TY  - JOUR
A1  - Grychtol, Bartłomiej
A1  - Elke, Gunnar
A1  - Meybohm, Patrick
A1  - Weiler, Norbert
A1  - Frerichs, Inéz
A1  - Adler, Andy
T1  - Functional validation and comparison framework for EIT lung imaging
T2  - PLoS One
N2  - Introduction: Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited.
Methods: We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data.
Results and Conclusions: Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT.
Y1  - 2014
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/34775
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-347753
SN  - 1932-6203
N1  - Copyright: © 2014 Grychtol et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
VL  - 9
IS  - (8):e103045
PB  - PLoS
CY  - Lawrence, Kan.
ER  -