Article
Reference
Chest electrical impedance tomography examination, data analysis,
terminology, clinical use and recommendations: consensus statement
of the translational eit development study group
FRERICHS, Inéz, et al. & TREND study group
Abstract
Electrical impedance tomography (EIT) has undergone 30 years of development. Functional
chest examinations with this technology are considered clinically relevant, especially for
monitoring regional lung ventilation in mechanically ventilated patients and for regional
pulmonary function testing in patients with chronic lung diseases. As EIT becomes an
established medical technology, it requires consensus examination, nomenclature, data
analysis and interpretation schemes. Such consensus is needed to compare, understand and
reproduce study findings from and among different research groups, to enable large clinical
trials and, ultimately, routine clinical use. Recommendations of how EIT findings can be
applied to generate diagnoses and impact clinical decision-making and therapy planning are
required. This consensus paper was prepared by an international working group, collaborating
on the clinical promotion of EIT called TRanslational EIT developmeNt stuDy group. It
addresses the stated needs by providing (1) a new classification of core processes involved in
chest EIT examinations and data analysis, (2) focus on [...]
FRERICHS, Inéz, et al. & TREND study group. Chest electrical impedance tomography
examination, data analysis, terminology, clinical use and recommendations: consensus
statement of the translational eit development study group. Thorax, 2017, vol. 72, no. 1, p.
83-93
DOI : 10.1136/thoraxjnl-2016-208357
PMID : 27596161
Available at:
http://archive-ouverte.unige.ch/unige:96763
Disclaimer: layout of this document may differ from the published version.
1 / 1
Chest electrical impedance tomography examination,
data analysis, terminology, clinical use and
recommendations: consensus statement of the
TRanslational EIT developmeNt stuDy group
Inéz Frerichs,
1
Marcelo B P Amato,
2
Anton H van Kaam,
3
David G Tingay,
4
Zhanqi Zhao,
5
Bartłomiej Grychtol,
6
Marc Bodenstein,
7
Hervé Gagnon,
8
Stephan H Böhm,
9
Eckhard Teschner,
10
Ola Stenqvist,
11
Tommaso Mauri,
12
Vinicius Torsani,
2
Luigi Camporota,
13
Andreas Schibler,
14
Gerhard K Wolf,
15
Diederik Gommers,
16
Steffen Leonhardt,
17
Andy Adler,
8
TREND study group
▸ Additional material is
published online only. To view
please visit the journal online
(http://dx.doi.org/10.1136/
thoraxjnl-2016-208357).
For numbered affiliations see
end of article.
Correspondence t o
Professor Dr Inéz Frerichs,
Department of Anesthesiology
and Intensive Care Medicine,
University Medical Center
Schleswig-Holstein, Campus
Kiel, Arnold-Heller-Str. 3,
Kiel 24105, Germany;
frerichs@anaesthesie.uni-kiel.de
Received 19 January 2016
Revised 12 July 2016
Accepted 16 July 2016
Published Online First
5 September 2016
To cite: Frerichs I,
Amato MBP, van Kaam AH,
et al. Thorax 2017;72:83–
93.
ABSTRACT
Electrical impedance tomography (EIT) has undergone
30 years of development. Functional chest examinations
with this technology are considered clinically relevant,
especially for monitoring regional lung ventilation in
mechanically ventilated patients and for regional
pulmonary function testing in patients with chronic lung
diseases. As EIT becomes an established medical
technology, it requires consensus examination,
nomenclature, data analysis and interpretation schemes.
Such consensus is needed to compare, understand and
reproduce study findings from and among different
research groups, to enable large clinical trials and,
ultimately, routine clinical use. Recommendations of how
EIT findings can be applied to generate diagnoses and
impact clinical decision-making and therapy planning are
required. This consensus paper was prepared by an
international working group, collaborating on the clinical
promotion of EIT called TRanslational EIT developmeNt
stuDy group. It addresses the stated needs by providing
(1) a new classification of core processes involved in
chest EIT examinations and data analysis, (2) focus on
clinical applications with structured reviews and outlooks
(separately for adult and neonatal/paediatric patients),
(3) a structured framework to categorise and understand
the relationships among analysis approaches and their
clinical roles, (4) consensus, unified terminology with
clinical user-friendly definitions and explanations, (5) a
review of all major work in thoracic EIT and (6)
recommendations for future development (193 pages of
online supplements systematically linked with the chief
sections of the main document). We expect this
information to be useful for clinicians and researchers
working with EIT, as well as for industry producers of
this technology.
INTRODUCTION
Electrical impedance tomography (EIT) is a
radiation-free functional imaging modality invented
over 30 years ago.
1
Scientific and clinical interest in
this method is driven by the clinical need for moni-
toring of lung ventilation and perfusion and for
assessment of regional lung function at the bedside.
The growing interest is testified by the continuously
increasing number of publications on EIT and by
the commercial availability of devices from several
companies.
This paper was prepared by a working group,
collaborating on the clinical promotion of EIT
called TRanslational EIT developmeNt stuDy
(TREND) group. The group was formed at the
meeting ‘ Chest EIT: Status, Vision and Priorities’
(Manchester, UK, 16–17 November 2012), at
which leaders of all clinically oriented EIT research
groups from North and South America, Europe,
Asia and Australia and a representative from each
company producing EIT technology were repre-
sented. The TREND group consists of pre-eminent
researchers and clinical leaders spanning neonatal,
paediatric and adult fields of chest EIT. Meetings of
this group take place at the annual EIT conferences
and congresses of the American Thoracic Society
and the European Respiratory Society.
One key concern of the TREND group that
resulted in the preparation of this paper was the
lack of recommendations for chest EIT examina-
tions, consistent terminology and generally accepted
approaches to EIT image analysis and interpretation.
The structure of this paper differs from former,
rather descriptive reviews.
2–11
It is based on five
core processes that we identified during EITexamin-
ation and data analysis (
figure 1). These processes
involve: (1) execution of EIT measurements, (2)
generation of raw EIT images, (3) EIT waveforms
and regions-of-interest (ROI), (4) functional EIT
images and (5) EIT measures. They are con-
secutively addressed in the first five sections of the
paper. Each section is accompanied by an electronic
online supplement (EOS) with detailed figures,
definitions, recommendations and examples. A
separate online supplement with the definitions of
EIT-related terms is provided.
The last part of the article focuses on the clinical
use of EIT in adult, neonatal and paediatric
patients. The major target populations are mechan-
ically ventilated patients, typically requiring inten-
sive care therapy, and pulmonology patients
suffering from chronic lung diseases. Two supple-
ments linked to these clinical sections provide sum-
maries and lists of clinical issues benefiting from
EIT-guided clinical decisions. Finally, we propose
Frerichs I, et al. Thorax 2017;72:83–93. doi:10.1136/thoraxjnl-2016-208357 83
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recommendations for the future research and development of
EIT presented in detail in the last EOS. All nine online supple-
ments contain comprehensive lists of references.
Our paper is the result of a joint effort of EIT experts
based on extensive literature search and, their expertise and
experience with this medical technology. It is neither a health
technology assessment nor a conventional systematic review.
Nonetheless, we believe that it will become a reference
document that reviews main achievements and outlines recom-
mendations for clinical use, describes how errors and misinter-
pretations in EIT data acquisition and analysis can be avoided
and facilitates sharing and comparison of research and clinical
results.
We expect our consensus document to be relevant to current
clinical users of EIT (adult and neonatal/paediatric intensivists),
potential new users (adult and paediatric pneumologists) and
producers of EIT technology.
EXECUTION OF EIT CHEST MEASUREMENTS
EIT examinations require the placement of electrodes on the
chest circumference, positioned to be sensitive to the phenom-
ena of interest. Electrodes are either placed individually with
equal spacing or are integrated into electrode belts or stripes,
which render the application user-friendly. Several EIT devices
use 16 electrodes, although systems with a higher and lower
number of electrodes have also been developed. The electrodes
are typically placed in one transverse plane, although oblique
placement has also been described. Large chest wounds, mul-
tiple chest tubes, non-conductive bandages or conductive wire
sutures may preclude or affect the measurements.
The location of the electrode plane impacts the findings;
12–15
thus, comparability of examinations performed on separate occa-
sions requires electrode locations to be the same. It is not
recommended to place the electrodes lower than the sixth inter-
costal space because the diaphragm may periodically enter the
measurement plane.
13
Posture
14 16–19
and type of ventilation
20–25
affect the findings. Specific ventilation manoeuvres, mechanical
ventilation mode and settings, etc should be recorded to ease the
interpretation of EIT findings.
During an EIT examination, very small alternating electrical
currents are applied through pairs of electrodes while the result-
ing voltages are measured on the remaining electrodes. The
most widespread spatial pattern of current applications and
voltage measurements is through adjacent electrode pairs. Other
patterns of current applications and voltage measurements are
increasingly used and can be expected to replace the adjacent
pattern because they offer technical advantages. Further infor-
mation on the execution of EIT measurements is provided in
EOS 1.
RAW EIT IMAGES
The set of EIT data acquired during one cycle of current appli-
cations and voltage measurements is typically called frame. One
EIT data frame contains the information necessary to generate
one raw image. The number of frames (or raw images) acquired
per second corresponds with the EIT scan rate. Current EIT
devices offer maximum scan rates of about 50 images/s allowing
the assessment of lung function under dynamic conditions.
EIT is sensitive to periodic and non-periodic changes in elec-
trical tissue conductivity in a slice with a vertical thickness
roughly half the chest width.
26
An increase in intrapulmonary
gas volume decreases conductivity, while increased blood or
fluid volume or disruption of cellular barriers raise it.
Image reconstruction is the process of generating raw EIT
images from the measured voltages, typically of a two-
dimensional slice through the electrode plane.
27
Time-difference
Figure 1 Schematic presentation of
the chest EIT examination and data
analysis. The drawings, examples of
EIT images and EIT measures illustrate
the different steps involved. The
images were generated using the
GREIT image reconstruction algorithm
from data acquired in a healthy adult
subject with the Goe-MF II EIT device
(CareFusion, Höchberg, Germany).
(These images as well as the data
shown in subsequent figures originate
from examinations approved by the
institutional ethics committees and
acquired with written informed
consent.) ARDS, acute respiratory
distress syndrome; EIT, electrical
impedance tomography; rel. ΔZ,
relative impedance change; GI, global
inhomogeneity index; CoV, centre of
ventilation; PEEP, positive end-
expiratory pressure; ROP, regional
opening pressure; RVD, regional
ventilation delay.
84 Frerichs I, et al. Thorax 2017;72:83–93. doi:10.1136/thoraxjnl-2016-208357
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EIT image reconstruction calculates images of the change in
tissue properties between a baseline (reference) measurement
frame and the current frame. Time-difference imaging is well
suited to trace time-varying physiological phenomena like lung
ventilation and perfusion. Two other imaging modalities are
active areas of research, but currently insufficiently robust for
chest EIT: (1) frequency-difference imaging, sensitive to the dif-
ference in tissue properties between two stimulation frequencies
at a given time and (2) absolute imaging, which calculates
images of the properties at a given time (ie, not just relative
impedance changes).
An ideal reconstruction algorithm should guarantee uniform
amplitude response, small and uniform position error, small
ringing artefacts, uniform resolution, limited shape deformation,
high resolution and exhibit small sensitivity to electrode and
boundary movement.
28
The images are either round or, in
newer algorithms, their contour reflects the anatomical form of
the chest. Development of new algorithms is an active field in
EIT research with advances in image quality achieved by using,
for example, a priori anatomical information.
The orientation of EIT images is identical to the images gen-
erated by established imaging modalities like CT with the right
chest side on the left side of the image and with anterior at the
top. The colour coding of EIT images depends on the choice of
the baseline frame and is not unified (for examples, see EOS 2).
EIT WAVEFORMS AND ROI
EIT data analysis is based on the EIT waveforms that are gener-
ated from a series of raw EIT images in individual image pixels.
ROI can be defined in an image (minimum size being one image
pixel). In each ROI, the waveform over time displays the short-
term and long-term changes in local electrical impedance result-
ing from various physiological or pathological effects. Periodic
signal fluctuations are induced by ventilation or by heart action
and lung perfusion (
figure 2). Digital frequency filtering is often
used in EIT data analysis to isolate these periodic phenomena. A
non-periodic change may be caused, for example, by an overall
increase in gas volume induced by raising the positive
end-expiratory pressure (PEEP) during mechanical ventila-
tion.
29–31
The magnitude of the impedance changes associated with
spontaneous breathing or mechanical ventilation is approxi-
mately one order of magnitude larger than the changes induced
by heart action and lung perfusion.
32
Besides physiological and
pathological effects, EIT waveforms may also display artefacts
originating from, for example, body movement
33
or interference
with some medical devices.
34
Modern EIT devices have some-
what improved robustness to interference. The artefacts can
often be eliminated by adapting the EIT data acquisition para-
meters or by signal postprocessing.
EIT images show not only the lungs but the whole chest
cross-section. To increase the sensitivity of EIT data analysis,
ideally only waveforms originating from lung regions should be
analysed. The border between the pulmonary and non-
pulmonary tissue is blurred in EIT images. Therefore, several
approaches have been proposed to determine ROIs representing
the lungs.
35 36
EIT lung ROIs are mostly functionally identified as regions
where ventilation-related impedance changes occur. If this
approach is applied, lung regions with absent or small
Figure 2 Electrical impedance tomography (EIT) waveforms simultaneously registered in one image pixel in the dorsal region of the dependent
(left) and in another pixel in the dorsal region of the non-dependent lungs (right) in a healthy man aged 43 years lying on his right side. The raw
data were obtained using the Goe-MF II EIT device (CareFusion, Höchberg, Germany) and reconstructed with the GREIT algorithm. During the first
30 s, the subject was breathing quietly, then he was instructed to hold his breath for 20 s after tidal inspiration, finally he took three deep breaths.
The periodic ventilation-related changes of the EIT signal, given as relative impedance change (rel. ΔZ), are higher than those associated with the
cardiac action. (The latter are best discernible during the apnoea phase.) The tidal changes in rel. ΔZ during the first and the third phases of this
measurement are higher in the dependent than in the non-dependent lung reflecting the physiologically known higher ventilation of the dependent
lung regions in adult subjects spontaneously breathing at the functional residual capacity level. During the apnoeic phase, the EIT signal falls
continuously in the dependent lung due to local gas volume loss caused by the continuing gas exchange. This is not observed in the non-dependent
lung. The changes in rel. ΔZ synchronous with the heartbeat are of comparable amplitude in both pixels. The breathing rate (BR) and heart rate (HR)
in each of the three examination phases given in the lower part of the figure were derived from frequency filtering of the EIT signal.
Frerichs I, et al. Thorax 2017;72:83–93. doi:10.1136/thoraxjnl-2016-208357 85
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ventilation-related impedance changes (eg, atelectasis, pleural
effusion or pneumothorax) may be missed. If unaccounted for,
this may impact subsequent analyses, for example, by showing
less ventilation heterogeneity, than present.
The other motivation for ROI-based analysis of EIT data is to
characterise the spatial heterogeneity of lung ventilation. For
this application, arbitrary ROIs, like image quadrants or layers
are used.
24 37–39
These are either applied to the whole image or
are combined with a previously defined lung ROI. Further
details can be found in EOS 3.
FUNCTIONAL EIT IMAGES
Functional EIT images are generated from series of raw images
and the corresponding pixel EIT waveforms, by use of appropri-
ate mathematical equations in each image pixel. All calculated
values are then plotted (or image colour-coded) in the respective
pixels. Various functional EIT measures have been proposed and
used to quantify and characterise regional lung ventilation (and
perfusion). These are briefly addressed here but described in
detail in
EOS 4.
Today’s high EIT scan rates allow precise identification of the
tidal peak-to-trough changes in the pixel EIT waveforms and
generation of functional EIT images proportional to the local
tidal volume (V
T
).
25 37 40 41
Identification of pixel
end-expiratory minima before and after a change in ventilator
settings (eg, in PEEP) creates a functional EIT image of the local
changes in end-expiratory lung volume (EELV).
29
If EIT data are
acquired during the forced full expiration then the calculation of
the electrical impedance change within the first second of the
forced exhalation will image the distribution of local FEV
1
.
42
The analysis of the dynamic characteristics of pixel EIT wave-
forms enables the assessment of the non-linearity of local filling
and emptying of the lungs and creation of functional EIT
images showing the spatial distribution of this non-linear behav-
iour.
43
If EIT examination is performed during a stepwise infla-
tion or deflation of the lungs then fitting of mathematical
functions to pixel EIT waveforms may be used to calculate and
image local respiratory time constants.
44
Combination of pixel EIT waveforms with other simultan-
eously registered signals like the airway pressure allows the gen-
eration of pixel pressure-volume curves
45 46
and generation of
functional images showing, for example, regional lung opening
and closing
47
or regional respiratory system compliance (C
rs
).
48
Several types of functional images can be generated from a
single EIT measurement. They address different aspects of
regional lung function, thus, the combination of these findings
allows a more thorough interpretation of EIT data.
EIT MEASURES
Functional EIT images display the calculated functional measures
with the highest spatial resolution available. Based on these
images, it is desirable to create quantifiable clinically relevant
measures to assess the present state of ventilation distribution
and its trends. Images and numeric values are complementary.
Quantitative EIT measures can be divided into three groups.
The first group has the same functional measures as the ones
used to generate functional EIT images, only the pixel values of
these measures are averaged (or summed) across the whole
image or its sections. For instance, the sum of tidal impedance
changes in all image pixels provides an estimate of regional V
T
in the studied chest slice.
The second group aims at characterising the spatial distribu-
tion of ventilation. One subgroup describes the overall degree of
spatial heterogeneity of ventilation. Examples are the global
inhomogeneity index
36 40 49
or the coefficient of vari-
ation,
36 42 50
calculated from the maps of tidal impedance vari-
ation. Another subgroup describes the orientation of the spatial
distribution of functional measures, usually in the anteroposter-
ior direction. This direction is clinically relevant when patients
are examined in the supine position, where it corresponds to
the gravity vector. The simplest measure is the anteroposterior
(upper-to-lower) ventilation ratio, calculated as the ratio
between the sum of tidal impedance changes in the anterior and
posterior halves of the functional image or the lung ROI within
it.
51
Alternatively, the anterior and posterior fractions (percen-
tages) of ventilation are calculated.
24
Fractions of ventilation can
also be computed in larger number of smaller ROIs spanning
the whole image in the anteroposterior direction and used to
create ventilation profiles.
37 52 53
The centre of ventilation,
frequently used to describe the ventilation distribution with
relation to the chest diameter, is derived from such
profiles.
20 37 53 54
The third group includes examination-specific measures.
Examples are measures of perfusion via an infusion of
conductivity-contrasting bolus,
55
or measures that are derived
from the EIT data registered in parallel with other signals,
mostly airway pressure. Such measures aim at characterising
regional C
rs
under quasistatic
45 56
but mostly dynamic condi-
tions.
57 58
The high scan rates allow the assessment of intratidal
changes in regional C
rs.
38
Another EIT measure of respiratory
mechanics is the regional respiratory time constant.
44 59
Temporal heterogeneity of ventilation can be characterised by
calculating the phase shifts in regional ventilation
60
or ventila-
tion delay index.
61
Regional expiration times needed to exhale
specified percentages of regional gas volumes can also be
derived from EIT waveforms.
42 62 63
Further details on EIT
measures are presented in EOS 5.
The taxonomy of EIT terms with clinical user-friendly defini-
tions and explanations is provided in EOS 6.
CLINICAL USE OF EIT IN ADULT PAT IENTS
Three general uses of thoracic EIT have been promising in adult
patients: (a) monitoring of mechanical ventilation, (b) monitor-
ing of heart activity and lung perfusion and (c) pulmonary func-
tion testing. The validity and reproducibility of EIT findings is
derived from several experimental and clinical studies compar-
ing EIT with reference techniques like CT,
61 64–66
single-photon
emission CT,
67
positron emission tomography,
68
vibration
response imaging,
69
inert-gas washout
70
and spirometry.
14 30 71
EIT examinations over time often provide unique clinical
information difficult to obtain by other technologies at the
bedside. With almost no side effects, EIT allows the sensitive
and prompt assessment of lung characteristics over the course of
disease and treatment.
Monitoring of mechanical ventilation
The need for monitoring regional effects of mechanical ventila-
tion is based on our understanding of the direct damage
inflicted by the ventilator on the fragile lung. Protective ventila-
tion has been increasingly demanded inside and outside inten-
sive care units to prevent/minimise ventilator-associated lung
injury. Global measures of oxygenation or respiratory system
mechanics, traditionally used as references to adjust mechanical
ventilation, may produce misleading information by ‘averaging’
opposite pathological phenomena (eg, tidal recruitment and
overdistension) in different lung units. This underlines the need
for regional functional lung monitoring.
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