Visualisation of time-varying respiratory system elastance in experimental ARDS animal models.

Erwin J Van Drunen,Thomas Desaive,Christopher Pretty,J Geoffrey Chase,Bernard Lambermont,Nathalie Janssen,Geoffrey M Shaw,Yeong Shiong Chiew

doi:10.1186/1471-2466-14-33

Abstract

BackgroundPatients with acute respiratory distress syndrome (ARDS) risk lung collapse, severely altering the breath-to-breath respiratory mechanics. Model-based estimation of respiratory mechanics characterising patient-specific condition and response to treatment may be used to guide mechanical ventilation (MV). This study presents a model-based approach to monitor time-varying patient-ventilator interaction to guide positive end expiratory pressure (PEEP) selection.MethodsThe single compartment lung model was extended to monitor dynamic time-varying respiratory system elastance, Edrs, within each breathing cycle. Two separate animal models were considered, each consisting of three fully sedated pure pietrain piglets (oleic acid ARDS and lavage ARDS). A staircase recruitment manoeuvre was performed on all six subjects after ARDS was induced. The Edrs was mapped across each breathing cycle for each subject.ResultsSix time-varying, breath-specific Edrs maps were generated, one for each subject. Each Edrs map shows the subject-specific response to mechanical ventilation (MV), indicating the need for a model-based approach to guide MV. This method of visualisation provides high resolution insight into the time-varying respiratory mechanics to aid clinical decision making. Using the Edrs maps, minimal time-varying elastance was identified, which can be used to select optimal PEEP.ConclusionsReal-time continuous monitoring of in-breath mechanics provides further insight into lung physiology. Therefore, there is potential for this new monitoring method to aid clinicians in guiding MV treatment. These are the first such maps generated and they thus show unique results in high resolution. The model is limited to a constant respiratory resistance throughout inspiration which may not be valid in some cases. However, trends match clinical expectation and the results highlight both the subject-specificity of the model, as well as significant inter-subject variability.

Highlights

Patients with acute respiratory distress syndrome (ARDS) risk lung collapse, severely altering the breath-to-breath respiratory mechanics
ARDS patients are admitted to the intensive care unit (ICU) and require mechanical ventilation (MV) for breathing support
The time-varying, breath-specific Edrs map of the recruitment manoeuvre (RM) for Subjects 1-6 are shown in Figures 1, 2, 3, 4, 5 and 6 respectively, where blue indicates low Edrs and red indicates high Edrs

Summary

Introduction

Patients with acute respiratory distress syndrome (ARDS) risk lung collapse, severely altering the breath-to-breath respiratory mechanics. This study presents a model-based approach to monitor time-varying patient-ventilator interaction to guide positive end expiratory pressure (PEEP) selection. ARDS involves alterations in a patient’s breath-to-breath respiratory mechanics Modelling these alterations can potentially provide a non-invasive, patient-specific method to obtain clinically and physiologically useful information to guide treatment in real-time [8,9,10,11]. This approach can provide unique insight into disease progression and patient response to MV [12,13,14,15]. Real-time monitoring of respiratory mechanics throughout MV treatment is, to date, limited in clinical application and impact [16]

Methods

Results

Discussion

Conclusion