration and magnitude that optimally balances the amount of open lung achieved against protection from VILI. The overall goals of the proposal is to establish that such an optimal recruitment regime exists, that it is specific to each subject, and that it can be deduced from ongoing measurements of pulmonary mechanics. We will verify this concept in mouse models of ALI and translate the concept to human patients, in the following three specific aims. Specific Aim 1: To establish how the frequency, magnitude and duration of deep inflations determine lung mechanics and the mean amount of open lung in mouse models of ALI. Specific Aim 2: To determine how the magnitude, frequency and duration of deep inflations lead to VILI. Specific Aim 3: To translate the results obtained in mouse models of ALI and VILI to human patients. The results of our studies are expected to lead to the design of physiologically-based lung recruitment strategies that can be tailored to the individual patient with ALI. This will set the stage for future clinical trials. [unreadable] [unreadable]