Electrical Impedance Tomography for Cardio-Pulmonary Monitoring

Abstract

Electrical Impedance Tomography (EIT) is a bedside monitor that does not require any surgery to see the local airflow and even lung perfusion. The paper summarizes and analyzes the methodological and clinical aspects of the thoracic EIT. Initially, investigators addressed the validity of EIT to measure regional ventilation. Research is currently focused on its clinical applications to determine the extent of lung collapse, tidal recruitment, and lung overdistension to measure positive end-expiratory pressure (PEEP) and the volume of tidal. In addition, EIT may help to detect pneumothorax. Recent studies assessed EIT as a method to measure lung perfusion in the region. Indicator-free EIT tests could be enough to continuously monitor cardiac stroke volume. A contrast agent like saline could be necessary to evaluate regional lung perfusion. As a result, EIT-based monitoring of respiratory ventilation and lung perfusion may visualize local perfusion and oxygenation which could be beneficial in treating patients with acute respiratory distress syndrome (ARDS).

Keywords: Electrical impedance tomography bioimpedance; image reconstruction; thorax; regional ventilation and regional perfusion monitoring.

1. Introduction

Electric impedance tomography (EIT) is one of the radiation-free functional imaging technique that permits non-invasive bedside monitoring of regional lung ventilation and , possibly perfusion. Commercially accessible EIT devices were introduced to allow clinical applications of this method, and thoracic EIT is used in a safe manner in both adult and pediatric patients [ 1., ].

2. Basics of Impedance Spectroscopy

Impedance Spectroscopy is the voltage response of biological tissue to externally applied alternating electronic current (AC). It is normally measured using four electrodes, of which two are utilized for AC injection and the other two electrodes are used to measure voltage 3.,]. Thoracic EIT measures the regional distribution of intra-thoracic Impedance Spectroscopyand could be seen by extending the four electrode principle to the image plane spanned by the electrode belt 11. In terms of dimensions, electrical impedance (Z) is the same as resistance , and the related International System of Units (SI) unit is Ohm (O). It can be described in a complex form, where the real part is resistance, while the imaginary portion is called reaction, which determines the effect of resistance or capacitance. The amount of capacitance is determined by biomembranes’ properties of the tissue such as ion channels and fatty acids as well as gap junctions, whereas resistance is determined by the nature and amount of extracellular fluid [ 1., 2]. At frequencies less than 5 Kilohertz (kHz) that is, electrical energy is carried by extracellular fluid and is primarily dependent on its resistive properties of tissues. In higher frequencies above 50 kHz, electrical impulses are slightly redirected at cell membranes , which results in an increase in tissue capacitive properties. For frequencies higher than 100 kHz electrical current can flow through cell membranes, and diminish the capacitive component [ 22. Therefore, the effects that determine the amount of tissue impedance depend on the utilized stimulation frequency. Impedance Spectroscopy typically refers to conductivity and resistivity. They will normalize conductance or resistance in relation to the area of the unit and the length. The SI equivalent units consist of Ohm-meter (O*m) for resistivity and Siemens per meters (S/m) to measure conductivity. The resistance of thoracic tissue varies between 150 O*cm for blood and 700 O*cm in lung tissue that has been deflated, and up to 2400 o*cm for an inflated lung tissue ( Table 1). In general, the tissue’s resistance or conductivity will vary based on levels of ion and fluid content. Regarding the lung, it also is dependent on the quantity of air inside the alveoli. While most tissues exhibit isotropic behavior, the heart as well as muscle fibers in the skeletal system exhibit anisotropic behavior, meaning that resistivity strongly depends on the direction that it is measured.

Table 1. Electrical resistivity of thoracic tissues.

3. EIT Measurements and Image Reconstruction

For EIT measurements, electrodes are placed around the chest in a transverse plane that is usually located in the 4th-5th intercostal space (ICS) near Parasternal Line [5]. As a result, changes in the impedance of the lungs can be measured within the lower lobes of the left and right lungs as well as in the heart area ,2[ 1,2]. To place the electrodes below the 6th ICS might be challenging as the abdominal contents and diaphragm are frequently inserted into the measurement plane.

Electrodes are either single self-adhesive electrodes (e.g., electrocardiogram ECG,) which are placed with equal spacing in-between the electrodes or are integrated in electrode belts ,22. Additionally, self-adhesive stripe are accessible for a more convenient application ,2[ 1,2]. Chest tubes, chest wounds, non-conductive bandages or conductive wire sutures can hinder or greatly affect EIT measurements. Commercially available EIT devices typically use 16 electrodes, but EIT systems with eight (or 32) electrodes are available (please consult Table 2 for information) It is recommended to consult Table 2 for more details. ,2[ 1,2].

Table 2. Electrical impedance devices that are commercially accessible. tomography (EIT) instruments.

During an EIT measurement sequence, small AC (e.g. the smallest value of 5 microamps at 100 kHz) are applied to several electrodes, and the output voltages are analyzed using the remaining other electrodes [ 6. Bioelectrical impedance that is measured between the injecting and measuring electrode pairs is calculated based on the applied current as well as the measured voltages. Most commonly nearby electrode pairs are used for AC application in a 16-elektrode set-up for example, while 32-elektrode systems generally employ a skip pattern (see Table 2) to increase the distance between the electrodes for current injection. The resultant voltages are measured with those remaining electrodes. Currently, there is a constant debate regarding different methods of stimulation as well as their advantages and disadvantages [7]. In order to obtain an complete EIT data set of bioelectrical measurements The injecting and electrodes that measure are constantly turned around the entire thorax .

1. Measurements of voltage and current within the thorax, using an EIT system that has 16 electrodes. Within a few milliseconds, each of the electrodes for current as well as activated voltage electrodes are repeatedly rotated around the thorax.

The AC used during the EIT tests are safe to apply to the body and remains undetected by the patient. For safety reasons, the use of EIT in patients with electrically active devices (e.g., cardiac pacemakers or cardioverter-defibrillators) is not recommended.

A EIT data set which is recorded in one cycle within AC apps is termed a frame . It is comprised of the voltage measurements that create an Raw EIT image. The term frame rate reflects the number of EIT frames that are recorded every second. Frame rates at least 10 images/s are necessary for monitoring ventilation and 25 images/s in order to monitor perfusion or cardiac function. Commercially accessible EIT devices have frame rates ranging from 40 to 50 images/s [2], as described in

To generate EIT images from the recorded frames, the so-called reconstructing of images is carried out. Reconstruction algorithms strive to resolve the problem that is the reverse of EIT, which is the restoration of the conductivity pattern in the thorax using the voltage measurements that have been acquired at the electrodes on the thorax surface. Initially, EIT reconstruction assumed that electrodes were placed on an ellipsoid, circular or circular plane, while newer algorithms make use of information regarding anatomy of the thorax. In the present, there are three main algorithms used for EIT: the Sheffield back-projection algorithm as well as the finite-element method (FEM) based linearized Newton-Raphson algorithm [ ], and the Graz consensus reconstruction algorithm for EIT (GREIT) [10] are frequently used.

It is generally true that EIT image are basically similar to a two-dimensional computed-tomography (CT) image: these images are usually rendered so that the user looks from cranial towards caudal when taking a look at the picture. Contrary to an CT image however, an EIT image doesn’t show an image “slice” but an “EIT sensitivity region” [11]. The EIT sensitive region is a lens-shaped intrathoracic space that is the source of impedance variations which contribute to the EIT image generation [1111. The dimensions and shape of the EIT area of sensitivity are dependent upon the dimensions, bioelectrical properties, and also the structure of the chest with the type of current injection and voltage measurement pattern [12].

Time-difference image is a technique that is used in EIT reconstruction to show the changes in conductivity and not the actual conductivity level. Time-difference EIT image compares changes in impedance to a base frame. It is an opportunity to observe time-dependent physiological processes such as lung respiration and perfusion [22. Color coding of EIT images isn’t unified but generally displays the change in intensity to a baseline level (2). EIT images are generally coded using a rainbow-colored scheme with red representing the most significant absolute impedance (e.g. during inspiration) as well as green, which is a medium relative impedance, and blue the lowest impedance (e.g. during expiration). In clinical settings it is possible to use color-scales that range from black (no change in impedance) or blue (intermediate impedance change), and white (strong impedance shift) to code ventilation or from black, to white and then red for mirror perfusion.

2. There are a variety of color codes available for EIT images when compared with the CT scan. The rainbow-color scheme is based on red for the greatest value of impedance relative (e.g., during inspiration) as well as green for a low relative impedance and blue when the relative resistance is lowest (e.g. at expiration). A newer color scales use instead of black for no impedance changes) and blue for an intermediate impedance shift, and white for the strongest impedance changes.

4. Functional Imaging and EIT Waveform Analysis

Analyzing Impedance Analyzers data is done using EIT waveforms which are created in the individual pixels of a series of raw EIT images over the course of time (Figure 3.). An area of concern (ROI) is a term used as a summary of activity in specific pixels of the image. In each ROI, the waveform displays fluctuations in regional conductivity in time , resulting from ventilatory activity (ventilation-related signal, also known as VRS) and cardiac activities (cardiac-related signal CRS). Furthermore, electrically conductive contrast agents such as hypertonic Saline can be utilized to create an EIT pattern (indicator-based signal, IBS) and can be linked to the perfusion of the lung. The CRS can originate from both the lung and the cardiac region and may also be attributed to lung perfusion. The exact cause and the composition aren’t understood completely 13]. Frequency Spectrum Analysis is typically employed to distinguish between ventilationas well as cardiac-related changes in impedance. Impedance changes outside of the periodic cycle could be caused by changes in settings for the ventilator.

Figure 3. EIT forms and the functions of EIT (fEIT) photographs originate from the initial EIT images. EIT waveforms are defined in a pixel-wise manner or based on a specific region in interest (ROI). Conductivity variations are caused by ventilatory (VRS) and cardiac activities (CRS) but may also be induced artificially, e.g. using injection of bolus (IBS) to determine perfusion. fEIT images display some of the regional physiological parameters, such as perfusion (Q) and ventilation (V) or perfusion (Q) that are extracted from the raw EIT images using an algorithmic process over time.

Functional EIT (fEIT) images are produced by applying a mathematical calculation on the sequence of raw images along with the associated pixel EIT spectrums. Since the mathematical procedure is applied to calculate the physiologically relevant parameters for each pixel, physiological regional characteristics like regional ventilation (V) and respiratory system compliance, as well as regions perfusion (Q) can be assessed and visualized (Figure 3.). The information derived from EIT waveforms , as well as concurrently registered airway pressure values can be used to determine the lung’s compliance and lung closing and opening for each pixel by calculating changes of pressure and impedance (volume). Comparable EIT measurements during stepwise inflation and deflation of lung volumes allow for the display of pressure-volume curves on the pixel level. Depending on the mathematical method used, different types of fEIT scans could reflect different functional characteristics of the cardio-pulmonary system.