Comparison of bolus- and filtering-based EIT measures of lung perfusion in an animal model
Objective: Two main functional imaging approaches have been used to measure regional lung perfusion using electrical impedance tomography (EIT): venous injection of a hypertonic saline contrast agent and imaging of its passage through the heart and lungs, and digital filtering of heart-frequency imp...
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Published in | Physiological measurement Vol. 40; no. 5; p. 054002 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
IOP Publishing
04.06.2019
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Subjects | |
Online Access | Get full text |
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Summary: | Objective: Two main functional imaging approaches have been used to measure regional lung perfusion using electrical impedance tomography (EIT): venous injection of a hypertonic saline contrast agent and imaging of its passage through the heart and lungs, and digital filtering of heart-frequency impedance changes over sequences of EIT images. This paper systematically compares filtering-based perfusion estimates and bolus injection methods to determine to which degree they are related. Approach: EIT data was recorded on seven mechanically ventilated newborn lambs in which ventilation distribution was varied through changes in posture between prone, supine, left- and right-lateral positions. Perfusion images were calculated using frequency filtering and ensemble averaging during both ventilation and apnoea time segments for each posture to compare against contrast agent-based methods using Jaccard distance score. Main results: Using bolus-based EIT measures of lung perfusion as the reference frequency filtering techniques performed better than ensemble averaging and both techniques performed equally well across apnoea and ventilation data segments. Significance: Our results indicate the potential for use of filtering-based EIT measures of heart-frequency activity as a non-invasive proxy for contrast agent injection-based measures of lung perfusion. |
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Bibliography: | Institute of Physics and Engineering in Medicine PMEA-102877.R1 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0967-3334 1361-6579 1361-6579 |
DOI: | 10.1088/1361-6579/ab1794 |