Design and calibration of a compact multi-frequency EIT system for acute stroke imaging

Exploratory study of a multifrequency EIT-based method for detecting intracranial abnormalities

Objective

The purpose of this paper is to compare the differences in the features of multifrequency electrical impedance tomography (MFEIT) images of human heads between healthy subjects and patients with brain diseases and to explore the possibility of applying MFEIT to intracranial abnormality detection.

Methods

Sixteen healthy volunteers and 8 patients with brain diseases were recruited as subjects, and the cerebral MFEIT data of 9 frequencies in the range of 21 kHz - 100 kHz of all subjects were acquired with an MFEIT system. MFEIT image sequences were obtained according to certain imaging algorithms, and the area ratio of the ROI (AR_ROI) and the mean value of the reconstructed resistivity change of the ROI (MVRRC_ROI) on both the left and right sides of these images were extracted. The geometric asymmetry index (GAI) and intensity asymmetry index (IAI) were further proposed to characterize the symmetry of MFEIT images based on the extracted indices and to statistically compare and analyze the differences between the two groups of subjects on MFEIT images.

Results

There were no significant differences in either the AR_ROI or the MVRRC_ROI between the two sides of the brains of healthy volunteers (p > 0.05); some of the MFEIT images mainly in the range of 30 kHz - 60 kHz of patients with brain diseases showed stronger resistivity distributions (larger area or stronger signal) that were approximately symmetric with the location of the lesions. However, statistical analysis showed that the AR_ROI and the MVRRC_ROI on the healthy sides of MFEIT images of patients with unilateral brain disease were not significantly different from those on the affected side (p > 0.05). The GAI and IAI were higher in all patients with brain diseases than in healthy volunteers except for 80 kHz (p < 0.05).

Conclusion

There were significant differences in the geometric symmetry and the signal intensity symmetry of the reconstructed targets in the MFEIT images between healthy volunteers and patients with brain diseases, and the above findings provide a reference for the rapid detection of intracranial abnormalities using MFEIT images and may provide a basis for further exploration of MFEIT for the detection of brain diseases.

An alternative excitation method for electrical impedance tomography

Electrical impedance tomography (EIT) can be utilized to image the conductivity distribution of material under test. The EIT measurements depend on the quality in the current injection and voltage measuring circuits. The current source plays a vital role in the EIT instruments. In most of the research studies, the push-pull current sources were employed for the source and sink signal generation. It usually requires frequent calibration to achieve proper functioning, especially for the sweeping frequency measurements. In this paper, an alternative excitation method has been proposed for simplifying the design of the current source in EIT instruments, which aims to achieve the performance of the push-pull current source by using a single-ended current source. It could offer the following advantages: (1) hardware simplification and (2) reduced requirements on current source calibration. The corrected measurements could be consistent with that using push-pull excitation, as confirmed by the numerical simulations. In addition, the reconstructed images have also been investigated to illustrate the effectiveness of the proposed method.

Advances in electrical impedance tomography-based brain imaging

Novel advances in the field of brain imaging have enabled the unprecedented clinical application of various imaging modalities to facilitate disease diagnosis and treatment. Electrical impedance tomography (EIT) is a functional imaging technique that measures the transfer impedances between electrodes on the body surface to estimate the spatial distribution of electrical properties of tissues. EIT offers many advantages over other neuroimaging technologies, which has led to its potential clinical use. This qualitative review provides an overview of the basic principles, algorithms, and system composition of EIT. Recent advances in the field of EIT are discussed in the context of epilepsy, stroke, brain injuries and edema, and other brain diseases. Further, we summarize factors limiting the development of brain EIT and highlight prospects for the field. In epilepsy imaging, there have been advances in EIT imaging depth, from cortical to subcortical regions. In stroke research, a bedside EIT stroke monitoring system has been developed for clinical practice, and data support the role of EIT in multi-modal imaging for diagnosing stroke. Additionally, EIT has been applied to monitor the changes in brain water content associated with cerebral edema, enabling the early identification of brain edema and the evaluation of mannitol dehydration. However, anatomically realistic geometry, inhomogeneity, cranium completeness, anisotropy and skull type, etc., must be considered to improve the accuracy of EIT modeling. Thus, the further establishment of EIT as a mature and routine diagnostic technique will necessitate the accumulation of more supporting evidence.

Simplifying the hardware requirements for fast neural EIT of peripheral nerves

OBJECTIVE

The main objective of this study was to assess the feasibility of lowering the hardware requirements for fast neural EIT in order to support the distribution of this technique. Specifically, the feasibility of replacing the commercial modules present in the existing high-end setup with compact and cheap customized circuitry was assessed.

APPROACH

Nerve EIT imaging was performed on rat sciatic nerves with both our standard ScouseTom setup and a customized version in which commercial benchtop current sources were replaced by custom circuitry. Electrophysiological data and images collected in the same experimental conditions with the two setups were compared. Data from the customized setup was subject to a down-sampling analysis to simulate the use of a recording module with lower specifications.

MAIN RESULTS

Compound action potentials (573±287µV and 487±279µV, p=0.28) and impedance changes (36±14µV and 31±16µV, p=0.49) did not differ significantly when measured using commercial high-end current sources or our custom circuitry, respectively. Images reconstructed from both setups showed neglibile (<1voxel, i.e. 40µm) difference in peak location and a high degree of correlation (R2=0.97). When down-sampling from 24 to 16 bits ADC resolution and from 100KHz to 50KHz sampling frequency, signal-to-noise ratio showed acceptable decrease (<-20%), and no meaningful image quality loss was detected (peak location difference <1voxel, pixel-by-pixel correlation R2=0.99).

SIGNIFICANCE

The technology developed for this study greatly reduces the cost and size of a fast neural EIT setup without impacting quality and thus promotes the adoption of this technique by the neuroscience research community.

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 Review on Electrical Impedance Tomography Spectroscopy

Electrical Impedance Tomography Spectroscopy (EITS) enables the reconstruction of material distributions inside an object based on the frequency-dependent characteristics of different substances. In this paper, we present a review of EITS focusing on physical principles of the technology, sensor geometries, existing measurement systems, reconstruction algorithms, and image representation methods. In addition, a novel imaging method is proposed which could fill some of the gaps found in the literature. As an example of an application, EITS of ice and water mixtures is used.

The ACE1 Electrical Impedance Tomography System for Thoracic Imaging

The design and performance of the ACE1 (Active Complex Electrode) electrical impedance tomography system for single-ended phasic voltage measurements is presented. The design of the hardware and calibration procedures allow for reconstruction of conductivity and permittivity images. Phase measurement is achieved with the ACE1 active electrode circuit which measures the amplitude and phase of the voltage and the applied current at the location at which current is injected into the body. An evaluation of the system performance under typical operating conditions includes details of demodulation and calibration and an in-depth look at insightful metrics, such as signal-to-noise ratio variations during a single current pattern. Static and dynamic images of conductivity and permittivity are presented from ACE1 data collected on tank phantoms and human subjects to illustrate the system's utility.

Capacitively Coupled Electrical Impedance Tomography for Brain Imaging

Electrical impedance tomography (EIT) is considered as a potential candidate for brain stroke imaging due to its compactness and potential use in bedside and emergency settings. The electrode-skin contact impedance and low conductivity of skull pose some practical challenges to the EIT head imaging. This paper studies the application of capacitively coupled electrical impedance tomography (CCEIT) in brain imaging for the first time. CCEIT is a new contactless EIT technique which uses voltage excitation without direct contact with the skin, as oppose to directly injecting the current to the skin in EIT. Because the safety issue of a new technique should be strictly treated, simulation work based on a simplified head model was carried out to investigate the safety aspects of CCEIT. By comparing with the standard EIT excited by a typical safe current level used in brain imaging, the safe excitation reference of CCEIT is obtained. This is done by comparing the maximum level of internal electrical field (internal current density) of EIT and that of CCEIT. Simulation results provide useful knowledge of excitation signal level of CCEIT and also show a critical comparison with traditional EIT. Practical experiments were carried out with a 12-electrode CCEIT phantom, saline, and carrot samples. Experimental results show the feasibility and potential of CCEIT for stroke imaging. In this paper, the anomaly diameter resolution is 10 mm (1/18 of the phantom diameter), which indicates that small-volume stroke could be detected. This is achieved by a low excitation voltage of 1 V, showing the possibility of even better performance when higher but yet safe level of excitation voltages is used.

Structured Design Methodology to Achieve a High SNR Electrical Impedance Tomography

In this paper, we present a methodology for designing the main circuit building blocks of an electrical impedance tomography (EIT) system. In particular, we derive equations that map system-level EIT specifications to the performance requirements of each circuit block. We also review the circuit architectures that are best suited for meeting a given set of performance requirements. Our proposed design methodology is focused on maximizing the EIT system's signal-to-noise ratio while minimizing total power consumption.

Exploring the Potential of Electrical Impedance Tomography for Tissue Engineering Applications

In tissue engineering, cells are generally cultured in biomaterials to generate three-dimensional artificial tissues to repair or replace damaged parts and re-establish normal functions of the body. Characterizing cell growth and viability in these bioscaffolds is challenging, and is currently achieved by destructive end-point biological assays. In this study, we explore the potential to use electrical impedance tomography (EIT) as a label-free and non-destructive technology to assess cell growth and viability. The key challenge in the tissue engineering application is to detect the small change of conductivity associated with sparse cell distributions in regards to the size of the hosting scaffold, i.e., low volume fraction, until they assemble into a larger tissue-like structure. We show proof-of-principle data, measure cells within both a hydrogel and a microporous scaffold with an ad-hoc EIT equipment, and introduce the frequency difference technique to improve the reconstruction.

Addition of internal electrodes is beneficial for focused bioimpedance measurements in the lung

OBJECTIVE

Bioimpedance measurements such as bioimpedance spectroscopy (BIS) or electrical impedance tomography (EIT) are used in many biomedical applications. While BIS measures and analyzes the impedance in a frequency range at constant electrode positions, EIT aims to reconstruct images of the conductivity distribution from multiple measurements at different electrode positions. Our aim is to add spatial information to tetrapolar BIS measurements by using electrode positions that focus measurements on desired regions of interest. In this paper, we aim to investigate, whether internal electrodes that can be integrated into breathing or gastroesophageal tubes, can improve the local sensitivity of bioimpedance spectroscopy measurements.

APPROACH

We present the results of a simulation study, in which we investigated more than 4 M different electrode configurations on their ability to monitor specific regions of interest (ROI) in the lung. Based on the sensitivity, which describes the impact of a conductivity change on the measured impedance, we define three main criteria which we use to evaluate our simulation results: the selectivity [Formula: see text], which describes the impact of a conductivity change inside the region of interest compared to a conductivity change outside the ROI; the homogeneity [Formula: see text], which describes the distribution of the sensitivity inside the ROI; and the absolute impedance contribution ratio [Formula: see text], which describes the contribution of the ROI to the measured impedance.

MAIN RESULTS

Depending on the region of interest, electrode configurations using internal electrodes are between 9.8 % and 90 % better with respect to these criteria than configurations using external electrodes only.

SIGNIFICANCE

The combination of internal and external electrodes improves the focusing ability of tetrapolar impedance measurements on specific lung regions, which may be especially beneficial for lung monitoring in intensive care.

A 10 MHz Read-Out Chain for Electrical Impedance Tomography

This paper presents the design and implementation of a read-out chain for electrical impedance tomography (EIT) imaging. The EIT imaging approach can be incorporated to take spectral images of the tissue under study, offering an affordable, portable device for home health monitoring. A fast read-out channel covering a wide range of frequencies is a must for such applications. The proposed read-out channel comprising a programmable gain instrumentation amplifier, an analog-to-digital converter (ADC), and an ADC driver is designed and fabricated in a 0.18  m CMOS technology. The proposed read-out chain operates over the wide frequency range of 100 Hz to 10 MHz, with an average signal-to-noise ratio of more than 60 dB. The entire read-out channel consumes between 6.9 and 21.8 mW, depending on its frequency of operation.

Applications of Bioimpedance Measurement Techniques in Tissue Engineering

Rapid development in the field of tissue engineering necessitates implementation of monitoring methods for evaluation of the viability and characteristics of the cell cultures in a real-time, non-invasive and non-destructive manner. Current monitoring techniques are mainly histological and require labeling and involve destructive tests to characterize cell cultures. Bioimpedance measurement technique which benefits from measurement of electrical properties of the biological tissues, offers a non-invasive, label-free and real-time solution for monitoring tissue engineered constructs. This review outlines the fundamentals of bioimpedance, as well as electrical properties of the biological tissues, different types of cell culture constructs and possible electrode configuration set ups for performing bioimpedance measurements on these cell cultures. In addition, various bioimpedance measurement techniques and their applications in the field of tissue engineering are discussed.

A multi-frequency electrical impedance tomography system for real-time 2D and 3D imaging

This paper presents the design and evaluation of a configurable, fast multi-frequency Electrical Impedance Tomography (mfEIT) system for real-time 2D and 3D imaging, particularly for biomedical imaging. The system integrates 32 electrode interfaces and the current frequency ranges from 10 kHz to 1 MHz. The system incorporates the following novel features. First, a fully adjustable multi-frequency current source with current monitoring function is designed. Second, a flexible switching scheme is developed for arbitrary sensing configuration and a semi-parallel data acquisition architecture is implemented for high-frame-rate data acquisition. Furthermore, multi-frequency digital quadrature demodulation is accomplished in a high-capacity Field Programmable Gate Array. At last, a 3D imaging software, visual tomography, is developed for real-time 2D and 3D image reconstruction, data analysis, and visualization. The mfEIT system is systematically tested and evaluated from the aspects of signal to noise ratio (SNR), frame rate, and 2D and 3D multi-frequency phantom imaging. The highest SNR is 82.82 dB on a 16-electrode sensor. The frame rate is up to 546 fps at serial mode and 1014 fps at semi-parallel mode. The evaluation results indicate that the presented mfEIT system is a powerful tool for real-time 2D and 3D imaging.

In Vivo Bioimpedance Spectroscopy Characterization of Healthy, Hemorrhagic and Ischemic Rabbit Brain within 10 Hz-1 MHz

Acute stroke is a serious cerebrovascular disease and has been the second leading cause of death worldwide. Conventional diagnostic modalities for stroke, such as CT and MRI, may not be available in emergency settings. Hence, it is imperative to develop a portable tool to diagnose stroke in a timely manner. Since there are differences in impedance spectra between normal, hemorrhagic and ischemic brain tissues, multi-frequency electrical impedance tomography (MFEIT) shows great promise in detecting stroke. Measuring the impedance spectra of healthy, hemorrhagic and ischemic brain in vivo is crucial to the success of MFEIT. To our knowledge, no research has established hemorrhagic and ischemic brain models in the same animal and comprehensively measured the in vivo impedance spectra of healthy, hemorrhagic and ischemic brain within 10 Hz–1 MHz. In this study, the intracerebral hemorrhage and ischemic models were established in rabbits, and then the impedance spectra of healthy, hemorrhagic and ischemic brain were measured in vivo and compared. The results demonstrated that the impedance spectra differed significantly between healthy and stroke-affected brain (i.e., hemorrhagic or ischemic brain). Moreover, the rate of change in brain impedance following hemorrhagic and ischemic stroke with regard to frequency was distinct. These findings further validate the feasibility of using MFEIT to detect stroke and differentiate stroke types, and provide data supporting for future research.

A Versatile and Reproducible Multi-Frequency Electrical Impedance Tomography System

A highly versatile Electrical Impedance Tomography (EIT) system, nicknamed the ScouseTom, has been developed. The system allows control over current amplitude, frequency, number of electrodes, injection protocol and data processing. Current is injected using a Keithley 6221 current source, and voltages are recorded with a 24-bit EEG system with minimum bandwidth of 3.2 kHz. Custom PCBs interface with a PC to control the measurement process, electrode addressing and triggering of external stimuli. The performance of the system was characterised using resistor phantoms to represent human scalp recordings, with an SNR of 77.5 dB, stable across a four hour recording and 20 Hz to 20 kHz. In studies of both haeomorrhage using scalp electrodes, and evoked activity using epicortical electrode mats in rats, it was possible to reconstruct images matching established literature at known areas of onset. Data collected using scalp electrode in humans matched known tissue impedance spectra and was stable over frequency. The experimental procedure is software controlled and is readily adaptable to new paradigms. Where possible, commercial or open-source components were used, to minimise the complexity in reproduction. The hardware designs and software for the system have been released under an open source licence, encouraging contributions and allowing for rapid replication.

A novel multi-frequency electrical impedance tomography spectral imaging algorithm for early stroke detection

Multi-frequency electrical impedance tomography (MFEIT) reconstructs the image of conductivity inside the human body based on the dependence of tissue conductivity on frequency. As there exist differences in the conductivity over frequency between blood, ischemic cortical tissue and normal cortical tissue, MFEIT has potential application in the detection of acute stroke. However, because the conductivity distribution of the human head is highly inhomogeneous and the conductivities of normal head tissue and stroke lesion tissue both change with frequency, the anomaly and normal head tissues are often mixed together in the reconstructed image, which makes it difficult to discern the anomaly. Here we present a spectral decomposition frequency-difference (SD-FD) imaging algorithm in an attempt to address this issue: firstly, we reconstruct so-called EIT spectral images according to the conductivity spectra of tissues; secondly, we obtain the EIT image of the anomaly from the spectral images by using independent component analysis. The results show that the proposed algorithm is capable of detecting the anomaly in a numerical head phantom, as well as in a realistic human head tank with frequency-dependent and heterogeneous conductivities distribution. The proposed SD-FD algorithm may support MFEIT use for human stroke imaging in the future.

Feasibility of Imaging Tissue Electrical Conductivity by Switching Field Gradients with MRI

Tissue conductivity is a biophysical marker of tissue structure and physiology. Present methods of measuring tissue conductivity are limited. Electrical impedance tomography, and magnetic resonance electrical impedance tomography rely on passing external current through the object being imaged, which prevents its use in most human imaging. Recently, the RF field used for MR excitation has been used to non-invasively measure tissue conductivity. This technique is promising, but conductivity at higher frequencies is less sensitive to tissue structure. Measuring tissue conductivity non-invasively at low frequencies remains elusive. It has been proposed that eddy currents generated during the rise and decay of gradient pulses could act as a current source to map low-frequency conductivity. This work centers on a gradient echo pulse sequence that uses large gradients prior to excitation to create eddy currents. The electric and magnetic fields during a gradient pulse are simulated by a finite-difference time-domain simulation. The sequence is also tested with a phantom and an animal MRI scanner equipped with gradients of high gradient strengths and slew rate. The simulation demonstrates that eddy currents in materials with conductivity similar to biological tissue decay with a half-life on the order of nanoseconds and any eddy currents generated prior to excitation decay completely before influencing the RF signal. Gradient-induced eddy currents can influence phase accumulation after excitation but the effect is too small to image. The animal scanner images show no measurable phase accumulation. Measuring low-frequency conductivity by gradient-induced eddy currents is presently unfeasible.

Multifrequency electrical impedance tomography with total variation regularization

Multifrequency electrical impedance tomography (MFEIT) reconstructs the distribution of conductivity by exploiting the dependence of tissue conductivity on frequency. MFEIT can be performed on a single instance of data, making it promising for applications such as stroke and cancer imaging, where it is not possible to obtain a 'baseline' measurement of healthy tissue. A nonlinear MFEIT algorithm able to reconstruct the volume fraction distribution of tissue rather than conductivities has been developed previously. For each volume, the fraction of a certain tissue should be either 1 or 0; this implies that the sharp changes of the fractions, representing the boundaries of tissue, contain all the relevant information. However, these boundaries are blurred by traditional regularization methods using [Formula: see text] norm. The total variation (TV) regularization can overcome this problem, but it is difficult to solve due to its non-differentiability. Because the fraction must be between 0 and 1, this imposes a constraint on the MFEIT method based on the fraction model. Therefore, a constrained optimization method capable of dealing with non-differentiable problems is required. Based on the primal and dual interior point method, we propose a new constrained TV regularized method to solve the fraction reconstruction problem. The noise performance of the new MFEIT method is analysed using simulations on a 2D cylindrical mesh. Convergence performance is also analysed through experiments using a cylindrical tank. Finally, simulations on an anatomically realistic head-shaped mesh are demonstrated. The proposed MFEIT method with TV regularization shows higher spatial resolution, particularly at the edges of the perturbation, and stronger noise robustness, and its image noise and shape error are 20% to 30% lower than the traditional fraction method.

Comparison of total variation algorithms for electrical impedance tomography

The applications of total variation (TV) algorithms for electrical impedance tomography (EIT) have been investigated. The use of the TV regularisation technique helps to preserve discontinuities in reconstruction, such as the boundaries of perturbations and sharp changes in conductivity, which are unintentionally smoothed by traditional l2 norm regularisation. However, the non-differentiability of TV regularisation has led to the use of different algorithms. Recent advances in TV algorithms such as the primal dual interior point method (PDIPM), the linearised alternating direction method of multipliers (LADMM) and the spilt Bregman (SB) method have all been demonstrated successful EIT applications, but no direct comparison of the techniques has been made. Their noise performance, spatial resolution and convergence rate applied to time difference EIT were studied in simulations on 2D cylindrical meshes with different noise levels, 2D cylindrical tank and 3D anatomically head-shaped phantoms containing vegetable material with complex conductivity. LADMM had the fastest calculation speed but worst resolution due to the exclusion of the second-derivative; PDIPM reconstructed the sharpest change in conductivity but with lower contrast than SB; SB had a faster convergence rate than PDIPM and the lowest image errors.

An instrumental electrode model for solving EIT forward problems

An instrumental electrode model (IEM) capable of describing the performance of electrical impedance tomography (EIT) systems in the MHz frequency range has been proposed. Compared with the commonly used Complete Electrode Model (CEM), which assumes ideal front-end interfaces, the proposed model considers the effects of non-ideal components in the front-end circuits. This introduces an extra boundary condition in the forward model and offers a more accurate modelling for EIT systems. We have demonstrated its performance using simple geometry structures and compared the results with the CEM and full Maxwell methods. The IEM can provide a significantly more accurate approximation than the CEM in the MHz frequency range, where the full Maxwell methods are favoured over the quasi-static approximation. The improved electrode model will facilitate the future characterization and front-end design of real-world EIT systems.

Multi-frequency electrical impedance tomography system with automatic self-calibration for long-term monitoring

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.

Multifrequency electrical impedance tomography using spectral constraints

Multifrequency electrical impedance tomography (MFEIT) exploits the dependence of tissue impedance on frequency to recover an image of conductivity. MFEIT could provide emergency diagnosis of pathologies such as acute stroke, brain injury and breast cancer. We present a method for performing MFEIT using spectral constraints. Boundary voltage data is employed directly to reconstruct the volume fraction distribution of component tissues using a nonlinear method. Given that the reconstructed parameter is frequency independent, this approach allows for the simultaneous use of all multifrequency data, thus reducing the degrees of freedom of the reconstruction problem. Furthermore, this method allows for the use of frequency difference data in a nonlinear reconstruction algorithm. Results from empirical phantom measurements suggest that our fraction reconstruction method points to a new direction for the development of multifrequency EIT algorithms in the case that the spectral constraints are known, and may provide a unifying framework for static EIT imaging.

FPGA Based High Speed Data Acquisition System for Electrical Impedance Tomography

Electrical Impedance Tomography (EIT) systems are used to image tissue bio-impedance. EIT provides a number of features making it attractive for use as a medical imaging device including the ability to image fast physiological processes (>60 Hz), to meet a range of clinical imaging needs through varying electrode geometries and configurations, to impart only non-ionizing radiation to a patient, and to map the significant electrical property contrasts present between numerous benign and pathological tissues. To leverage these potential advantages for medical imaging, we developed a modular 32 channel data acquisition (DAQ) system using National Instruments' PXI chassis, along with FPGA, ADC, Signal Generator and Timing and Synchronization modules. To achieve high frame rates, signal demodulation and spectral characteristics of higher order harmonics were computed using dedicated FFT-hardware built into the FPGA module. By offloading the computing onto FPGA, we were able to achieve a reduction in throughput required between the FPGA and PC by a factor of 32:1. A custom designed analog front end (AFE) was used to interface electrodes with our system. Our system is wideband, and capable of acquiring data for input signal frequencies ranging from 100 Hz to 12 MHz. The modular design of both the hardware and software will allow this system to be flexibly configured for the particular clinical application.

Comparison of frequency difference reconstruction algorithms for the detection of acute stroke using EIT in a realistic head-shaped tank

Imaging of acute stroke might be possible using multi-frequency electrical impedance tomography (MFEIT) but requires absolute or frequency difference imaging. Simple linear frequency difference reconstruction has been shown to be ineffective in imaging with a frequency-dependant background conductivity; this has been overcome with a weighted frequency difference approach with correction for the background but this has only been validated for a cylindrical and hemispherical tank. The feasibility of MFEIT for imaging of acute stroke in a realistic head geometry was examined by imaging a potato perturbation against a saline background and a carrot-saline frequency-dependant background conductivity, in a head-shaped tank with the UCLH Mk2.5 MFEIT system. Reconstruction was performed with time difference (TD), frequency difference (FD), FD adjacent (FDA), weighted FD (WFD) and weighted FDA (WFDA) linear algorithms. The perturbation in reconstructed images corresponded to the true position to <9.5% of image diameter with an image SNR of >5.4 for all algorithms in saline but only for TD, WFDA and WFD in the carrot-saline background. No reliable imaging was possible with FD and FDA. This indicates that the WFD approach is also effective for a realistic head geometry and supports its use for human imaging in the future.

Validation of weighted frequency-difference EIT using a three-dimensional hemisphere model and phantom

Frequency-difference (FD) electrical impedance tomography (EIT) using a weighted voltage difference has recently been proposed for imaging haemorrhagic stroke, abdominal bleeding and tumors. Although its feasibility was demonstrated through two-dimensional numerical simulations and phantom experiments, we should validate the method in three-dimensional imaging objects. At the same time, we need to investigate its robustness against geometrical modeling errors in boundary shapes and electrode positions. We performed a validation study of the weighted FD method through three-dimensional numerical simulations and phantom experiments. Adopting hemispherical models and phantoms whose admittivity distributions change with frequency, we investigated the performance of the method to detect an anomaly. We found that the simple FD method fails to detect the anomaly, whereas reconstructed images using the weighted FD method clearly visualize the anomaly. The weighted FD method is robust against modeling errors of boundary-shape deformations and displaced electrode positions. We also found that the method is capable of detecting an anomaly surrounded by a shell-shaped obstacle simulating the skull. We propose the weighted FD method for future studies of animal and human experiments.

Frequency-division multiplexing for electrical impedance tomography in biomedical applications

Electrical impedance tomography (EIT) produces an image of the electrical impedance distribution of tissues in the body, using electrodes that are placed on the periphery of the imaged area. These electrodes inject currents and measure voltages and from these data, the impedance can be computed. Traditional EIT systems usually inject current patterns in a serial manner which means that the impedance is computed from data collected at slightly different times. It is usually also a time-consuming process. In this paper, we propose a method for collecting data concurrently from all of the current patterns in biomedical applications of EIT. This is achieved by injecting current through all of the current injecting electrodes simultaneously, and measuring all of the resulting voltages at once. The signals from various current injecting electrodes are separated by injecting different frequencies through each electrode. This is called frequency-division multiplexing (FDM). At the voltage measurement electrodes, the voltage related to each current injecting electrode is isolated by using Fourier decomposition. In biomedical applications, using different frequencies has important implications due to dispersions as the tissue's electrical properties change with frequency. Another significant issue arises when we are recording data in a dynamic environment where the properties change very fast. This method allows simultaneous measurements of all the current patterns, which may be important in applications where the tissue changes occur in the same time scale as the measurement. We discuss the FDM EIT method from the biomedical point of view and show results obtained with a simple experimental system.

A novel method for recording neuronal depolarization with recording at 125-825 Hz: implications for imaging fast neural activity in the brain with electrical impedance tomography

Electrical impedance tomography (EIT) is a recently developed medical imaging method which has the potential to produce images of fast neuronal depolarization in the brain. Previous modelling suggested that applied current needed to be below 100 Hz but the signal-to-noise ratio (SNR) recorded with scalp electrodes during evoked responses was too low to permit imaging. A novel method in which contemporaneous evoked potentials are subtracted is presented with current applied at 225 Hz to cerebral cortex during evoked activity; although the signal is smaller than at DC by about 10×, the principal noise from the EEG is reduced by about 1000×, resulting in an improved SNR. It was validated with recording of compound action potentials in crab walking leg nerve where peak changes of -0.2% at 125 and 175 Hz tallied with biophysical modelling. In recording from rat cerebral cortex during somatosensory evoked responses, peak impedance decreases of -0.07 ± 0.006% (mean ± SE) with a SNR of >50 could be recorded at 225 Hz. This method provides a reproducible and artefact free means for recording resistance changes during neuronal activity which could form the basis for imaging fast neural activity in the brain.

Factorization method and its physical justification in frequency-difference electrical impedance tomography

Time-difference electrical impedance tomography (tdEIT) requires two data sets measured at two different times. The difference between them is utilized to produce images of time-dependent changes in a complex conductivity distribution inside the human body. Frequency-difference EIT (fdEIT) was proposed to image frequency-dependent changes of a complex conductivity distribution. It has potential applications in tumor and stroke imaging since it can visualize an anomaly without requiring any time-reference data obtained in the absence of an anomaly. In this paper, we provide a rigorous analysis for the detectability of an anomaly based on a constructive and quantitative physical correlation between a measured fdEIT data set and an anomaly. From this, we propose a new noniterative frequency-difference anomaly detection method called the factorization method (FM) and elaborate its physical justification. To demonstrate its practical applicability, we performed fdEIT phantom imaging experiments using a multifrequency EIT system. Applying the FM to measured frequency-difference boundary voltage data sets, we could quantitatively evaluate indicator functions inside the imaging domain, of which values at each position reveal presence or absence of an anomaly. We found that the FM successfully localizes anomalies inside an imaging domain with a frequency-dependent complex conductivity distribution. We propose the new FM as an anomaly detection algorithm in fdEIT for potential applications in tumor and stroke imaging.

Real-time imaging of subarachnoid hemorrhage in piglets with electrical impedance tomography

Subarachnoid hemorrhage (SAH) is one of the most severe medical emergencies in neurosurgery. Early detection or diagnosis would significantly reduce the rate of disability and mortality, and improve the prognosis of the patients. Although the present medical imaging techniques generally have high sensitivity to identify bleeding, the use of an additional, non-invasive imaging technique capable of continuously monitoring SAH is required to prevent contingent bleeding or re-bleeding. In this study, electrical impedance tomography (EIT) was applied to detect the onset of SAH modeled on eight piglets in real time, with the subsequent process being monitored continuously. The experimental SAH model was introduced by one-time injection of 5 ml fresh autologous arterial blood into the cisterna magna. Results showed that resistivity variations within the brain caused by the added blood could be detected using the EIT method and may be associated not only with the resistivity difference among brain tissues, but also with variations of cerebrospinal fluid dynamics. In conclusion, EIT has unique potential for use in clinical practice to provide invaluable real-time neuroimaging data for SAH after the improvement of electrode design, anisotropic realistic modeling and instrumentation.

The sensitivity of focused electrical impedance measurements

One of the problems with tetrapolar impedance measurements is the lack of spatial sensitivity within the measured volume. In this paper we compare the sensitivity of tetrapolar measurements and the focused impedance measurements (FIM) proposed by Rabbani et al (1999 Ann. New York Acad. Sci. 873 408-20), which give an improved sensitivity profile. Using a previously validated model of sensitivity based on Geselowitz's lead theory, the sensitivity of FIM using eight, six and four electrodes was investigated. All electrode configurations showed a maximum in the average sensitivity of a plane at a depth of one-third of the drive-receive electrode spacing. No difference was found in the sensitivity value of this maximum between electrode configurations having the same drive-receive electrode spacing. The six- and eight-electrode configurations showed negative sensitivity regions down to half of the drive-receive electrode spacing, whilst the four-electrode measurement showed negative sensitivity regions down to one-third of the drive-receive electrode spacing. The single peak in sensitivity beneath the centre of the electrode configuration became dominant at 0.56, 1.4 and 0.14 of the receive electrode spacing for the eight-, six- and four-electrode configurations respectively. Thus, the four-electrode FIM configuration gives a single peak closest to the surface.

Code-division-multiplexed electrical impedance tomography spectroscopy

Electrical impedance tomography uses multiple impedance measurements to image the internal conductivity of an object, such as the human body. Code-division multiplexing is proposed as a new method that can provide simultaneous impedance measurements of the multiple channels. Code division provides clear advantages of a wide frequency range at reduced cost and reduced complexity of sources. A potential drawback is the lack of perfectly orthogonal code sets. This caused an increase of 0.62% in root-mean-square spectral error when two codes were used to record two impedance channels simultaneously on a low-pass filter network. The method described provides images and spectra which are equivalent to the conventional time-multiplexed method, with increases in frequency resolution and measurement speed which may be of benefit in some applications of electrical impedance tomography spectroscopy.

An electrode addressing protocol for imaging brain function with electrical impedance tomography using a 16-channel semi-parallel system

Electrical impedance tomography of brain function poses special problems because applied current is diverted by the resistive skull. In the past, image resolution was maximized with the use of an electrode addressing protocol with widely spaced drive electrode pairs and use of a multiplexer so that many electrode pairs could be flexibly addressed. The purpose of this study was to develop and test an electrode protocol for a 16-channel semi-parallel system which uses parallel recording channels with fixed wiring, the Kyung Hee University (KHU) Mk1. Ten protocols were tested, all addressing pairs of electrodes for recording or current drive, based on recording with a spiral, spiral with suboccipital electrodes (spiral s-o) and zig-zag configurations, and combinations of current injection from electrode pairs at 180 degrees , 120 degrees and 60 degrees . These were compared by assessing the image reconstruction quality of five simulated perturbations in a homogenous model of the human head and of four epileptic foci in an anatomically realistic model in the presence of realistic noise, in terms of localization error, resolution, image distortion and sensitivity in the region of interest. The spiral s-o with current injection at 180 degrees + 120 degrees + 60 degrees gave the best image quality and permitted reconstruction with a localization error of less than 10% of the head diameter. This encourages the view that it might be possible to obtain satisfactory images of focal abnormalities in the human brain with 16 scalp electrodes and improved instrumentation avoiding multiplexers on recording circuits.

A method for recording resistance changes non-invasively during neuronal depolarization with a view to imaging brain activity with electrical impedance tomography

Electrical impedance tomography (EIT) is a recently developed medical imaging method which has the potential to produce images of fast neuronal depolarization in the brain. The principle is that current remains in the extracellular space at rest but passes into the intracellular space during depolarization through open ion channels. As current passes into the intracellular space across the capacitance of cell membranes at higher frequencies, applied current needs to be below 100 Hz. A method is presented for its measurement with subtraction of the contemporaneous evoked potentials which occur in the same frequency band. Neuronal activity is evoked by stimulation and resistance is recorded from the potentials resulting from injection of a constant current square wave at 1 Hz with amplitude less than 25% of the threshold for stimulating neuronal activity. Potentials due to the evoked activity and the injected square wave are removed by subtraction. The method was validated with compound action potentials in crab walking leg nerve. Resistance changes of -0.85+/-0.4% (mean+/-SD) occurred which decreased from -0.97+/-0.43% to -0.46+/-0.16% with spacing of impedance current application electrodes from 2 to 8 mm but did not vary significantly with applied currents of 1-10 microA. These tallied with biophysical modelling, and so were consistent with a genuine physiological origin. This method appears to provide a reproducible and artefact free means for recording resistance changes during neuronal activity which could lead to the long-term goal of imaging of fast neural activity in the brain.

Impedance changes recorded with scalp electrodes during visual evoked responses: implications for Electrical Impedance Tomography of fast neural activity

Electrical Impedance Tomography (EIT) is a recently developed medical imaging method which could enable fast neural imaging in the brain by recording the resistance changes which occur as ion channels open during neuronal depolarization. In published studies in animal models with intracranial electrodes, changes of 0.005 to 3% have been reported but the amplitude of changes in the human is not known. The purpose of this work was to determine if resistance changes could be recorded non-invasively in humans during evoked activity which could form the basis for EIT of fast neural activity. Resistance was recorded with scalp electrodes during 2 Hz pattern visual evoked responses over 10 min using an insensible 1 Hz square wave constant current of 0.1-1 mA. Significant resistance decreases of 0.0010+/-0.0005% (0.30+/-0.15 microV, signal-to-noise ratio (SNR) of 2:1, n=16 recordings over 6 subjects) (mean+/-SE) were recorded. These are in broad agreement with modelling which estimated changes of 0.0039+/-0.0034% (1.03+/-0.75 microV) using an anatomically realistic finite element model. This is the first demonstration of such changes in humans and so encourages the belief that EIT could be used for neural imaging. Unfortunately, the signal-to-noise ratio was not sufficient to permit imaging at present because recording over multiple injection sites needed for imaging would require impractically long recording times. However, in the future, invasive imaging with intracranial electrodes in animal models or humans and improved signal processing or recording may still enable imaging; this would constitute a significant advance in neuroscience technology.