Under the alternating electrical excitation, biological tissues produce a complex electrical impedance which depends on tissue composition, structures, health status, and applied signal frequency, and hence the bioelectrical impedance methods can be utilized for noninvasive tissue characterization. As the impedance responses of these tissue parameters vary with frequencies of the applied signal, the impedance analysis conducted over a wide frequency band provides more information about the tissue interiors which help us to better understand the biological tissues anatomy, physiology, and pathology. Over past few decades, a number of impedance based noninvasive tissue characterization techniques such as bioelectrical impedance analysis (BIA), electrical impedance spectroscopy (EIS), electrical impedance plethysmography (IPG), impedance cardiography (ICG), and electrical impedance tomography (EIT) have been proposed and a lot of research works have been conducted on these methods for noninvasive tissue characterization and disease diagnosis. In this paper BIA, EIS, IPG, ICG, and EIT techniques and their applications in different fields have been reviewed and technical perspective of these impedance methods has been presented. The working principles, applications, merits, and demerits of these methods has been discussed in detail along with their other technical issues followed by present status and future trends.

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Bioelectrical Impedance Methods for Noninvasive Health Monitoring: A Review.

Cross-sectional imaging of an electrical conductivity distribution inside the human body has been an active research goal in impedance imaging. By injecting current into an electrically conducting object through surface electrodes, we induce current density and voltage distributions. Based on the fact that these are determined by the conductivity distribution as well as the geometry of the object and the adopted electrode configuration, electrical impedance tomography (EIT) reconstructs cross-sectional conductivity images using measured current-voltage data on the surface. Unfortunately, there exist inherent technical difficulties in EIT. First, the relationship between the boundary current-voltage data and the internal conductivity distribution bears a nonlinearity and low sensitivity, and hence the inverse problem of recovering the conductivity distribution is ill posed. Second, it is difficult to obtain accurate information on the boundary geometry and electrode positions in practice, and the inverse problem is sensitive to these modeling errors as well as measurement artifacts and noise. These result in EIT images with a poor spatial resolution. In order to produce high-resolution conductivity images, magnetic resonance electrical impedance tomography (MREIT) has been lately developed. Noting that injection current produces a magnetic as well as electric field inside the imaging object, we can measure the induced internal magnetic flux density data using an MRI scanner. Utilization of the internal magnetic flux density is the key idea of MREIT to overcome the technical difficulties in EIT. Following original ideas on MREIT in early 1990s, there has been a rapid progress in its theory, algorithm and experimental techniques. The technique has now advanced to the stage of human experiments. Though it is still a few steps away from routine clinical use, its potential is high as a new impedance imaging modality providing conductivity images with a spatial resolution of a few millimeters or less. This paper reviews MREIT from the basics to the most recent research outcomes. Focusing on measurement techniques and experimental methods rather than mathematical issues, we summarize what has been done and what needs to be done. Suggestions for future research directions, possible applications in biomedicine, biology, chemistry and material science are discussed.

https://iopscience.iop.org/article/10.1088/0967-3334/29/10/R01/pdf

Magnetic resonance electrical impedance tomography (MREIT) for high-resolution conductivity imaging

Electrical impedance tomography (EIT) uses electrical stimulation and measurement at the body surface to image the electrical properties of internal tissues. It has the advantage of noninvasiveness and high temporal resolution but suffers from poor spatial resolution and sensitivity to electrode movement and contact quality. EIT can be useful to applications, where there are conductive contrasts between tissues, fluids, or gasses, such as imaging of cancerous or ischemic tissue or functional monitoring of breathing, blood flow, gastric motility, and neural activity. The past decade has seen clinical application and commercial activity using EIT for ventilation monitoring. Interpretation of EIT-based measures is complex, and this review paper focuses on describing the image interpretation “pathway.” We review this pathway, from Tissue Electrical Properties , EIT Electrodes & Hardware , Sensitivity , Image Reconstruction , Image Processing to EIT Measures . The relationship is discussed between the clinically relevant parameters and the reconstructed properties. An overview is given of areas of EIT application and of our perspectives for research and development.

Electrical Impedance Tomography: Tissue Properties to Image Measures

Magnetic resonance electrical impedance tomography (MREIT) is a recently developed medical imaging modality visualizing conductivity images of an electrically conducting object. MREIT was motivated by the well-known ill-posedness of the image reconstruction problem of electrical impedance tomography (EIT). Numerous experiences have shown that practically measurable data sets in an EIT system are insufficient for a robust reconstruction of a high-resolution static conductivity image due to its ill-posed nature and the influences of errors in forward modeling. To overcome the inherent ill-posed characteristics of EIT, the MREIT system was proposed in the early 1990s to use the internal data of magnetic flux density ${\bf B}=(B_x,B_y,B_z)$, which is induced by an externally injected current. MREIT uses an MRI scanner as a tool to measure the $z$-component $B_z$ of the magnetic flux density, where $z$ is the axial magnetization direction of the MRI scanner. In 2001, a constructive $B_z$-based MREIT algorithm called the harmonic $B_z$ algorithm was developed and its numerical simulations showed that high-resolution conductivity image reconstructions are possible. This novel algorithm is based on the key observation that the Laplacian $\Delta B_z$ probes changes in the log of the conductivity distribution along any equipotential curve having its tangent to the vector field ${\bf J}\times (0,0,1)$, where ${\bf J}=(J_x,J_y,J_z)$ is the induced current density vector. Since then, imaging techniques in MREIT have advanced rapidly and have now reached the stage of in vivo animal and human experiments. This paper reviews MREIT from its mathematical framework to the most recent human experiment outcomes.

Magnetic Resonance Electrical Impedance Tomography (MREIT)

Electrical Impedance Tomography (EIT) is a safe medical imaging technology, requiring no ionizing or heating radiation, as opposed to most other imaging modalities. This has led to a clinical interest in its use for long-term monitoring, possibly at the bedside, for ventilation monitoring, bleeding detection, gastric emptying and epilepsy foci diagnosis. These long-term applications demand auto-calibration and high stability over long time periods. To address this need we have developed a new multi-frequency EIT system called the KHU Mark2.5 with automatic self-calibration and cooperation with other devices via a timing signal for synchronization with other medical instruments. The impedance measurement module (IMM) for flexible configuration as a key component includes an independent constant current source, an independent differential voltmeter, and a current source calibrator, which allows automatic self-calibration of the current source within each IMM. We installed a resistor phantom inside the KHU Mark2.5 EIT system for intra-channel and inter-channel calibrations of all voltmeters in multiple IMMs. We show the deterioration of performance of an EIT system over time and the improvement due to automatic self-calibration. The system is able to maintain SNR of 80 dB for frequencies up to 250 kHz and below 0.5% reciprocity error over continuous operation for 24 hours. Automatic calibration at least every 3 days is shown to maintain SNR above 75 dB and reciprocity error below 0.7% over 7 days at 1 kHz. A clear degradation in performance results with increasing time between automatic calibrations allowing the tailoring of calibration to suit the performance requirements of each application.

Multi-Frequency Electrical Impedance Tomography System With Automatic Self-Calibration for Long-Term Monitoring

Frequency-difference electrical impedance tomography (fdEIT) has been proposed to deal with technical difficulties of a conventional static EIT imaging method caused by unknown boundary geometry, uncertainty in electrode positions and other systematic measurement artifacts. In fdEIT, we try to produce images showing changes of a complex conductivity distribution with respect to frequency. Simultaneously injecting currents with at least two frequencies, we find differences of measured boundary voltages between those frequencies. In most previous studies, real parts of frequency-difference voltage data were used to reconstruct conductivity changes and imaginary parts to reconstruct permittivity changes. This conventional approach neglects the interplay of conductivity and permittivity upon measured boundary voltage data. In this paper, we propose an improved fdEIT image reconstruction algorithm that properly handles the interaction. It uses weighted frequency differences of complex voltage data and a complex sensitivity matrix to reconstruct frequency-difference images of complex conductivity distributions. We found that there are two major sources of image contrast in fdEIT. The first is a contrast in complex conductivity values between an anomaly and background. The second is a frequency dependence of a complex conductivity distribution to be imaged. We note that even for the case where conductivity and permittivity do not change with frequency, the fdEIT algorithm may show a contrast in frequency-difference images of complex conductivity distributions. On the other hand, even if conductivity and permittivity values significantly change with frequency, there is an example where we cannot find any contrast. The performance of the proposed method is demonstrated by using computer simulations to validate its feasibility in future experimental studies.

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Frequency-difference electrical impedance tomography (fdEIT): algorithm development and feasibility study.

Validation and interpretation of reconstructed images using a multi-frequency electrical impedance tomography (mfEIT) requires a conductivity phantom including imaging objects with known complex conductivity (σ + iωe) spectra. We describe imaging experiments using the recently developed mfEIT system called the KHU Mark1 with the frequency range of 10 Hz to 500 kHz. Using a bio-impedance spectroscopy (BIS) system, we first measured complex conductivity spectra of different imaging objects including saline, agar, polyacrylamide, TX151, animal hide gelatin, banana and cucumber. Based on an analysis of how conductivity and permittivity affect measured complex boundary voltages, we suggested a new complex version of a multi-frequency time-difference image reconstruction algorithm. Imaging experiments were conducted to produce time-difference images of the objects at multiple frequencies using the proposed algorithm. Images of a conductor (stainless steel) and an insulator (acrylic plastic) were used to set a common scale bar to display all images. Comparing reconstructed time-difference images at multiple frequencies with measured complex conductivity spectra, we found that they showed an overall similarity in terms of changes in complex conductivity values with respect to frequency. However, primarily due to the limitation of the difference imaging algorithm, we suggest that multi-frequency time-difference images must be interpreted in terms of relative contrast changes with respect to frequency. We propose further imaging studies using biological tissues of known complex conductivity spectra and using human subjects to find clinical applications of the mfEIT system.

/pdf/validation-of-a-multi-frequency-electrical-impedance-156q7bbzj5.pdf

Validation of a multi-frequency electrical impedance tomography (mfEIT) system KHU Mark1: impedance spectroscopy and time-difference imaging.

Magnetic resonance electrical impedance tomography (MREIT) attempts to provide conductivity images of an electrically conducting object with a high spatial resolution. When we inject current into the object, it produces internal distributions of current density J and magnetic flux density B=(Bx,By,Bz). By using a magnetic resonance imaging (MRI) scanner, we can measure Bz data where z is the direction of the main magnetic field of the scanner. Conductivity images are reconstructed based on the relation between the injection current and Bz data. The harmonic Bz algorithm was the first constructive MREIT imaging method and it has been quite successful in previous numerical and experimental studies. Its performance is, however, degraded when the imaging object contains low-conductivity regions such as bones and lungs. To overcome this difficulty, we carefully analyzed the structure of a current density distribution near such problematic regions and proposed a new technique, called the local harmonic Bz algorithm. We first reconstruct conductivity values in local regions with a low conductivity contrast, separated from those problematic regions. Then, the method of characteristics is employed to find conductivity values in the problematic regions. One of the most interesting observations of the new algorithm is that it can provide a scaled conductivity image in a local region without knowing conductivity values outside the region. We present the performance of the new algorithm by using computer simulation methods.

Local Harmonic $B_z$ Algorithm With Domain Decomposition in MREIT: Computer Simulation Study

We describe a new multi-frequency technique for breast cancer detection. Applying a constant voltage with multiple sinusoidal frequencies between a reference electrode on a distal part of a patient and a scan probe placed on the breast, we measure exit currents from an array of electrodes inside the probe that are kept at the ground potential. The distribution of measured exit currents is called the trans-admittance map and the instrument is called the trans-admittance scanner (TAS). We assume a three-dimensional homogeneous domain including an internal lesion with a complex conductivity different from that of the background. Mathematically analyzing the multi-frequency trans-admittance map obtained on the surface of the domain, we found that both conductivity and permittivity ratios between the background and the lesion are crucial in extracting any useful information about the lesion from the map. Choosing two frequencies in the range of 10 Hz to 500 kHz with one significantly lower than the other and assuming that conductivity values of the background and the lesion do not change much from the low to high frequency, the lesion underneath the probe can be detected only when the conductivity ratio between the background and the lesion is different from the permittivity ratio between the background and the lesion at the chosen high frequency. Results of numerical simulations and saline phantom experiments using a developed TAS system are well matched with the mathematical analysis. The biggest advantage of this multi-frequency technique is that we do not need separately measured reference data in the absence of any lesion. We suggest future studies of a more sophisticated lesion detection algorithm based on the analysis and findings described in this paper.

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Feasibility of breast cancer lesion detection using a multi-frequency trans-admittance scanner (TAS) with 10 Hz to 500 kHz bandwidth

In magnetic resonance electrical impedance tomography (MREIT) where we try to reconstruct conductivity images with high spatial resolution, we should generate at least two nonparallel internal current density distribution by sequentially injecting multiple independent currents. However, when the object has a relatively very low conductivity region, the direction of current density due to any injection current becomes tangential to the boundary of the region. This kind of regions may include bones, lungs, and air-filled stomach. Hence, the previous MREIT reconstruction algorithm failto provide accurate conductivity recunstructionnear boundaries of insulating regions since this requirement is not satisfied. To deal with this difficulty, we propose local harmonicB z -algorithm which find conductivity values in the seperated problematic regions.

Sung Wan Kim

Papers

Frequency-difference electrical impedance tomography (fdEIT): algorithm development and feasibility study.

Validation of a multi-frequency electrical impedance tomography (mfEIT) system KHU Mark1: impedance spectroscopy and time-difference imaging.

Local Harmonic $B_z$ Algorithm With Domain Decomposition in MREIT: Computer Simulation Study

Feasibility of breast cancer lesion detection using a multi-frequency trans-admittance scanner (TAS) with 10 Hz to 500 kHz bandwidth

Local harmonic B z algorithm in MREIT