The ACE1 Electrical Impedance Tomography System for Thoracic Imaging

Simultaneous Acquisition of EIT and ECG Signals on Active EIT Electrodes

OBJECTIVE

This paper introduces a new method of simultaneous acquisition of electrocardiogram (ECG) signals and electrical impedance tomography (EIT) measurements on active electrodes, i.e. electrodes that are applying current, in an EIT system.

METHODS

Howland noise reduction followed by an integrate-and-dump filter and adaptive filtering are used to extract the ECG signal without loss of amplitude.

RESULTS

Results of simultaneous ECG signals and EIT reconstructions on human subjects are shown. It is also demonstrated that the recovered ECG waveforms from 32 electrodes can be used to reconstruct the heart current source vectors during a cardiac cycle, yielding an approximate solution to the inverse problem of electrocardiography.

SIGNIFICANCE

Acquiring ECG signals from all electrodes attached to the body simultaneously with EIT data acquisition eliminates the need for a separate system to collect ECG signals. Time-aligned ECG signals are helpful in interpreting pulsatile perfusion images by providing exact timing of each image in relation to the cardiac cycle. Additionally, collecting ECG signals from many or all of the EIT electrodes enables reconstruction of the heart's moving dipole moment at the same time as the EIT images.

Flexi-EIT: A Flexible and Reconfigurable Active Electrode Electrical Impedance Tomography System

Electrical Impedance Tomography (EIT) systems have shown great promise in many fields such as real-time wearable healthcare imaging, but their fixed number of electrodes and placement locations limit the system's flexibility and adaptability for further advancement. In this article, we propose a flexible and reconfigurable EIT system (Flexi-EIT) based on digital active electrode (DAE) architecture to address these limitations. By integrating a reconfigurable number of up to 32 replaceable DAEs into the flexible printed circuit (FPC) based wearable electrode belt, we can enable rapid, reliable, and easy placement while maintaining high device flexibility and reliability. We also explore hardware-software co-optimization image reconstruction solutions to balance the size and accuracy of the model, the power consumption, and the real-time latency. Each DAE is designed using commercial chips and fabricated on a printed circuit board (PCB) measuring 13.1 mm × 24.4 mm and weighing 2 grams. In current excitation mode, it can provide programmable sinusoidal current signal output with frequencies up to 100 kHz and amplitudes up to 1 mA p-p that meets IEC 60601-1 standard. In voltage acquisition mode, it can pre-amplify, filter, and digitize the external response voltage signal, improving the robustness of the system while avoiding the need for subsequent analog signal processing circuits. Measured results on a mesh phantom demonstrate that the Flexi-EIT system can be easily configured with different numbers of DAEs and scan patterns to provide EIT measurement frames at 38 fps and real-time EIT images with at least 5 fps, showing the potential to be deployed in a variety of application scenarios and providing the optimal balance of system performance and hardware resource usage solutions.

ACT5 Electrical Impedance Tomography System

OBJECTIVE

This article introduces the Adaptive Current Tomograph 5 (ACT5) Electrical Impedance Tomography (EIT) system. ACT5 is a 32 electrode applied-current multiple-source EIT system that can display real-time images of conductivity and susceptivity at 27 frames per second. The adaptive current sources in ACT5 can apply fully programmable current patterns with frequencies varying from 5 kHz to 500 kHz. The system also displays real-time ECG readings during the EIT imaging process.

METHODS

The hardware and software design and specifications are presented, including the current source design, FPGA hardware, safety features, calibration, and shunt impedance measurement.

RESULTS

Images of conductivity and susceptivity are presented from ACT5 data collected on tank phantoms and a human subject illustrating the system's ability to provide real-time images of pulsatile perfusion and ECG traces.

SIGNIFICANCE

The portability, high signal-to-noise ratio, and flexibility of applied currents over a wide range of frequencies enable this instrument to be used to obtain useful human subject data with relative clinical ease.

Improved resolution of D-bar images of ventilation using a Schur complement property and an anatomical atlas

BACKGROUND

Electrical impedance tomography (EIT) is a nonionizing imaging technique for real-time imaging of ventilation of patients with respiratory distress. Cross-sectional dynamic images are formed by reconstructing the conductivity distribution from measured voltage data arising from applied alternating currents on electrodes placed circumferentially around the chest. Since the conductivity of lung tissue depends on air content, blood flow, and the presence of pathology, the dynamic images provide regional information about ventilation, pulsatile perfusion, and abnormalities. However, due to the ill-posedness of the inverse conductivity problem, EIT images have a coarse spatial resolution. One method of improving the resolution is to include prior information in the reconstruction.

PURPOSE

In this work, we propose a technique in which a statistical prior built from an anatomical atlas is used to postprocess EIT reconstructions of human chest data. The effectiveness of the method is demonstrated on data from two patients with cystic fibrosis.

METHODS

A direct reconstruction algorithm known as the D-bar method was used to compute a two-dimensional reconstruction of the conductivity distribution in the plane of the electrodes. Reconstructions using one step in an iterative (regularized) Newton's method were also computed for comparison. An anatomical atlas consisting of 1589 synthetic EIT images computed from X-ray computed tomography (CT) scans of 74 adult male subjects was computed for use as a statistical prior. The resolution of the D-bar images was then improved by maximizing the conditional probability density function of an image that is consistent with the a priori information and the statistical model. A new method to evaluate the accuracy of the EIT images using CT scans of the imaged patient as ground truth is presented. The novel approach is tested on data from two patients with cystic fibrosis.

RESULTS AND CONCLUSIONS

The D-bar images resulted in better structural similarity index measures (SSIM) and multiscale (MS) SSIM measures for both subjects using the mask or amplitude evaluation approach than the one-step (regularized) Newton's method. Further improvement was achieved using the Schur complement (SC) approach, with MS-SSIM values of 0.718 and 0.682 using SC evaluated with the mask and amplitude approach, respectively, for Patient 1, and MS-SSIM values of 0.726 and 0.692 using SC evaluated with the mask and amplitude approach, respectively, for Patient 2. The results from applying an anatomical atlas and statistical prior to EIT data from two patients with cystic fibrosis suggest that the spatial resolution of the EIT image can be improved to reveal pathology that may be difficult to discern in the original EIT image. The novel metric of evaluation is consistent with the appearance of improved spatial resolution and provides a new way to evaluate the accuracy of EIT reconstructions when a CT scan is available.

Evaluation of Pulmonary Structure and Function in Patients with Cystic Fibrosis from Electrical Impedance Tomography Data

Electrical impedance tomography (EIT) is a medical imaging technique in which low frequency, low amplitude electromagnetic fields applied through electrodes on the skin are used to compute the conductivity and/or permittivity inside the body and form functional images from the reconstructed values. This work describes methods of computing EIT-derived surrogate measures of pulmonary function and identifying regions of air trapping and consolidation from functional EIT images. These methods were developed for pediatric patients with cystic fibrosis, for whom a real-time non-ionizing imaging modality can be of great benefit for monitoring disease progression or a pulmonary exacerbation.

Sorted L1 regularization method for damage detection based on electrical impedance tomography

Carbon fiber reinforced polymers (CFRPs) are composite materials in which carbon provides strength and stiffness, whereas polymers provide cohesiveness and toughness. The electrical impedance of CFRP laminates is changed due to different kinds of damages. Electrical impedance tomography (EIT) has significant advantages such as non-intrusion, portability, low cost, and quick response and has widely been used as a nondestructive testing method. Therefore, EIT has great potential in structural health monitoring of CFRPs. Regularization can solve the ill-posed inverse problem of EIT. However, conventional regularization algorithms have their own limitations, such as over-smoothness of reconstructed edges and unstable solution caused by measurement noise. In addition, the anisotropic property of CFRPs also affects the image quality based on traditional methods. In this paper, the sorted L₁-norm regularization is proposed. It promotes grouping highly correlated variables while encouraging sparsity by using more effective penalty terms. The sharp edges between different materials can be obtained, and the obtained solution is more stable. The image quality of different objects, especially the image quality of multi-targets, can be significantly improved with this new method. In addition, the sorted L₁ norm can generate adaptive regularization parameters without empirical selection. The new regularization problem is solved by the alternating direction method of multipliers. Both experimental and simulation results demonstrate that the sorted L₁ norm improves the quality of reconstructed images under various noise levels. The proposed method is comprehensively evaluated with three image quality criteria by numerical simulation quantitatively.

A Point-Matching Method of Moment with Sparse Bayesian Learning Applied and Evaluated in Dynamic Lung Electrical Impedance Tomography

Dynamic lung imaging is a major application of Electrical Impedance Tomography (EIT) due to EIT's exceptional temporal resolution, low cost and absence of radiation. EIT however lacks in spatial resolution and the image reconstruction is very sensitive to mismatches between the actual object's and the reconstruction domain's geometries, as well as to the signal noise. The non-linear nature of the reconstruction problem may also be a concern, since the lungs' significant conductivity changes due to inhalation and exhalation. In this paper, a recently introduced method of moment is combined with a sparse Bayesian learning approach to address the non-linearity issue, provide robustness to the reconstruction problem and reduce image artefacts. To evaluate the proposed methodology, we construct three CT-based time-variant 3D thoracic structures including the basic thoracic tissues and considering 5 different breath states from end-expiration to end-inspiration. The Graz consensus reconstruction algorithm for EIT (GREIT), the correlation coefficient (CC), the root mean square error (RMSE) and the full-reference (FR) metrics are applied for the image quality assessment. Qualitative and quantitative comparison with traditional and more advanced reconstruction techniques reveals that the proposed method shows improved performance in the majority of cases and metrics. Finally, the approach is applied to single-breath online in-vivo data to qualitatively verify its applicability.

Practical Implementation of a Novel Output Impedance Measurement Technique for EIT System While Attached to a Load. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:3952-3956. [PMID: 34892096 PMCID: PMC9310546 DOI: 10.1109/embc46164.2021.9629839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

A novel method for measuring the output impedance of current sources in an EIT system is implemented and tested. The paper shows that the proposed method can be used at the time of operation while the load is attached to the EIT system. the results also show that performance of the system improves when the shunt impedance values from the proposed technique are used to set the adaptive sources as opposed to the shunt impedance values acquired through open circuit measurements.

Calderón's Method with a Spatial Prior for 2-D EIT Imaging of Ventilation and Perfusion

Bedside imaging of ventilation and perfusion is a leading application of 2-D medical electrical impedance tomography (EIT), in which dynamic cross-sectional images of the torso are created by numerically solving the inverse problem of computing the conductivity from voltage measurements arising on electrodes due to currents applied on electrodes on the surface. Methods of reconstruction may be direct or iterative. Calderón’s method is a direct reconstruction method based on complex geometrical optics solutions to Laplace’s equation capable of providing real-time reconstructions in a region of interest. In this paper, the importance of accurate modeling of the electrode location on the body is demonstrated on simulated and experimental data, and a method of including a priori spatial information in dynamic human subject data is presented. The results of accurate electrode modeling and a spatial prior are shown to improve detection of inhomogeneities not included in the prior and to improve the resolution of ventilation and perfusion images in a human subject.

Evaluation of Thoracic Equivalent Multiport Circuits Using an Electrical Impedance Tomography Hardware Simulation Interface

Electrical impedance tomography is a low-cost, safe, and high temporal resolution medical imaging modality which finds extensive application in real-time thoracic impedance imaging. Thoracic impedance changes can reveal important information about the physiological condition of patients’ lungs. In this way, electrical impedance tomography can be a valuable tool for monitoring patients. However, this technique is very sensitive to measurement noise or possible minor signal errors, coming from either the hardware, the electrodes, or even particular biological signals. Thus, the design of a good performance electrical impedance tomography hardware setup which properly interacts with the tissue examined is both an essential and a challenging concept. In this paper, we adopt an extensive simulation approach, which combines the system’s analogue and digital hardware, along with equivalent circuits of 3D finite element models that represent thoracic cavities. Each thoracic finite element model is created in MATLAB based on existing CT images, while the tissues’ conductivity and permittivity values for a selected frequency are acquired from a database using Python. The model is transferred to a multiport RLC network, embedded in the system’s hardware which is simulated at LT SPICE. The voltage output data are transferred to MATLAB where the electrical impedance tomography signal sampling and digital processing is also simulated. Finally, image reconstructions are performed in MATLAB, using the EIDORS library tool and considering the signal noise levels and different electrode and signal sampling configurations (ADC bits, sampling frequency, number of taps).

Analysis, Simulation, and Development of a Low-Cost Fully Active-Electrode Bioimpedance Measurement Module

A low-cost 1 kHz–400 kHz operating frequency fully-active electrode bioimpedance measurement module, based on Howland current source, is presented in this paper. It includes a buffered positive feedback Howland current source, implemented with operational amplifiers, as well as an AD8421 instrumentation amplifier, for the differential voltage measurements. Each active electrode module can be connected to others, assembling a wearable active electrode module array. From this array, 2 electrodes can be selected to be driven from a THS413 fully differential amplifier, activating a mirrored Howland current source. This work performs a complete circuit analysis, verified with MATLAB and SPICE simulations of the current source’s transconductance and output impedance over the frequency range between 1 kHz and 1 MHz. Resistors’ tolerances, possible mismatches, and the operational amplifiers’ non-idealities are considered in both the analysis and simulations. A comparison study between four selected operational amplifiers (ADA4622, OPA2210, AD8034, and AD8672) is additionally performed. The module is also hardware-implemented and tested in the lab for all four operational amplifiers and the transconductance is measured for load resistors of 150 Ω, 660 Ω, and 1200 Ω. Measurements showed that, using the AD8034 operational amplifier, the current source’s transconductance remains constant for frequencies up to 400 KHz for a 150 Ω load and 250 kHz for a 1200 Ω load, while lower performance is achieved with the other 3 operational amplifiers. Finally, transient simulations and measurements are performed at the AD8421 output for bipolar measurements on the 3 aforementioned load resistor values.

Simultaneous Imaging of Bio- and Non-Conductive Targets by Combining Frequency and Time Difference Imaging Methods in Electrical Impedance Tomography

As a promising medical imaging modality, electrical impedance tomography (EIT) can image the electrical properties within a region of interest using electrical measurements applied at electrodes on the region boundary. This paper proposes to combine frequency and time difference imaging methods in EIT to simultaneously image bio- and non-conductive targets, where the image fusion is accomplished by applying a wavelet-based technique. To enable image fusion, both time and frequency difference imaging methods are investigated regarding the reconstruction of bio- or non-conductive inclusions in the target region at varied excitation frequencies, indicating that none of those two methods can tackle with the scenarios where both bio- and non-conductive inclusions exist. This dilemma can be resolved by fusing the time difference (td) and appropriate frequency difference (fd) EIT images since they are complementary to each other. Through simulation and in vitro experiment, it is demonstrated that the proposed fusion method can reasonably reconstruct both the bio- and non-conductive inclusions within the lung models established to simulate the ventilation process, which is expected to be beneficial for the diagnosis of lung-tissue related diseases by EIT.

A Three Dimensional Calderon-Based Method for EIT on the Cylindrical Geometry

OBJECTIVE

Electrical impedance tomography (EIT) is an imaging modality in which voltage data arising from currents applied on the boundary are used to reconstruct the conductivity distribution in the interior. This paper provides a novel direct (noniterative) 3-D reconstruction algorithm for EIT in the cylindrical geometry.

METHODS

The algorithm is based on Calderón's method [Calderón, 1980], and is implemented for data collected on two or four rows of electrodes on the boundary of a cylinder.

RESULTS

The effectiveness of the method to localize inhomogeneities in the plane of the electrodes and in the z-direction is demonstrated on simulated and experimental data.

CONCLUSIONS AND SIGNIFICANCE

The results from simulated and experimental data show that the method is effective for distinguishing in-plane and nearby out-of-plane inhomogeneities with good spatial resolution in the vertical z direction with computational efficiency.

Shape-Driven EIT Reconstruction Using Fourier Representations

Shape-driven approaches have been proposed as an effective strategy for the electrical impedance tomography (EIT) reconstruction problem in recent years. In order to augment the shape-driven approaches, we propose a new method that transforms the shape to be reconstructed as basic primitives directly modeled by using Fourier representations. To allow automatic topological changes between the basic primitives and surrounding objects simultaneously, Boolean operations are employed. The Boolean operations with direct representation of primitives can be utilized for dimensionality and ill-posedness reduction, enabling feasible shape and topology optimization with shape-driven approaches. As a proof of principle, we leverage the proposed method for two dimensional shape reconstruction in EIT with various conductivity distributions. We demonstrate that our method is able to improve EIT reconstructions by enabling accurate shape and topology optimization.

Electrical Impedance Tomography - Recent Applications and Developments

Electrical impedance tomography (EIT) is a low-cost noninvasive imaging method. The main purpose of this paper is to highlight the main aspects of the EIT method and to review the recent advances and developments. The advances in instrumentation and in the different image reconstruction methods and systems are demonstrated in this review. The main applications of the EIT are presented and a special attention made to the papers published during the last years (from 2015 until 2020). The advantages and limitations of EIT are also presented. In conclusion, EIT is a promising imaging approach with a strong potential that has a large margin of progression before reaching the maturity phase.

Introduction of Sample Based Prior into the D-Bar Method Through a Schur Complement Property

Electrical impedance tomography (EIT) is a non-invasive medical imaging technique in which images of the conductivity in a region of interest in the body are computed from measurements of voltages on electrodes arising from low-frequency, low-amplitude applied currents. Mathematically, the inverse conductivity problem is nonlinear and ill-posed, and the reconstructions have characteristically low spatial resolution. One approach to improve the spatial resolution of EIT images is to include anatomically and physiologically-based prior information in the reconstruction algorithm. Statistical inversion theory provides a means of including prior information from a representative sample population. In this paper, a method is proposed to introduce statistical prior information into the D-bar method based on Schur complement properties. The method presents an improvement of the image obtained by the D-bar method by maximizing the conditional probability density function of an image that is consistent with a prior information and the model, given a D-bar image computed from the voltage measurements. Experimental phantoms show an improved spatial resolution by the use of the proposed method for the D-bar image reconstructions.

A second order Calderón's method with a correction term and a priori information

Calderón's method is a direct linearized reconstruction method for the inverse conductivity problem with the attribute that it can provide absolute images of both conductivity and permittivity with no need for forward modeling. In this work, an explicit relationship between Calderón's method and the D-bar method is provided, facilitating a "higher-order" Calderón's method in which a correction term is included, derived from the relationship to the D-bar method. Furthermore, a method of including a spatial prior is provided. These advances are demonstrated on simulated data and on tank data collected with the ACE1 EIT system.

Analog Realization of Fractional-Order Skin-Electrode Model for Tetrapolar Bio-Impedance Measurements

This work compares two design methodologies, emulating both AgCl electrode and skin tissue Cole models for testing and verification of electrical bio-impedance circuits and systems. The models are based on fractional-order elements, are implemented with active components, and capture bio-impedance behaviors up to 10 kHz. Contrary to passive-elements realizations, both architectures using analog filters coupled with adjustable transconductors offer tunability of the fractional capacitors’ parameters. The main objective is to build a tunable active integrated circuitry block that is able to approximate the models’ behavior and can be utilized as a Subject Under Test (SUT) and electrode equivalent in bio-impedance measurement applications. A tetrapolar impedance setup, typical in bio-impedance measurements, is used to demonstrate the performance and accuracy of the presented architectures via Spectre Monte-Carlo simulation. Circuit and post-layout simulations are carried out in 90-nm CMOS process, using the Cadence IC suite.

The D-bar method for electrical impedance tomography-demystified

Electrical impedance tomography (EIT) is an imaging modality where a patient or object is probed using harmless electric currents. The currents are fed through electrodes placed on the surface of the target, and the data consists of voltages measured at the electrodes resulting from a linearly independent set of current injection patterns. EIT aims to recover the internal distribution of electrical conductivity inside the target. The inverse problem underlying the EIT image formation task is nonlinear and severely ill-posed, and hence sensitive to modeling errors and measurement noise. Therefore, the inversion process needs to be regularized. However, traditional variational regularization methods, based on optimization, often suffer from local minima because of nonlinearity. This is what makes regularized direct (non-iterative) methods attractive for EIT. The most developed direct EIT algorithm is the D-bar method, based on Complex Geometric Optics solutions and a nonlinear Fourier transform. Variants and recent developments of D-bar methods are reviewed, and their practical numerical implementation is explained.

Reconstruction of Organ Boundaries With Deep Learning in the D-Bar Method for Electrical Impedance Tomography

OBJECTIVE

Medical electrical impedance tomography is a non-ionizing imaging modality in which low-amplitude, low-frequency currents are applied on electrodes on the body, the resulting voltages are measured, and an inverse problem is solved to determine the conductivity distribution in the region of interest. Due the ill-posedness of the inverse problem, the boundaries of internal organs are typically blurred in the reconstructed image.

METHODS

A deep learning approach is introduced in the D-bar method for reconstructing a 2-D slice of the thorax to recover the boundaries of organs. This is accomplished by training a deep neural network on labeled pairs of scattering transforms and the boundaries of the organs in the data from which the transforms were computed. This allows the network to "learn" the nonlinear mapping between them by minimizing the error between the output of the network and known actual boundaries. Further, a "sparse" reconstruction is computed by fusing the results of the standard D-bar reconstruction with reconstructed organ boundaries from the neural network.

RESULTS

Results are shown on simulated and experimental data collected on a saline-filled tank with agar targets simulating the conductivity of the heart and lungs.

CONCLUSIONS AND SIGNIFICANCE

The results demonstrate that deep neural networks can successfully learn the mapping between scattering transforms and the internal boundaries of structures.

Performance of an Adaptive Current Source for EIT Driving Loads through a Shielded Coaxial Cable

In Electrical Impedance Tomography (EIT) the coaxial cables used to connect the electrodes to the electronics have long been a concern due to their impact on system performance. Driving the shield of the cable is useful, since it mitigates the shunt capacitance. However, this approach introduces complexity and, sometimes, stability issues. Using "active electrodes", i.e. placing the front end of the electronics at the electrode end of the cables, is also helpful but can introduce packaging and hygiene problems. In this paper, a new type of high-precision current source is described and its performance is studied when driving loads through a coaxial cable. This new current source adjusts its current output to compensate for current lost in any shunt impedance to ground, including the shunt losses in the cable. Experimental results for frequencies up to 1 MHz are provided, comparing performance with resistive and complex loads connected without a cable, with 1 m of RG-174 coaxial cable with a driven shield, and 1 m of RG-174 coaxial cable with a grounded shield. The results for all 3 cases are similar, demonstrating that the source can provide satisfactory performance with a grounded-shield cable.

A Parametric EIT System Spice Simulation with Phantom Equivalent Circuits

In this paper a number of LT Spice simulations have been carried out on an Electrical Impedance Tomography (EIT) system, which includes the whole analog and digital circuitry as well as the subject to be examined (phantom model). The aim of this study is to show how the analog and digital parts, the electrodes and the subject’s physical properties may impact the measurements and the quality of the reconstructed image. This could provide a useful tool for designing an EIT system. Special attention has been given to the current source’s output impedance and swing, to the noise produced by the circuits and to the Analog to Digital Converters (ADCs) resolution and sampling rate. Furthermore, some 3D phantom subjects have been modeled and simulated as equivalent circuits, merged with the EIT simulated hardware, in order to observe how changes on their properties interact with the whole circuitry and affect the final result. Observations show that mirrored current sources with z o u t > 350 k Ω and sufficiently high ADC acquisition sampling rate ( f s a m p l e ≥ 16 f i n ) can result to accurate impedance measurements and therefore quality image reconstruction within a frequency span of at least 10 to 100 kHz. Moreover, possible hardware failures (electrode disconnections and imbalanced contact impedances) can be detected with a simple examination of the first extracted image and measurement set, so that by direct modification of the reconstruction process, a corrected result can be obtained.