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Electrical Impedance Tomography for Cardio-Pulmonary Monitoring

Abstract

Electrical Impedance Tomography (EIT) is an instrument that monitors the bedside and provides non-invasive visualisation of local ventilation and possibly lung perfusion distribution. The paper summarizes and discusses the methodological and clinical aspects of the thoracic EIT. Initially, researchers focused on the validity of EIT to determine regional ventilation. The current research focuses on clinical applications of EIT to measure lung collapse Tidal Recruitment, and lung overdistension. This allows for the titration of positive end-expir pressure (PEEP) and Tidal volume. In addition, EIT may help to detect pneumothorax. Recent studies evaluated EIT as a means to gauge regional lung perfusion. Indicate-free EIT measurements might be sufficient for continuous measurement of cardiac stroke volume. The use of a contrast agent such as saline could be necessary to check regional lung perfusion. This is why EIT-based monitoring of regional ventilation as well as lung perfusion can be used to assess local ventilation and perfusion matching, which can be helpful in treating patients with chronic respiratory distress syndrome (ARDS).

Keywords: electrical impedance imaging Bioimpedance; image reconstruction Thorax; regional adrenergic, regional perfusion; monitoring

1. Introduction

Electric impedance tomography (EIT) can be described as a non-radiation functional imaging modality that permits non-invasive monitoring of bedside regional lung ventilatory and perhaps perfusion. Commercially accessible EIT devices were introduced for the clinical use of this technique, and thoracic EIT is safe in both adult and pediatric patients 1., 2.

2. Basics of Impedance Spectroscopy

Impedance Spectroscopy is the variation in the voltage of biological tissue to externally applied alternating electronic current (AC). It is usually measured with four electrodes. Two are used for AC injection, and the remaining two for voltage measurement [ 3.,4. Thoracic EIT measures the regional distribution of intra-thoracic Impedance Spectroscopyand is seen in the same way as applying the principle of four electrodes onto the image plane which is defined by the electrode belt [ 11. Dimensionally, electrical resistance (Z) is identical to resistance and the corresponding International System of Units (SI) unit is Ohm (O). It can be described as a complicated number, in which it is the actual portion of resistance, while the imaginary portion is called reactance. This determines the effect of capacitors or the effect of inductance. The amount of capacitance is determined by biomembranes’ specifics of the tissue , which includes ion channels, fatty acids, and gap junctions. The resistance is mostly determined by composition and quantity of extracellular fluid [ 1., 2]. In frequencies that are less than 5 kilohertz (kHz) electricity circulates through extracellular fluids and is predominantly dependent on the resistance characteristics of tissues. At higher frequencies of up to 50 kHz, electrical currents can be slightly deflected through cell membranes , leading to an increase in the tissue’s capacitive properties. For frequencies higher than 100 kHz electrical current can flow through cell membranes and reduce the capacitive component [ 21. Therefore, the effects that determine the impedance of tissue depend on the stimulation frequency. Impedance Spectroscopy is usually given as conductivity or resistivity, which is a measure of conductance or resistance to unit size and length. The corresponding SI units consist of Ohm-meter (O*m) for resistivity and Siemens per meter (S/m) to measure conductivity. The thoracic tissue’s resistance ranges between 150 O*cm for blood as high as 700 O*cm with air-filled lung tissue, and up to 2400 o*cm for inflated lung tissue ( Table 1). In general, the tissue’s resistance or conductivity is dependent on amount of fluid and the ion concentration. In the case of the lungs, it depends on the amount of air inside the alveoli. While the majority of tissues exhibit isotropic behavior, heart and muscle skeleton exhibit anisotropy, this means that resistivity is heavily dependent on the direction that you measure it.

Table 1. The electrical resistance of the thoracic tissue.

3. EIT Measurements and Image Reconstruction

In order to perform EIT measurements electrodes are set around the Thorax in a horizontal plane which is typically located in the 4th to 5th intercostal areas (ICS) near just below the parasternal line5. In turn, the variations in the impedance of the lungs can be measured within those lobes that are lower in the right and left lungs, as well as in the heart area ,22. The placement of the electrodes below the 6th ICS might be difficult as the abdominal and diaphragm regularly enter the measurement plan.

Electrodes can be self-adhesive or single electrodes (e.g. electrocardiogram ECG) that are placed individually with equal spacing in-between the electrodes or are integrated in electrode belts [ ,2(1). Also, self-adhesive stripes are readily available for a user-friendly application [ ,2[ 1,2]. Chest wounds, chest tubes bandsages that are not conductive or wire sutures can hinder or severely affect EIT measurements. Commercially available EIT devices typically utilize 16 electrodes. However, EIT systems with 8 (or 32) electrodes are also available (please consult Table 2 for details) For more information, refer to Table 2. ,2[ 1,2.

Table 2. Electronic impedance tomography (EIT) instruments.

During an EIT measuring sequence, very small AC (e.g. approximately 5 1 mA at 100 kHz) are applied through different electrode pairs and the output voltages are analyzed using the remaining other electrodes [ ]. Bioelectrical impedance between the injecting and the electrodes that are measuring can be calculated by using the applied current and the measured voltages. The majority of the time connected electrode pairs are used for AC application in a 16-elektrode set-up as opposed to 32-elektrode systems, which typically employ a skip pattern (see the table 2.) to increase the distance between electrodes that inject current. The resulting voltages are measured using one of the other electrodes. Presently, there’s an ongoing discussion about different electrical stimulation techniques and their unique advantages and disadvantages [7]. For a complete EIT data set of bioelectrical tests as well as the injecting and electrode pairs that measure are continually rotating around the entire thorax .

1. Measurements of voltage and current around the thorax utilizing an EIT system featuring 16 electrodes. In just a few milliseconds as well as the voltage and current electrodes and these active electrodes are moved within the thorax.

The AC utilized during EIT measurements are safe to apply to the body and will not be detected by the individual patient. For safety reasons, the use of EIT in patients with electrically active devices (e.g., cardiac pacemakers or cardioverter-defibrillators) is not recommended.

The EIT data set captured during a single cycle during AC application is called frames and includes the voltage measurements to generate EIT’s unprocessed EIT image. The term “frame rate” refers to the number of EIT frames recorded each second. Frame rates of no less than 10 images/s are required to monitor ventilation and 25 images/s are required to monitor cardiac function or perfusion. Commercially accessible EIT devices have frame rates of 40 to 50 images/s as described in

To generate EIT images using the recorded frames, the process of image reconstruction procedure is utilized. Reconstruction algorithms seek to solve the inverse problem of EIT which is the restoration of the conductivity pattern within the thorax based upon the voltage measurements that have been acquired at the electrodes on the thorax’s surface. At first, EIT reconstruction assumed that electrodes were placed in an ellipsoid or circular plane, while newer algorithms incorporate information about how the anatomical shape of thorax. Presently, there is it is the Sheffield back-projection algorithm [ and the finite element algorithm (FEM) with a linearized Newton–Raphson algorithm ], and the Graz consensus reconstruction algorithm for EIT (GREIT) [10] are frequently used.

In general, EIT images can be compared to a computed two-dimensional (CT) image: these images are usually rendered so that the operator looks from caudal to cranial when reviewing the image. Contrary to a CT image, an EIT image does not show the appearance of a “slice” but an “EIT sensitivity region” [1111. The EIT sensitivity region is a lens-shaped intrathoracic space and is where the impedance change contributes to EIT picture generationThe EIT image is generated by impedance changes. The size and shape of the EIT sensitization region is determined by the dimensions, the bioelectrical properties, and also the shape of the thorax as depending on the current injection and voltage measurement pattern [12].

Time-difference imaging is a technique that is employed in EIT reconstruction to show the changes in conductivity and not the absolute conductivity levels. An time-difference EIT image displays the change in impedance to a baseline frame. This allows you to observe time-dependent physiological processes like lung ventilation or perfusion [22. Color-coding for EIT images isn’t unified however, it typically displays the change in impedance to an appropriate level (2). EIT images are generally encoded with a rainbow-color scheme with red representing the highest value of relative imperf (e.g. during inspiration) and green for a middle relative impedance, and blue being the lowest relative impedance (e.g. when expiration is in progress). For clinical purposes, an interesting option is to employ color scales that vary from black (no impedance change) through blue (intermediate impedance change) as well as white (strong impedance shift) to code ventilation or from black, to white and red towards mirror perfusion.

2. Different color codings for EIT images when compared with the CT scan. The rainbow-color scheme employs red for the highest percentage of the relative imperceptibility (e.g., during inspiration) as well as green for a medium relative impedance, and blue to indicate the least relative imperceptibility (e.g. when expiration is in progress). A newer color scales use instead of black to avoid any impedance changes) or blue to indicate the intermediate impedance change and white for the largest impedance shift.

4. Functional Imaging and EIT Waveform Analysis

Analyzing Impedance Analyzers data is done using EIT waves that are generated within individual image pixels of the form of a sequence of raw EIT images over long periods of (Figure 3). The term “region of interest” (ROI) can be defined to represent activity within individual pixels of the image. In the ROIs, each waveform displays variations in the conductivity of the region over time as a result of ventilatory activity (ventilation-related signal, VRS) and cardiac activities (cardiac-related signal CRS). In addition, electrically conductive contrast agents such as hypertonic salinity can be used to produce an EIT waveform (indicator-based signal IBS) and can be linked to lung perfusion. The CRS could originate from both the lungs and the cardiac region, and could be partially related to lung perfusion. The exact source and composition is not fully understood 1313. Frequency Spectrum Analysis is typically used to discriminate between ventilationand cardiac-related impedance fluctuations. Impedance changes that are not periodic could be caused by modifications in the settings of the ventilator.

Figure 3. EIT Waveforms as well as functional EIT (fEIT) Images are extracted from initial EIT images. EIT waves can be defined pixels-wise or based on a area to be studied (ROI). Conductivity changes occur naturally as a result of breathing (VRS) (or cardiac activity (CRS) but may also be generated artificially e.g. using IBS (IBS) for perfusion measurement. FEIT images depict specific physiological parameters of the region such as ventilation (V) as well as perfusion (Q) that are extracted from the raw EIT images by using an algorithmic process over time.

Functional EIT (fEIT) images are produced through the application of a mathematical algorithm on an array of raw images and the corresponding EIT Waveforms. Since the mathematical procedure is used to determine an appropriate physiological parameter for each pixel. The regional physiological features like regional ventilation (V), respiratory system compliance, as along with regions perfusion (Q) can be assessed and displayed (Figure 3.). The data drawn from EIT waves and simultaneously registered airway pressure measurements can be utilized to determine the lung’s compliance and the rate of lung opening and closing at each pixel, using variations of pressure and impedance (volume). Comparable EIT measurements taken during the deflation and inflation of the lungs permit the display of pressure-volume curves on an individual pixel. Based on the mathematical operation, different kinds of fEIT images might address distinct functional characteristics for the cardio-pulmonary system.

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