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  3. Determination of respiratory gas flow by electrical impedance tomography in an animal model of mechanical ventilation
 

Determination of respiratory gas flow by electrical impedance tomography in an animal model of mechanical ventilation

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BORIS DOI
10.7892/boris.66009
Date of Publication
2014
Publication Type
Article
Division/Institute

Universitätsklinik fü...

Contributor
Bodenstein, Marc
Boehme, Stefan
Bierschock, Stephan
Vogt, Andreasorcid-logo
Universitätsklinik für Anästhesiologie und Schmerztherapie
David, Matthias
Markstaller, Klaus
Subject(s)

600 - Technology::610...

Series
BMC pulmonary medicine
ISSN or ISBN (if monograph)
1471-2466
Publisher
BioMed Central
Language
English
Publisher DOI
10.1186/1471-2466-14-73
PubMed ID
24779960
Description
Background

A recent method determines regional gas flow of the lung by electrical impedance tomography (EIT). The aim of this study is to show the applicability of this method in a porcine model of mechanical ventilation in healthy and diseased lungs. Our primary hypothesis is that global gas flow measured by EIT can be correlated with spirometry. Our secondary hypothesis is that regional analysis of respiratory gas flow delivers physiologically meaningful results.
Methods

In two sets of experiments n = 7 healthy pigs and n = 6 pigs before and after induction of lavage lung injury were investigated. EIT of the lung and spirometry were registered synchronously during ongoing mechanical ventilation. In-vivo aeration of the lung was analysed in four regions-of-interest (ROI) by EIT: 1) global, 2) ventral (non-dependent), 3) middle and 4) dorsal (dependent) ROI. Respiratory gas flow was calculated by the first derivative of the regional aeration curve. Four phases of the respiratory cycle were discriminated. They delivered peak and late inspiratory and expiratory gas flow (PIF, LIF, PEF, LEF) characterizing early or late inspiration or expiration.
Results

Linear regression analysis of EIT and spirometry in healthy pigs revealed a very good correlation measuring peak flow and a good correlation detecting late flow. PIFEIT = 0.702 · PIFspiro + 117.4, r2 = 0.809; PEFEIT = 0.690 · PEFspiro-124.2, r2 = 0.760; LIFEIT = 0.909 · LIFspiro + 27.32, r2 = 0.572 and LEFEIT = 0.858 · LEFspiro-10.94, r2 = 0.647. EIT derived absolute gas flow was generally smaller than data from spirometry. Regional gas flow was distributed heterogeneously during different phases of the respiratory cycle. But, the regional distribution of gas flow stayed stable during different ventilator settings. Moderate lung injury changed the regional pattern of gas flow.
Conclusions

We conclude that the presented method is able to determine global respiratory gas flow of the lung in different phases of the respiratory cycle. Additionally, it delivers meaningful insight into regional pulmonary characteristics, i.e. the regional ability of the lung to take up and to release air.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/131370
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1471-2466-14-73.pdftextAdobe PDF1.12 MBpublishedOpen
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