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Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection

Electrical impedance tomography (EIT) is increasingly being used as a bedside tool for monitoring regional lung ventilation. However, most clinical systems use serial data collection which, if uncorrected, results in image distortion, particularly at high breathing rates. The objective of this study...

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Detalles Bibliográficos
Autores principales: Yerworth, Rebecca J., Frerichs, Inéz, Bayford, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5599443/
https://www.ncbi.nlm.nih.gov/pubmed/27534624
http://dx.doi.org/10.1007/s10877-016-9920-y
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author Yerworth, Rebecca J.
Frerichs, Inéz
Bayford, Richard
author_facet Yerworth, Rebecca J.
Frerichs, Inéz
Bayford, Richard
author_sort Yerworth, Rebecca J.
collection PubMed
description Electrical impedance tomography (EIT) is increasingly being used as a bedside tool for monitoring regional lung ventilation. However, most clinical systems use serial data collection which, if uncorrected, results in image distortion, particularly at high breathing rates. The objective of this study was to determine the extent to which this affects derived parameters. Raw EIT data were acquired with the GOE-MF II EIT device (CareFusion, Höchberg, Germany) at a scan rate of 13 images/s during both spontaneous breathing and mechanical ventilation. Boundary data for periods of undisturbed tidal breathing were corrected for serial data collection errors using a Fourier based algorithm. Images were reconstructed for both the corrected and original data using the GREIT algorithm, and parameters describing the filling characteristics of the right and left lung derived on a breath by breath basis. Values from the original and corrected data were compared using paired t-tests. Of the 33 data sets, 23 showed significant differences in filling index for at least one region, 11 had significant differences in calculated tidal impedance change and 12 had significantly different filling fractions (p = 0.05). We conclude that serial collection errors should be corrected before image reconstruction to avoid clinically misleading results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10877-016-9920-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-55994432017-10-03 Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection Yerworth, Rebecca J. Frerichs, Inéz Bayford, Richard J Clin Monit Comput Original Research Electrical impedance tomography (EIT) is increasingly being used as a bedside tool for monitoring regional lung ventilation. However, most clinical systems use serial data collection which, if uncorrected, results in image distortion, particularly at high breathing rates. The objective of this study was to determine the extent to which this affects derived parameters. Raw EIT data were acquired with the GOE-MF II EIT device (CareFusion, Höchberg, Germany) at a scan rate of 13 images/s during both spontaneous breathing and mechanical ventilation. Boundary data for periods of undisturbed tidal breathing were corrected for serial data collection errors using a Fourier based algorithm. Images were reconstructed for both the corrected and original data using the GREIT algorithm, and parameters describing the filling characteristics of the right and left lung derived on a breath by breath basis. Values from the original and corrected data were compared using paired t-tests. Of the 33 data sets, 23 showed significant differences in filling index for at least one region, 11 had significant differences in calculated tidal impedance change and 12 had significantly different filling fractions (p = 0.05). We conclude that serial collection errors should be corrected before image reconstruction to avoid clinically misleading results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10877-016-9920-y) contains supplementary material, which is available to authorized users. Springer Netherlands 2016-08-17 2017 /pmc/articles/PMC5599443/ /pubmed/27534624 http://dx.doi.org/10.1007/s10877-016-9920-y Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Research
Yerworth, Rebecca J.
Frerichs, Inéz
Bayford, Richard
Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection
title Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection
title_full Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection
title_fullStr Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection
title_full_unstemmed Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection
title_short Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection
title_sort analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5599443/
https://www.ncbi.nlm.nih.gov/pubmed/27534624
http://dx.doi.org/10.1007/s10877-016-9920-y
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