title: Analysis and compensation for errors in electrical impedance tomography images and ventilation-related measures due to serial data collection.
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 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.
authors.affiliation: Medical Physics and Biomedical Engineering Department, University College London, London, WC1E 6BT, England, UK. r.yerworth@ucl.ac.uk.
authors.forename: Rebecca J
authors.identifier: http://orcid.org/0000-0003-4442-1643
authors.initials: RJ
authors.lastname: Yerworth
authors.affiliation: Department of Anaesthesiology and Intensive Care Medicine, University Medical Centre Schleswig-Holstein, Campus Kiel, Kiel, Germany.
authors.forename: Inéz
authors.initials: I
authors.lastname: Frerichs
authors.affiliation: Department of Natural Sciences, Middlesex University, London, England, UK.
authors.forename: Richard
authors.initials: R
authors.lastname: Bayford
mesh_terms: D000328:Adult; D000465:Algorithms; D003625:Data Collection; D017097:Electric Impedance; D004566:Electrodes; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008168:Lung / Q000473:pathology*; D008991:Monitoring, Physiologic / Q000379:methods; D015203:Reproducibility of Results; D012119:Respiration; D012121:Respiration, Artificial / Q000379:methods*; D012189:Retrospective Studies; D012815:Signal Processing, Computer-Assisted; D014054:Tomography / Q000379:methods*
keywords: EIT; Imaging; Lung; Mechanical ventilation; Ventilation distribution