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

Yerworth, Rebecca J., Frerichs, Inéz and Bayford, Richard ORCID: https://orcid.org/0000-0001-8863-6385 (2017) Analysis and compensation for errors in electrical impedance tomography images and ventilation-­related measures due to serial data collection. Journal of Clinical Monitoring and Computing, 31 (5) . pp. 1093-1101. ISSN 1387-1307 [Article] (doi:10.1007/s10877-016-9920-y)

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Abstract

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 GOE­MF 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.

Item Type: Article
Research Areas: A. > School of Science and Technology > Natural Sciences > Biophysics and Bioengineering group
Item ID: 20323
Notes on copyright: © The Author(s) 2016. This article is published with open access at Springerlink.com
Open Access: This 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.
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Depositing User: Richard Bayford
Date Deposited: 12 Aug 2016 14:17
Last Modified: 08 Mar 2021 15:04
URI: https://eprints.mdx.ac.uk/id/eprint/20323

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